Prevalence and Diversity of Antibiotic Resistance Genes in Swedish Aquatic Environments Impacted by Household and Hospital Wastewater

Abstract

Antibiotic-resistant Enterobacteriaceae and non-lactose fermenting Gram-negative bacteria are a major cause of nosocomial infections. Antibiotic misuse has fueled the worldwide spread of resistant bacteria and the genes responsible for antibiotic resistance (ARGs). There is evidence that ARGs are ubiquitous in non-clinical environments, especially those affected by anthropogenic activity. However, the emergence and primary sources of ARGs in the environment of countries with strict regulations for antibiotics usage are not fully explored. The aim of the present study was to evaluate the repertoire of ARGs of culturable Gram-negative bacteria from directionally connected sites from the hospital to the wastewater treatment plant (WWTP), and downstream aquatic environments in central Sweden. The ARGs were detected from genomic DNA isolated from a population of selectively cultured coliform and Gram-negative bacteria using qPCR. The results show that hospital wastewater was a reservoir of several class B β-lactamase genes such as bla _IMP-1 , bla _IMP-2, and bla _OXA-23, however, most of these genes were not observed in downstream locations. Moreover, β-lactamase genes such as bla _OXA-48, bla _CTX-M-8, and bla _SFC-1, bla _{V IM-1}, and bla _{V IM-13} were detected in downstream river water but not in the WWTP. The results indicate that the WWTP and hospital wastewaters were reservoirs of most ARGs and contribute to the diversity of ARGs in associated natural environments. However, this study suggests that other factors may also have minor contributions to the prevalence and diversity of ARGs in natural environments.

Keywords: VIM-1; antimicrobial resistance gene co-occurrence; carbapenemase; enterobacteriaceae; extended-spectrum beta-lactamase; surface water; urban wastewater.

FIGURE 1

Illustration of the sample sites along the wastewater system in Örebro city, Sweden. Wastewater from households, industries, and the hospital are transported to the wastewater treatment plant (WWTP) located along the Svartån river downstream of Örebro City. Svartån River flows through the city and exits into Hjälmaren Lake. Sample locations are indicated as orange boxes. Wastewater samples were collected from hospital effluent (H), and incoming wastewater (IW), and treated effluent wastewater (EW) at the WWTP. Environmental water samples were collected from Svartån River upstream of Örebro city (UR), Svartån River downstream of WWTP (RR) and Hjälmaren Lake (RL), which is one nautical mile downstream of RR.

FIGURE 2

Levels of E. coli and other coliform bacteria in wastewaters and recipient environmental waters in Örebro Sweden. Symbols in the figure represent the following: H, hospital wastewater; IW, incoming sewage water from the wastewater treatment plant; EW, effluent wastewater from the wastewater treatment plant; UR, surface water from Svartån river upstream of Örebro city; RR, surface water from Svartån river water downstream of wastewater treatment plant; and RL, surface water from Hjälmaren lake downstream of wastewater treatment plant. Statistical significance is shown by ^∗ for P ≤ 0.05, ^∗∗ for P ≤ 0.01, and ^∗∗∗ for P ≤ 0.001 as determined by Student’s t-test. Error bars represent the standard deviation of three biological replicates (n = 3).

FIGURE 3

The number of antibiotic resistance genes (ARGs) detected from wastewater and environmental waters in Örebro Sweden. Wastewater samples were taken from hospital effluent (H), incoming wastewater to WWTP (IW), and effluent wastewater (EW). Environmental water samples were taken from Svartån River upstream of Örebro city (UR), Svartån River downstream of WWTP (RR) and Hjälmaren Lake (HF), which is one nautical mile downstream of RR. The number at the top of each bar indicates the total number of detected ARGs in a particular location. MDR indicates multi-drug resistance efflux pump genes. M.L.S indicates genes conferring resistance to either of the macrolide, lincosamide, and streptogramin B antibiotics.

FIGURE 4

Venn diagram of antibiotic-resistance genes detected in the hospital wastewater, wastewater treatment plant (WWTP), and recipient river and lake waters. The number in the bracket indicates the total number of genes detected from a particular sample type. The results from all six samples were divided into three sets based on the sample type; hospital wastewater, wastewater from WWTP (combined incoming and effluent wastewater), and aquatic environments (upstream river and downstream river and lake water). The genes detected in all sample types are listed in the gray-shaded box. Carbapenemase genes are highlighted in red color.

FIGURE 5

Non-metric multidimensional scaling plot displaying similarities between ARG profiles of hospital wastewater, WWTP wastewater, and environmental water samples. Three replicate samples taken from each location are represented by 1, 2, and 3 after the symbol. Symbols in the figure represent the following: H, Hospital wastewater; IW, Incoming sewage water from the wastewater treatment plant; EW, effluent wastewater from the wastewater treatment plant; UR, surface water from Svartån river upstream of Örebro city; RR, surface water from Svartån river water downstream of the wastewater treatment plant; and RL, surface water from Hjälmaren lake downstream of the wastewater treatment plant. A low-stress value (0.09) indicates a good quality ordination.

FIGURE 6

Network plot showing co-occurrence of ARGs detected in wastewater and environmental water samples in Örebro, Sweden. The co-occurrence network is based on a correlation matrix among detected ARGs using Spearman’s rank correlation. Only correlations with a high correlation coefficient (p ≥ 0.8) and low P-value (P-value 0.01) are shown. The node size represents the number of connections with other ARGs. The thickness of the edge is proportional to the Spearman’s correlation coefficient (p) of the connection. The co-occurrence network is further divided into sub-networks (modules) based on modularity class (modularity index = 0.477). Genes in gray color do not show a significant correlation.