The taxonomic diversity and antibiotic resistance among freshwater bacterial communities in the major water bodies of Korea was examined using 437 penicillin-resistant, and 110 tetracycline-resistant bacterial isolates. Based on 16S rRNA gene sequence analysis, most isolates were assigned to Proteobacteria, which was then followed by Bacteroidetes. Strains of Aeromonas were found as the most abundant penicillin-resistant populations, whereas those affiliated to diverse species including enteric groups were found as the most abundant tetracycline-resistant populations. Most strains exhibited multiple antibiotic resistance, and all tested strains were resistant to penicillin and hygromycin. High levels of resistance were observed for antibiotics acting on cell wall synthesis, whereas low levels were for those acting on DNA replication or transcription in general. It is apparent from this study that penicillin resistance is widespread among environmental bacteria, although the antibiotic has been generally non-detectable in the environment. It is also likely from the taxonomic composition of the resistant communities that various sources including terrestrial animals and humans may contribute to antibiotic resistance in the freshwater environment.

INTRODUCTION

Since the first use of antibiotics in the 1940s, a huge number of antibiotics have been discovered and many of them have been mass produced for pharmaceutical and agricultural purposes. Recent reports indicate the continuous increase of antibiotic production and use worldwide (Sarmah et al. 2006; Hamad 2010). Antibiotics are naturally occurring substances, and thus antibiotic resistance would also be present within the natural microbial community. However, the widespread and extensive use of antibiotics in hospitals, agriculture and aquaculture exerts more selective pressures on environmental microbes, and may accelerate evolution and dissemination of antibiotic resistance. The spread of antibiotic resistance among pathogenic microbes is an obvious example of microbial evolution in action, which can pose a significant problem to humans and livestock. The evolution and dissemination of antibiotic resistance among bacteria in environment has been well reviewed (Baquero & Blazquez 1997; Gomez-Lus 1998; Alonso et al. 2001; Normark & Normark 2002; Baquero et al. 2008; Davies & Davies 2010; Young et al. 2013).

The mechanisms of antibiotic resistance would be diverse, such as alterations of target sites, efflux of antibiotics, or their degradation or modifications, and the target sites for antibiotics include large or small subunit ribosomes, cell membranes, enzymes for nucleic acid synthesis such as DNA or RNA polymerases, components involved in cell wall biosynthesis, or components of metabolic pathways such as that of folate metabolism (D'Costa et al. 2006; Davies & Davies 2010). Mutations or transmission of resistance genes by horizontal gene transfer involving plasmid- or phage-mediated processes are considered the main genetic basis for the evolution and dissemination of resistance genes (Davies & Davies 2010).

The term resistome has been used to describe the total complements of antibiotic resistance in the environment, which is known to span all known classes of natural and synthetic antibiotics (D'Costa et al. 2006; Wright 2007). Antibiotic resistance in various environments can be intrinsic, or due to anthropogenic activities (Davies & Davies 2010; Martinez 2012; Vaz-Moreira et al. 2014). Antibiotic resistance genes from pathogens may comprise a small fraction of the resistome, and resistant genes from non-pathogenic bacteria include those from antibiotic producers and ‘cryptic resistance genes' (Wright 2007). Studies indicate that many of the environmental bacteria are likely resistant to multiple antibiotics (D'Costa et al. 2007; Davies & Davies 2010; Diene & Rolain 2013). Thus, natural antibiotic resistance would no doubt be present in a considerable amount within environmental bacterial communities, although more studies are necessary to understand the nature of such resistance.

There have been some studies on antibiotic resistant bacteria in the natural or artificial freshwater environment (Ash et al. 2002; Lobova et al. 2002; Schwartz et al. 2003; Papadopoulou et al. 2008; Moore et al. 2010a, b; Falcone-Dias et al. 2012; Ozaktas et al. 2012; Marti et al. 2013), and there are a few reviews on the antibiotic resistance in the freshwater environment (Baquero et al. 2008; Kummerer 2009; Vaz-Moreira et al. 2014). However, not much is known on the taxonomic distribution of antibiotic resistant bacteria and their resistance to multiple antibiotics in natural freshwater bodies.

This study primarily focuses on the concentration and taxonomic diversity of antibiotic resistant bacteria using a culture-based approach and also the resistance potentials to various antibiotics in the natural freshwater environment of Korea. Two antibiotics, penicillin and tetracycline, were employed for the detection and isolation of resistant bacteria. For the representative isolates, resistance to multiple antibiotics were tested and compared to examine natural antibiotic resistance among the aquatic freshwater community.

MATERIALS AND METHODS

Samplings

Water samples were collected at 2 month intervals from April to October in 2012. Samples were taken from the surface water at two sites from each of the major inland water bodies of Korea, namely the Keum River (GPS N36.4706/E127.4690, N36.4586/E127.4018), Nakdong River (N36.1126/E128.3982, N36.0502/E128.2341), Lake Soyang and Juam Reservoir (N34.5856/E127.1308, N34.5950/E127.0806), respectively. The water bodies are the major sources of drinking water for each region, and the sampling sites were located in the upstream regions of each water body so as to minimize effects of anthropogenic activities. The water samples were kept at 4 °C and transported to the laboratory for immediate analysis.

