Occurrence, composition and risk assessment of antibiotics in soils from Kenya, Africa

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1 Ecotoxicology DOI /s Occurrence, composition and risk assessment of antibiotics in soils from Kenya, Africa Yuyi Yang 1,2 Anita Awino Owino 1,2,3 Yan Gao 4 Xue Yan 1,2 Chen Xu 1,2,3 Jun Wang 1,2 Accepted: 11 May 2016 Springer Science+Business Media New York 2016 Abstract Antibiotics can accumulate in soils via different ways, which may pose serious threat to ecological environment of soil and quality of agricultural products. In this study, the occurrence of 12 antibiotics including four sulfonamides (SAs), four tetracyclines (TETs) and four fluoroquinolones (FQs) was investigated in soils from four sampling sites of Kenya (Mai Mahiu, Narok, Mount Suswa Conservancy, and Juja), Africa. The soils in suburban area of Narok had the highest average concentrations of total 12 antibiotics with an average value of lg kg -1 dw (dry weight), followed by Mai Mahiu (26.70 lg kg -1 dw), Juja (24.41 lg kg -1 dw) and Mount Suswa Conservancy (12.21 lg kg -1 dw). Sulfamethoxazole, sulfamethazine, oxytetracycline, and enrofloxacin were identified as the main antibiotics polluted in soils. Total organic carbon may influence the distribution of SAs in Narok and FQs in Juja. Ecological risk analysis based on the risk quotient showed that SAs detected in soils have higher risk compared to TETs and FQs. Keywords Kenya Soils Sulfonamides Tetracyclines Fluoroquinolones Risk assessment & Jun Wang wangjun@wbgcas.cn Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan , China Sino-Africa Joint Research Center, Chinese Academy of Sciences, Wuhan , China University of Chinese Academy of Sciences, Beijing , China Wuhan Environmental Protection Bureau, Wuhan , China Introduction Antibiotics are not only widely used in medicine to save human lives or to control disease in factory farming (Durso and Cook 2014; Gothwal and Shashidhar 2015), resulting in lots of antibiotics in wastewater treatment plant (Michael et al. 2013; Zhou et al. 2013) and livestock manure (Ho et al. 2014, 2015; Prosser and Sibley 2015). However, conventional sewage treatment facilities were never designed to deal with pharmaceutical compounds, so the removal efficiency of antibiotics was not stable and lots of antibiotics were discharged into the environment (Michael et al. 2013). Soil is also regarded as one of the important media for existence and transformation of antibiotics (Tolls 2001; Zhang et al. 2011). Antibiotics entered into the soil via sewage irrigation and manure fertilizer, and so on. Antibiotics in soils has showed toxic effect on soil microorganism (Liu et al. 2015; Reichel et al. 2015) and plant (Du and Liu 2012; Jin et al. 2009). So, it is critical to assess the levels of antibiotics in soils to avoid potential health risk via plant (Li et al. 2014; Prosser and Sibley 2015). Degradation and adsorption were the two main environmental behaviors of antibiotics in soil. Adsorption mechanism of antibiotics in soil was mainly due to charge transfer and ion interactions, and was significantly influenced by the ph of the soil (Thiele-Bruhn 2003; Tolls 2001). Antibiotics were susceptible to microbial degradation under aerobic conditions (Pan and Chu 2016). In Africa, no adequately enforced legislations regarding antibiotic use in food-producing animals as well as monitoring and control of their residues are carried out (Nonga et al. 2010). Hence, lots of antibiotics in Africa are not only discharged into the environment, but also found in the food which may threat the human health. For example, all analyzed chicken eggs contained sulfadiazine (SD) and

2 Y. Yang et al. Fig. 1 The map of studied sites in Kenya, Africa 59.4 % contained sulfamethazine (SMZ) residues (Mubito et al. 2014). In Kenya, antibiotics were also widespread and intensively used in food producing, in which tetracyclines (TETs) and sulfonamides (SAs) accounted for more than 70 % of the total consumption (Mitema et al. 2001). TETs, SAs and trimethoprim, nitrofurans, aminoglycosides, b- lactams, and quinolones were the most commonly used drugs in food-producing animals in Kenya (Darwish et al. 2013). Antibiotic residues were found to be prevalent in milk within the Nakuru district of Kenya (Shitandi and SternesjÖ 2001). To the best of our knowledge, less information is about the antibiotics in soils of Kenya and other countries in Africa. The analysis of antibiotics found in agricultural soils of China and Malaysia indicated fertilization with animal feces might be the primary source of antibiotics (Ho et al. 2014; Wu et al. 2014). Due to the intensive use of antibiotics and low treatment rate of sewage water in Kenya, it is necessary to assess the levels of antibiotics in soils. In this study, the occurrence, distribution and risk assessment of 12 antibiotics in soils from Kenya were investigated. The information will expand our knowledge of antibiotic pollution in African soils and propose useful strategies for soils management in Kenya. Method and materials Reagents Four SAs including SD, SMZ, sulfameter (SME) and sulfamethoxazole (SMX), four TETs including oxytetracycline (OTC), tetracycline (TC), chlortetracycline (CTC) and doxycycline (DC), and four fluoroquinolones including norfloxacin (NOR), ciprofloxacin (CIP), ofloxacin (OFL), and enrofloxacin (ENR) were purchased from Sigma- Aldrich Co. (St. Louis, USA). Organic solvents used for antibiotics extraction were at chromatographical grade. Sampling sites and sample collection The total of 58 soil samples were obtained from Kenya, including 18 samples in the rural area of Mai Mahiu, 14