Determination of viable counts and isolation of bacteria

A volume of 100 μL from each sample was inoculated onto the Mueller Hinton agar plate (17.5 g casein acid hydrolysate, 2 g beef extract, 1.5 g starch and 17 g agar/L D.W.) supplemented with either penicillin G or tetracycline at 0.1 mg/mL concentration, and incubated at 37 °C for 2 days for viable counts. The counts for each sample were calculated from duplicate plates at two different dilution rates. Variations in viable counts were statistically evaluated using the Student t-test. Significance level was set at P values of <0.05.

Taxonomic identification of isolated bacteria

For isolation of bacteria, single colonies were picked and streaked on fresh Mueller Hinton agar plates. Isolates were subcultured twice to check the purity. Bacterial colonies were suspended in 1 mL 80% extraction buffer and were subjected to boiling for polymerase chain reaction (PCR) amplification of 16S rRNA genes. The 16S rRNA gene of the cells was PCR amplified and purified as described previously (Park et al. 2005). The obtained 16S rRNA gene sequences were identified using the EzBioCloud server (http://www.ezbiocloud.net/eztaxon/) (Kim et al. 2012).

Antibiotic resistance profiling of representative isolates

Selected strains of penicillin- and tetracycline-resistant isolates were tested against tetracycline and penicillin as well as 11 additional antibiotics, namely amikacin, ampicillin, chloramphenicol, ciprofloxacin, erythromycin, hygromycin, gentamycin, kanamycin, novobiocin, rifampicin and trimethoprim (Sigma-Aldrich, USA) at a fixed concentration of 50 μg/mL. Antibiotic containing Mueller Hinton agar plates were prepared, and 10 μL aqueous suspension of strains (A600 = 0.3) were spotted onto the plates. Plates were incubated overnight at 37 °C. Any growth was recorded after the incubation for 18–24 hours.

RESULTS

Viable counts of antibiotic resistance bacteria

The viable counts of penicillin-resistant bacteria in four water bodies over four sampling times were in the range of 27 ± 11 and 3.3 ± 2.8 × 104 CFU/mL (average = 2.7 ± 2.1 × 103), and those of tetracycline-resistant bacteria were between 0 and 99 ± 46 CFU/mL (average = 23 ± 7.4) CFU/mL. The distribution of antibiotic resistant populations differed among water bodies, as the highest average viable count of 9.0 ± 7.0 × 103 CFU/mL was recorded in Keum River for penicillin-resistant bacteria, while that of 38 ± 18 CFU/mL was recorded in Lake Soyang for tetracycline-resistant bacteria (Figure 1). The Juam Reservoir recorded lowest average counts in both cases, as the averages were 3.6 ± 0.76 × 102 CFU/mL for penicillin-resistant bacteria and 12 ± 8.5 CFU/mL for tetracycline-resistant bacteria. The average count of penicillin-resistant bacteria in the lotic waters was 5.1 ± 3.8 × 103 CFU/mL, which was comparable to that in the lentic waters (3.7 ± 0.58 × 102 CFU/mL). There was no statistically significant difference in the average counts of tetracycline-resistant bacteria between the lotic (20 ± 9.2 CFU/mL) and lentic (25 ± 11 CFU/mL) waters. There was no apparent correlation between the counts of penicillin-resistant and tetracycline-resistant bacteria as the correlation coefficient between them was 0.262. Seasonal variations were observed for penicillin-resistant bacteria in the two rivers, as the counts were lowest in April and highest in August, but no clear trend could be observed in lentic waters (Figure 1).
Figure 1

Viable counts of (a) penicillin-resistant and (b) tetracycline-resistant bacteria in the major water bodies.

Figure 1

Viable counts of (a) penicillin-resistant and (b) tetracycline-resistant bacteria in the major water bodies.

Taxonomic composition of antibiotic resistant bacteria

Based on 16S rRNA gene sequence analysis, the penicillin-resistant isolates were assigned to Proteobacteria (94.1% of the total isolates), Bacteroidetes (4.3%), Firmicutes (0.9%) and Actinobacteria (0.7%) (Figure 2(a)). Gammaproteobacteria were the majority, comprising 82.2% of the total isolates, which was then followed by Betaproteobacteria (8.2%) and Alphaproteobacteria (3.7%). The tetracycline-resistant isolates were assigned to two phyla, Proteobacteria (80.0%) and Bacteroidetes (20.0%) (Figure 2(b)). Gammaproteobacteria were again the majority, comprising 68.2% of the total isolates, which was followed by Betaproteobacteria (10.9%) and Alphaproteobacteria (0.9%).
Figure 2

Taxonomic composition of penicillin-resistant (a) and tetracycline-resistant bacteria (b) in the major water bodies.

Figure 2

Taxonomic composition of penicillin-resistant (a) and tetracycline-resistant bacteria (b) in the major water bodies.

Aeromonas (47.1%) and Pseudomonas (19.0%) were found as the major penicillin-resistant genera (Figure 2(c)), and 42 other genera including Acinetobacter (5.7%), Enterobacter (3.0%), Chryseobacterium (2.1%) and Flavobacterium (2.1%) were also found (Table 1). In contrast, 25 genera including Acinetobacter (11.8%), Chryseobacterium (11.8%), Pseudomonas (10.9%), Klebsiella (10.0%), Serratia (8.2%), Elizebethkingia (7.3%), Escherichia (5.5%) and Providencia (5.5%) were found as the main tetracycline-resistant genera (Figure 2(d)). Acinetobacter, Aeromonas, Chryseobacterium, Enterobacter, Klebsiella, Pseudomonas and Serratia were commonly occurring genera for both penicillin and tetracycline-resistant isolates.

Table 1

Generic composition of antibiotic resistant bacteria (%)

  Penicillin-resistant
 
Tetracycline-resistant
 
Site Keum Nakdong Soyang Juam Keum Nakdong Soyang Juam 
No. of isolates 146 115 100 76 64 35 
Acetobacter 0.7        
Acidovorax 2.7 0.9       
Acinetobacter 11.0 7.8   15.6 8.6   
Aeromonas 35.6 29.6 72.0 63.2 3.1 5.7   
Alcaligenes 0.7    4.7    
Aquitalea 0.7  1.0 1.3     
Asticcacaulis    1.3     
Azospirillum  0.9  2.6     
Bacillus 0.7   3.9     
Burkholderia     3.1    
Caulobacter 1.4 0.9  1.3     
Cedecea    1.3     
Chromobacterium 2.7   2.6     
Chryseobacterium 1.4 5.2  1.3 12.5 14.3   
Citrobacter    2.6     
Comamonas 2.7 2.6    2.9   
Cupriavidus  0.9       
Curtobacterium    1.3     
Dickeya 0.7        
Elizabethkingia 0.7    3.1 11.4  100 
Enterobacter 2.1 6.1 1.0 2.6  2.9 11.1  
Escherichia 0.7 0.9   4.7 8.6   
Ewingella       11.1  
Flavimonas         
Flavobacterium 2.1 5.2       
Gluconobacter     1.6    
Haemophilus 2.7  1.0      
Hafnia         
Hydrogenophaga  4.3       
Iodobacter 1.4        
Kinneretia 1.4        
Klebsiella 1.4 2.6   1.6 28.6   
Kluyvera     1.6    
Laribacter     3.1    
Leclercia 1.4        
Massilia 0.7        
Microvirgula    1.3 1.6    
Moraxella       11.1  
Morganella     6.3    
Nocardia    1.3     
Novosphingobium  1.7       
Ochrobactrum  0.9       
Providencia 1.4    9.4    
Pseudomonas 17.1 26.1 22.0 7.9 14.1  8.6   
Ralstonia         
Raoultella 1.4        
Rheinheimera  0.9       
Rhizobium  1.7       
Roseomonas 0.7        
Serratia 0.7 0.9 3.0 1.3 4.7 5.7 44.4  
Shigella     3.1 2.9   
Simplicispira     1.6    
Sphingomonas 0.7        
Staphylococcus         
Streptomyces    1.3     
Variovorax    1.3     
Vogesella 0.7    3.1    
Wautersiella     1.6    
Yersinia 1.4        
Yokenella 0.7      22.2  
  Penicillin-resistant
 
Tetracycline-resistant
 
Site Keum Nakdong Soyang Juam Keum Nakdong Soyang Juam 
No. of isolates 146 115 100 76 64 35 
Acetobacter 0.7        
Acidovorax 2.7 0.9       
Acinetobacter 11.0 7.8   15.6 8.6   
Aeromonas 35.6 29.6 72.0 63.2 3.1 5.7   
Alcaligenes 0.7    4.7    
Aquitalea 0.7  1.0 1.3     
Asticcacaulis    1.3     
Azospirillum  0.9  2.6     
Bacillus 0.7   3.9     
Burkholderia     3.1    
Caulobacter 1.4 0.9  1.3     
Cedecea    1.3     
Chromobacterium 2.7   2.6     
Chryseobacterium 1.4 5.2  1.3 12.5 14.3   
Citrobacter    2.6     
Comamonas 2.7 2.6    2.9   
Cupriavidus  0.9       
Curtobacterium    1.3     
Dickeya 0.7        
Elizabethkingia 0.7    3.1 11.4  100 
Enterobacter 2.1 6.1 1.0 2.6  2.9 11.1  
Escherichia 0.7 0.9   4.7 8.6   
Ewingella       11.1  
Flavimonas         
Flavobacterium 2.1 5.2       
Gluconobacter     1.6    
Haemophilus 2.7  1.0      
Hafnia         
Hydrogenophaga  4.3       
Iodobacter 1.4        
Kinneretia 1.4        
Klebsiella 1.4 2.6   1.6 28.6   
Kluyvera     1.6    
Laribacter     3.1    
Leclercia 1.4        
Massilia 0.7        
Microvirgula    1.3 1.6    
Moraxella       11.1  
Morganella     6.3    
Nocardia    1.3     
Novosphingobium  1.7       
Ochrobactrum  0.9       
Providencia 1.4    9.4    
Pseudomonas 17.1 26.1 22.0 7.9 14.1  8.6   
Ralstonia         
Raoultella 1.4        
Rheinheimera  0.9       
Rhizobium  1.7       
Roseomonas 0.7        
Serratia 0.7 0.9 3.0 1.3 4.7 5.7 44.4  
Shigella     3.1 2.9   
Simplicispira     1.6    
Sphingomonas 0.7        
Staphylococcus         
Streptomyces    1.3     
Variovorax    1.3     
Vogesella 0.7    3.1    
Wautersiella     1.6    
Yersinia 1.4        
Yokenella 0.7      22.2  

At the species level, the closest matches, not species identity, were searched and recorded since species assignment was not possible using 16S rRNA gene analysis alone. The strains affiliated to Aeromonas ichthiosmia (10.1%), Aeromonas popoffii (9.6%) and Aeromonas veronii (8.2%) were found as the most abundant penicillin-resistant groups. The strains affiliated to Aeromonas hydrophila (4.3%), Pseudomonas koreensis (4.3%), Aeromonas jandaei (3.2%), Aeromonas media (2.7%) and Aeromonas punctata subsp. caviae (2.7%) were also found as the common penicillin-resistant groups. In contrast, the strains affiliated to Elizabethkingia anopheles (7.3%), Acinetobacter bouvetii (4.5%), Chryseobacterium indologenes (4.5%), Escherichia coli (4.5%), Klebsiella pneumonia subsp. ozaenae (4.5%), Serratia marcescens (4.5%), Chryseobacterium joostei (3.6%) and Serratia nematodiphila (3.6%) were found as the most abundant tetracycline-resistant groups.

Antibiotic resistance profile of representative isolates

Selected penicillin-resistant and tetracycline-resistant strains were tested for antibiotic resistance against 12 other antibiotics (Tables 2 and 3). Strains within the same genera generally exhibited similar resistance profiles. The penicillin-resistant strains were least resistant to ciprofloxacin and rifampicin as only 4.7% of the tested strains were resistant to each of these antibiotics. The tetracycline-resistant strains were least resistant to ciprofloxacin (6.7%) and gentamycin (13.3%). Both the penicillin- and tetracycline-resistant strains were highly resistant to penicillin, hygromycin and ampicillin and erythromycin. Notably, all tested strains were resistant to penicillin and hygromycin. The penicillin-resistant strains were also resistant to an average of 4.2 additional antibiotics among 12 tested ones, and the tetracycline-resistant strains were also resistant to an average of 5.9 additional antibiotics.

Table 2

Antibiotic resistance profiles of penicillin-resistant isolates

    Antibioticsa
 
Strain Identification 10 11 12 
AUNP27 Acinetobacter beijerinckii − − − − − − − − − 
AUDP59 Acinetobacter calcoaceticus − − − − − − (+) − − − 
AUDP15 Acinetobacter johnsonii − − − − − − − ND − − − 
AUDP13 Acinetobacter junii − − − − − − − − − − − 
AUDP20 Acinetobacter junii − − − − − − − − − − − 
AUDP42 Acinetobacter junii − − − − − − − − − − − 
AUNP06 Acinetobacter junii − − − − − − − − − 
AUNP25 Acinetobacter junii − − − − − − − − 
AUNP26 Acinetobacter junii − − − − − − − − − − − 
AUDP40 Acinetobacter nosocomialis − − − − − − (+) − − 
AUDP12 Acinetobacter parvus − − − − − − − − − 
AUNP18 Acinetobacter parvus − − − − − − − − − − 
AUDP02 Acinetobacter tandoii − − − − − − − ND − − 
OCDP14 Aeromonas jandaei (+) − − − − − − − − 
JUN02 Aeromonas media − − − − − − − − 
OCDP12 Aeromonas popoffii − − − − − − − − − − − 
OCDP13 Aeromonas punctata subsp. caviae (+) − − −  − 
OCNP03 Aeromonas veronii − − − − − (+) − − − 
AUDP25 Alcaligenes faecalis subsp. faecalis (+) − − − − 
AUDP30 Chryseobacterium aestuarii − − − − − 
JUN01 Chryseobacterium arthrosphaerae − − − − 
OCDP15 Chryseobacterium vietnamense (+) − − − − − − 
AUNP23 Comamonas aquatica − − − − − − (+) − − − 
AUNP16 Comamonas thiooxydans − − − − − − (+) − − − 
AUDP61 Enterobacter asburiae − − − − − − − − − 
OCNP21 Enterobacter asburiae − − − − − − (+) − − 
AUDP46 Enterobacter ludwigii − − − − − − (+) − − 
OCDP16 Enterobacter ludwigii − − − − − − (+) − − 
AUDP57 Enterobacter mori − − − − − − − − 
OCNP07 Escherichia coli − (+) − − − 
AUDP54 Klebsiella pneumoniae subsp. ozaenae − − − − − − − − − 
AUDP36 Klebsiella variicola − − − − − − − (+) − 
AUNP32 Klebsiella variicola − − − − − − − − − 
OCNP02 Pseudomonas alcaligenes − − − − − − − − 
OCNP09 Pseudomonas alcaligenes − − − −  − − − − − 
APN27 Pseudomonas chlororaphis subsp. piscium − − − − − − 
AUNP09 Pseudomonas geniculata (+) − − 
APN06 Pseudomonas koreensis − − − − − − − − 
OCDP01 Pseudomonas parafulva − − − − − − − − − 
OCDP02 Pseudomonas taiwanensis − − − − − − 
JUD01 Raoultella ornithinolytica − − − 
OCDP32 Roseomonas cervicalis − − − − − − − − − 
AUNP20 Serratia marcescens subsp. sakuensis − − − − − − 
OCDP08 Serratia nematodiphila (+) − − − − − − − 
AUDP11 Yokenella regensburgei − − − − − − (+) − − 
AUNP08 Yokenella regensburgei − − − − − − ND − − − 
 Overall resistance to each antibiotic (%) 18.6 100 14.0 27.9 76.7 27.9 4.7 4.8 73.1 20.9 18.6 32.6 
    Antibioticsa
 
Strain Identification 10 11 12 
AUNP27 Acinetobacter beijerinckii − − − − − − − − − 
AUDP59 Acinetobacter calcoaceticus − − − − − − (+) − − − 
AUDP15 Acinetobacter johnsonii − − − − − − − ND − − − 
AUDP13 Acinetobacter junii − − − − − − − − − − − 
AUDP20 Acinetobacter junii − − − − − − − − − − − 
AUDP42 Acinetobacter junii − − − − − − − − − − − 
AUNP06 Acinetobacter junii − − − − − − − − − 
AUNP25 Acinetobacter junii − − − − − − − − 
AUNP26 Acinetobacter junii − − − − − − − − − − − 
AUDP40 Acinetobacter nosocomialis − − − − − − (+) − − 
AUDP12 Acinetobacter parvus − − − − − − − − − 
AUNP18 Acinetobacter parvus − − − − − − − − − − 
AUDP02 Acinetobacter tandoii − − − − − − − ND − − 
OCDP14 Aeromonas jandaei (+) − − − − − − − − 
JUN02 Aeromonas media − − − − − − − − 
OCDP12 Aeromonas popoffii − − − − − − − − − − − 
OCDP13 Aeromonas punctata subsp. caviae (+) − − −  − 
OCNP03 Aeromonas veronii − − − − − (+) − − − 
AUDP25 Alcaligenes faecalis subsp. faecalis (+) − − − − 
AUDP30 Chryseobacterium aestuarii − − − − − 
JUN01 Chryseobacterium arthrosphaerae − − − − 
OCDP15 Chryseobacterium vietnamense (+) − − − − − − 
AUNP23 Comamonas aquatica − − − − − − (+) − − − 
AUNP16 Comamonas thiooxydans − − − − − − (+) − − − 
AUDP61 Enterobacter asburiae − − − − − − − − − 
OCNP21 Enterobacter asburiae − − − − − − (+) − − 
AUDP46 Enterobacter ludwigii − − − − − − (+) − − 
OCDP16 Enterobacter ludwigii − − − − − − (+) − − 
AUDP57 Enterobacter mori − − − − − − − − 
OCNP07 Escherichia coli − (+) − − − 
AUDP54 Klebsiella pneumoniae subsp. ozaenae − − − − − − − − − 
AUDP36 Klebsiella variicola − − − − − − − (+) − 
AUNP32 Klebsiella variicola − − − − − − − − − 
OCNP02 Pseudomonas alcaligenes − − − − − − − − 
OCNP09 Pseudomonas alcaligenes − − − −  − − − − − 
APN27 Pseudomonas chlororaphis subsp. piscium − − − − − − 
AUNP09 Pseudomonas geniculata (+) − − 
APN06 Pseudomonas koreensis − − − − − − − − 
OCDP01 Pseudomonas parafulva − − − − − − − − − 
OCDP02 Pseudomonas taiwanensis − − − − − − 
JUD01 Raoultella ornithinolytica − − − 
OCDP32 Roseomonas cervicalis − − − − − − − − − 
AUNP20 Serratia marcescens subsp. sakuensis − − − − − − 
OCDP08 Serratia nematodiphila (+) − − − − − − − 
AUDP11 Yokenella regensburgei − − − − − − (+) − − 
AUNP08 Yokenella regensburgei − − − − − − ND − − − 
 Overall resistance to each antibiotic (%) 18.6 100 14.0 27.9 76.7 27.9 4.7 4.8 73.1 20.9 18.6 32.6 

a1, amikacin; 2, hygromycin; 3, gentamycin; 4, kanamycin; 5, ampicillin; 6, tetracycline; 7, ciprofloxacin; 8, rifampicin; 9, erythromycin; 10, novobiocin; 11, chloramphenicol; 12, trimethoprim. +, positive; −, negative; (+), weak; ND, not detected.

Table 3

Antibiotic resistance profiles of tetracycline-resistant isolates

    Antibioticsa
 
Strain Identification 10 11 12 
AUNT08 Acinetobacter guillouiae − − − − − − − − − 
AUNT04 Acinetobacter tandoii − − − − − − − − − 
AUNT05 Acinetobacter tandoii − − − − − − − − − 
AUDT09 Alcaligenes faecalis subsp. Faecalis (+) − − − − − 
AUDT16 Alcaligenes faecalis subsp. Faecalis (+) − − − − 
AUDT10 Alcaligenes faecalis subsp. parafaecalis (+) − − − − − 
OCDT03 Chryseobacterium arthrosphaerae − − − − 
AUNT11 Chryseobacterium indologenes − − − − − 
AUNT15 Comamonas testosteroni − − − − − 
OCNT01 Enterobacter ludwigii − − − − − − − − − 
AUDT19 Escherichia coli − − − − − − (+) − 
AUNT21 Escherichia coli − − − − − − 
AUNT20 Escherichia coli − − − − − − − 
AUNT06 Escherichia fergusonii − − − (+) − − − 
AUNT01 Klebsiella oxytoca − − − − − − 
AUNT14 Klebsiella pneumoniae subsp. ozaenae − − − − − − − 
AUNT18 Klebsiella pneumoniae subsp. ozaenae − − − − (+) − (+) − 
AUNT19 Klebsiella pneumoniae subsp. ozaenae − − − − − − (+) − 
AUNT22 Klebsiella pneumoniae subsp. ozaenae − − − − − − (+) − 
OCNT03 Klebsiella pneumoniae subsp. ozaenae − − − − − − − 
AUNT02 Klebsiella variicola − − − − (+) − − − 
OCNT02 Klebsiella variicola − − − − − − − 
AUDT33 Morganella morganii subsp. Morganii − − − − − − 
AUDT11 Morganella morganii subsp. Sibonii − − − − − − 
AUDT13 Morganella morganii subsp. Sibonii (+) − − − − 
AUDT05 Providencia alcalifaciens − − − − − − − 
OCDT02 Providencia alcalifaciens − − − − − − − 
AUDT14 Providencia stuartii − − − − − − 
AUNT12 Pseudomonas geniculata (+) − − − − 
AUNT03 Serratia marcescens subsp. marcescens − − − − − − 
AUNT17 Serratia nematodiphila (+) − − − (+) − − 
AUDT20 Shigella flexneri − − − − 
AUDT21 Shigella flexneri − − − − − − 
 Overall resistance to each antibiotic (%) 30.0 100 13.3 16.7 86.7 100 6.7 20.0 93.3 36.7 36.7 46.7 
    Antibioticsa
 
Strain Identification 10 11 12 
AUNT08 Acinetobacter guillouiae − − − − − − − − − 
AUNT04 Acinetobacter tandoii − − − − − − − − − 
AUNT05 Acinetobacter tandoii − − − − − − − − − 
AUDT09 Alcaligenes faecalis subsp. Faecalis (+) − − − − − 
AUDT16 Alcaligenes faecalis subsp. Faecalis (+) − − − − 
AUDT10 Alcaligenes faecalis subsp. parafaecalis (+) − − − − − 
OCDT03 Chryseobacterium arthrosphaerae − − − − 
AUNT11 Chryseobacterium indologenes − − − − − 
AUNT15 Comamonas testosteroni − − − − − 
OCNT01 Enterobacter ludwigii − − − − − − − − − 
AUDT19 Escherichia coli − − − − − − (+) − 
AUNT21 Escherichia coli − − − − − − 
AUNT20 Escherichia coli − − − − − − − 
AUNT06 Escherichia fergusonii − − − (+) − − − 
AUNT01 Klebsiella oxytoca − − − − − − 
AUNT14 Klebsiella pneumoniae subsp. ozaenae − − − − − − − 
AUNT18 Klebsiella pneumoniae subsp. ozaenae − − − − (+) − (+) − 
AUNT19 Klebsiella pneumoniae subsp. ozaenae − − − − − − (+) − 
AUNT22 Klebsiella pneumoniae subsp. ozaenae − − − − − − (+) − 
OCNT03 Klebsiella pneumoniae subsp. ozaenae − − − − − − − 
AUNT02 Klebsiella variicola − − − − (+) − − − 
OCNT02 Klebsiella variicola − − − − − − − 
AUDT33 Morganella morganii subsp. Morganii − − − − − − 
AUDT11 Morganella morganii subsp. Sibonii − − − − − − 
AUDT13 Morganella morganii subsp. Sibonii (+) − − − − 
AUDT05 Providencia alcalifaciens − − − − − − − 
OCDT02 Providencia alcalifaciens − − − − − − − 
AUDT14 Providencia stuartii − − − − − − 
AUNT12 Pseudomonas geniculata (+) − − − − 
AUNT03 Serratia marcescens subsp. marcescens − − − − − − 
AUNT17 Serratia nematodiphila (+) − − − (+) − − 
AUDT20 Shigella flexneri − − − − 
AUDT21 Shigella flexneri − − − − − − 
 Overall resistance to each antibiotic (%) 30.0 100 13.3 16.7 86.7 100 6.7 20.0 93.3 36.7 36.7 46.7 

a1, amikacin; 2, hygromycin; 3, gentamycin; 4, kanamycin; 5, ampicillin; 6, penicillin; 7, ciprofloxacin; 8, rifampicin; 9, erythromycin; 10, novobiocin; 11, chloramphenicol; 12, trimethoprim. +, positive −, negative; (+), weak.

The strains of Alcaligenes, Chryseobacterium and Shigella generally exhibited the broadest multiple antibiotic resistance, which was then followed by Escherichia, Serratia and Pseudomonas for both antibiotic resistant populations. As for individual strains, however, strain AUNP09, a penicillin-resistant strain affiliated to Pseudomonas geniculata, and strain JUD01, a penicillin-resistant strain affiliated to Raoultella ornithinolytica, were found as the two broadest multiple antibiotic resistant bacteria, resistant to 10 and nine additional antibiotics, respectively (Table 2). In addition, those affiliated to E. coli, Chryseobacterium arthrosphaerae and Alcaligenes faecalis subsp. faecalis were found to exhibit the broadest multiple antibiotic resistance among penicillin-resistant isolates. Among the tetracycline-resistant strains, strain AUDT16 affiliated to Alcaligenes faecalis, OCDT03 affiliated to Chryseobacterium arthrosphaerae, AUDT13 affiliated to Morganella morganii subsp. sibonii, AUNT12 affiliated to Pseudomonas geniculate, and AUDT20 affiliated to Shigella flexneri exhibited the broadest multiple antibiotic resistance (resistant to eight additional antibiotics) among tetracycline-resistant isolates (Table 3).

DISCUSSION

The low viable counts of tetracycline-resistant bacteria compared to the penicillin-resistant bacteria indicate that the tetracycline-resistant populations, exhibiting higher degree of multiple antibiotic resistance, constitute only small proportions within the total communities. This is notable as tetracyclines are used as the major veterinary pharmaceuticals and its presence in detectable concentration in freshwater environment has been reported, while penicillin has been virtually non-detectable in nationwide surveys (Kim et al. 2008; Son & Jang 2011). Tetracycline is known as a relatively resilient antibiotic to biodegradation, whereas penicillin is known to be subject to biodegradation more readily than other antibiotics (Gartiser et al. 2007; Son & Jang 2011). Another notable finding is that the antibiotic resistant populations in river waters are more diverse in taxonomic compositions than those in lake waters. Moreover, some taxa, namely Acinetobacter, Chryseobacterium, Comamonas, Klebsiella, Escherichia and Flavobacterium were found only in river waters in this study (Table 1). These observations altogether imply that penicillin resistance is widespread in the river environment.

Members of Proteobacteria, in particular Gammaproteobacteria, are apparently the main source for both penicillin and tetracycline-resistance. The prevalence of Proteobacteria is in line with previous observations in aquatic environment (Ash et al. 2002; Falcone-Dias et al. 2012; Sigala & Unc 2013; Young et al. 2013). Although the composition at genus level was different between the penicillin- and tetracycline-resistant populations, the presence of the genus Pseudomonas as the main constituent was common for both. In addition to Pseudomonas, Acinetobacter, Aeromonas, Chryseobacterium, Enterobacter, Escherichia, Klebsiella and Serratia constituted the main antibiotic resistant community, each of which has also been reported as a main antibiotic resistant population in the bacterial community of natural or artificial aquatic environments, for example rivers (Acinetobacter, Alcaligenes, Citrobacter, Enterobacter, Pseudomonas and Serratia), swimming pools (Pseudomonas, Leuconostoc, Staphylococcus, Chryseobacterium, Aeromonas, Enterobacter, Klebsiella and Ochrobactrum), wastewater systems (Pseudomonas, Shewanella, Escherichia, Acinetobacter, Arcobacter and Yersinia), and bottled mineral water (Arthrobacter, Acidovorax, Ralstonia, Curvibacter, Acidovorax and Hydrogenophaga) (Ash et al. 2002; Papadopoulou et al. 2008; Falcone-Dias et al. 2012; Sigala & Unc 2013; Young et al. 2013). Based on those previous studies and this study, the eight main genera can be considered to comprise the ‘core resistome’ in the natural freshwater environment. Alcaligenes, Comamonas, Elizabethkingia, Microvirgula, Providencia and Yokenella were also common constituents but in minor proportions. The isolates belonging to Enterobacteriaceae comprised 40.1% of the total tetracycline-resistant bacteria, but only 8.9% of the total penicillin-resistant bacteria. A small overlap was found between the two antibiotic resistant populations, as 25 species out of 161 species, i.e. species of Acinetobacter, Aeromonas, Alcaligenes, Chryseobacterium, Comamonas, Elizabethkingia, Enterobacter, Escherichia, Klebsiella, Microvirgula, Providencia, Pseudomonas, Serratia and Yokenella, were recovered in both antibiotic resistant populations.

Among the species identified in this study, those classified as risk group category 2 pathogens defined by the Korea Center for Disease Control and Prevention (www.cdc.go.kr) include Acinetobacter baumanii (tetracycline-resistant), Aeromonas hydrophila (penicillin-resistant), Aeromonas punctata subsp. punctata (penicillin-resistant), species of Klebsiella (penicillin and/or tetracycline-resistant), Moraxella osloensis (tetracycline-resistant), Pseudomonas aeruginosa (tetracycline-resistant) and Shigella flexneri (tetracycline-resistant). Apart from A. hydrophila, all other species were detected at low numbers in single, or only a few, occasions. No species classified as risk group 3 was detected. Among the ESKAPE pathogens (Rice 2008), A. baumanii, P. aeruginosa, Klebsiella pneumoniae, and species of Enterobacter, but not Enterococcus faecium and Staphylococcus aureus, were detected.

The intrinsic resistance of pathogenic microbes to antibiotics has been previously studied (Fajardo et al. 2008; Alvarez-Ortega et al. 2011), but not much is known on the resistance of environmental strains. Through the genome analysis, the pathogenic members of Pseudomonas, Acinetobacter and Aeromonas are known to contain the genetic elements that may render intrinsic resistance to antibiotics (Fournier et al. 2006; Diene & Rolain 2013), although it is not clear to what extent such genetic elements are distributed among environmental bacteria. Of the 55 genera confirmed in this study, Aquitalea, Asticcacaulis, Curtobacterium, Iodobacter, Kinneretia, Microvirgula, Simplicispira and Vogesella are generally known as environmental organisms, and antibiotic resistance for these taxa has not been reported before. However, most of the main taxa identified in this study have been reported as isolates from human or animal sources, for example, species of Aeromonas and other members of Gammaproteobacteria (Brenner & Farmer III 2005), and also species belonging to the family Enterobacteriaceae (Martin-Carnahan & Joseph 2005).

The strains affiliated to Alcaligenes faecalis, Chryseobacterium arthrosphaerae, and Pseudomonas geniculata were among the top broad-spectrum multiple antibiotic resistant bacteria in both resistant populations. Enterobacterial strains together with Alcaligenes, Chryseobacterium and Pseudomonas exhibited high levels of multiple antibiotic resistance in general. This observation is clearly comparable to the multiple antibiotic resistant species identified in other studies on artificial environment, for example swimming pools (Papadopoulou et al. 2008), bottled mineral water (Falcone-Dias et al. 2012), or wastewater (Sigala & Unc 2013).

The resistance profiles of the two antibiotic resistant populations to other antibiotics were generally similar, but tetracycline-resistant strains exhibited broader multiple antibiotic resistance (Figure 3). Interestingly, the majority of the closest matches to multiple resistant strains, namely Aeromonas punctata subsp. caviae, two subspecies of Alcaligenes faecalis, Chryseobacterium arthrosphaerae, Chryseobacterium indologenes, E. coli, Morganella morganii subsp. sibonii, Raoultella ornithinolytica, Serratia nematodiphila and Shigella flexneri, are known as fecal or human- or animal-associated bacteria (Brenner & Farmer III 2005; Busse & Auling 2005; Martin-Carnahan & Joseph 2005; Kämpfer et al. 2010; Bernardet et al. 2011). In most cases, none of these taxa were among the major constituents of both antibiotic resistant communities, although most of them appeared as minor constituents in both communities.
Figure 3

Antibiotic resistance profile of main bacterial genera according to taxonomic classification and mechanisms of action. (a) Penicillin-resistant bacteria; (b) tetracycline-resistant bacteria. Darkness indicates degrees of resistance. Alpha, Beta and Gamma groups indicate Alpha-, Beta- and Gammaproteobacteria, respectively. Ami, amikacin; Gen, gentamycin; Kan, kanamycin; Tet, tetracycline; Hyg, hygromycin; Ery, erythromycin; Chl, chloramphenicol; Amp, ampicillin; Cip, ciprofloxacin; Nov, novobiocin; Rif, rifampicin; Tri, trimethoprim.

Figure 3

Antibiotic resistance profile of main bacterial genera according to taxonomic classification and mechanisms of action. (a) Penicillin-resistant bacteria; (b) tetracycline-resistant bacteria. Darkness indicates degrees of resistance. Alpha, Beta and Gamma groups indicate Alpha-, Beta- and Gammaproteobacteria, respectively. Ami, amikacin; Gen, gentamycin; Kan, kanamycin; Tet, tetracycline; Hyg, hygromycin; Ery, erythromycin; Chl, chloramphenicol; Amp, ampicillin; Cip, ciprofloxacin; Nov, novobiocin; Rif, rifampicin; Tri, trimethoprim.

Ciprofloxacin and novobiocin, both known as DNA gyrase inhibitors, rendered least resistance among the tested antibiotics, together with rifampicin, known as an RNA polymerase inhibitor (Figure 3). In contrast, most strains were resistant to penicillin and ampicillin, known as cell wall synthesis inhibitors. Antibiotics known to act on translation levels caused varying degrees of resistance. For example, a low degree of resistance was observed against aminoglycosides (amikacin, gentamycin and kanamycin) to both populations, whereas a high degree of resistance was observed against erythromycin. The degree of antibiotic resistance by the action mechanism was in the order of RNA polymerase inhibitor and DNA gyrase inhibitors, translation inhibitors, metabolic inhibitor (tetrahydrofolate synthesis), and cell wall synthesis inhibitors. The degree of resistance by structural category of antibiotics was in the order of macrolide (erythromycin) and penicillins, trimethoprim, phenocol (chloramphenicol) and aminocoumarin (novobiocin), aminoglycosides, rifampicin, and quinolone (ciprofloxacin) (Figure 3). In general, this pattern of resistance agrees well with a previous observation by Moore et al. (2010a, b). The high degree of resistance to penicillins by antibiotic resistant bacteria is also in line with previous observations (Moore et al. 2010a, b; Mudryk et al. 2010; Walsh & Duffy 2013).

CONCLUSIONS

Through this study, resistance to antibiotics among diverse groups of planktonic bacteria in freshwater environments was confirmed. The bacterial taxa encompass environmental strains for which antibiotic resistance or pathogenicity has not been reported, as well as potential pathogens and also those well known for resistance. The level of viable counts of penicillin-resistant bacteria are notable, since penicillins have been virtually non-detectable in the freshwater environments of Korea. In addition, the low proportion of enteric bacteria in penicillin-resistant populations compared to that in tetracycline-resistant populations also implies the presence of the natural antibiotic resistant bacterial community in the aquatic environment.

Members of Pseudomonas were found as a prominent antibiotic resistant group for both antibiotics, and thus obviously forming the core freshwater resistome, together with other common genera including Acinetobacter, Aeromonas, Chryseobacterium, Klebsiella and Serratia. However, variations were found at species level, and no particular species could be identified as the core.

The resistance to multiple antibiotics having different action mechanisms may be intrinsic among some environmental microbes in general. However, the strains exhibiting broad multiple antibiotic resistance were mostly affiliated to species that have been frequently found in association with human or animal sources, and thus the extensive study on the multiple antibiotic resistant strains might provide an insight on the effect of anthropogenic activities to the microbial community in the aquatic environment.

ACKNOWLEDGEMENTS

This research was supported by the National Institute of Environmental Research (grant no. 2012-1730) of the Ministry of Environment, Korea, and by the CNU Research Grant (grant no. 2014-0784-01) of Chungnam National University. TWK, YC, JHH and SBK also acknowledge financial support from the Brain Korea 21 Plus Program funded by the National Research Foundation of Korea (NRF) of the Ministry of Education, Korea.

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