3 Occurrence, composition and risk assessment of antibiotics in soils from Kenya, Africa Table 1 Concentrations of 12 antibiotics in soils from Kenya (lg kg -1 dw) Antibiotic Mai Mahiu (n = 18) Narok (n = 14) Mount Suswa conservancy (n = 16) Juja (n = 10) Freq (%) Range Mean Freq (%) Range Mean Freq (%) Range Mean Freq (%) Range Mean SD 5.56 nd nd nd nd nd SMZ nd nd nd nd SME 5.56 nd nd nd nd 0 nd nd SMX nd nd nd nd P SAs nd nd OTC nd nd nd nd TC nd nd nd nd CTC nd nd nd nd DC 5.56 nd nd nd nd nd P TETs nd nd NOR nd nd nd nd CIP nd nd nd nd OFL nd nd nd nd ENR nd nd nd P FQs nd P Total nd Freq Frequency samples in the suburban area of Narok, 16 samples in the Mount Suswa Conservancy, and ten samples in the rural area of Juja (Fig. 1). The soil samples (0 5 cm) were collected with a grab sampler and packed in sterile containers. Three subsamples were collected at each site, and combined as one sample before analysis. All the sites were in the scope of highland area of Central Kenya. The ph and cation exchange capacity of soil in this region were and cmol kg -1, respectively. Sample preparation and analysis of antibiotics Five grams of lyophilized and ground soil samples were extracted successively in an ultrasonic bath for 15 min using solution mixture (15 ml of methanol, 5 ml of Na 2- EDTA and 10 ml of citrate buffer at ph 5.0). The process was repeated at three times. The mixture was collected and centrifuged at 40009g for 5 min. The supernatants were combined and diluted into 500 ml using deionized sterile water. The crude extract was cleaned up and concentrated by solid phase extraction (SPE) using Strata strong anion exchanger (SAX) cartridges (3 ml/200 mg, Thermo, USA) and oasis hydrophilic lipophilic balance (HLB) cartridges (6 ml/500 mg, Waters, UK) in series. Detail information for extraction of antibiotics could be found in the literature (Luo et al. 2010). High-performance liquid chromatography-tandem mass spectrometry (HPLC/MS/MS) operated in positive mode with electrospray ionization (ESI) was used to separate and detect the antibiotics as literature previously published (Kim and Carlson 2007). Quality assurance and quality control (QA/QC) Average recoveries were monitored under a strict quality assurance and quality control to test the availability of the method before the sample analysis. Ten replicate spiked soil samples with a concentration of 1.0 lg kg -1 were extracted and analyzed in the same way as all the samples. Method blanks were analyzed routinely with field samples to check for interference and cross contamination. The limits of detection (LOD) based on a signal-to-noise ratio of three (S/N = 3) ranged from 0.10 to 0.50 lg kg -1 for soil samples. The average recoveries of the target antibiotics ranged from 65.2 to %. The calibration curves obtained for the antibiotics presented good linear relationship (R 2 [ 0.99) for all individual standards. All results were corrected with the recovery and concentrations of antibiotics in soils were reported on dry-weight. Risk assessment Risk quotient (RQ) values was applied to assess the ecological risk of antibiotics in soils, which are calculated as the ratio of the measured environmental concentrations (MEC; or predicted environmental concentrations, PEC) to the predicted no-effect concentrations (PNEC) for the specific

4 Y. Yang et al. pollutants (European Commission 2003). In general, RQ \ 0.1 indicates low risk; 0.1 B RQ \ 1 means medium risk, and RQ C 1 symbolizes high risk (European Commission 2003; Verlicchi et al. 2012). The studies about the direct toxicity of antibiotics to the terrestrial compartment (particularly to the soil) are few (Gao et al. 2008), leading to the challenge in estimating the PNEC in soil. Nevertheless, the PNECsoil values estimated from PNECwater values through the equilibrium partition approach were recommended (European Commission 2003; Martı n et al. 2012; Wu et al. 2014). In this study, the PNECsoil values of OTC, CTC, TC, NOR, CIP, ENR, SD, and SMX were 50, 270, 30, 29.68, 25.64, 24, 0.92 and 1.19 lg kg-1, which could be found in literatures (Halling-Sorensen et al. 2000; Robinson et al. 2005; Thiele-Bruhn and Beck 2005; Vaclavik et al. 2004; Zhang et al. 2015). The PNECsoil value of SMZ was 0.62, which was multiplied by the soil water partition coefficient of SMZ (3.1 L kg-1) (Thiele-Bruhn 2003) and PNECwater values derived from toxicity of SMZ to Daphnia magna (202 lg L-1) (De Liguoro et al. 2009). Statistical analysis Statistical analysis was performed using Microsoft Excel 2007 and SPSS software (Version 19.0, IBM, USA). Oneway analyses of variance (ANOVA) and Duncan (D) test was performed to test the difference between the antibiotics in different sampling sites. Pearson correlation analysis was applied to investigate the relationship between TOC and concentration of antibiotics. Statistical tests were considered significant at p \ Results and discussion Profile of antibiotics in soils from Kenya Table 1 summarizes the concentrations of 12 antibiotics in soils from Kenya. The soils in suburban area of Narok had the highest mean concentrations of total 12 antibiotics with mean value of lg kg-1 dw (dry weight), followed by soils in Fig. 2 Composition of antibiotics in soils of Kenya, Africa. (1 Mai Mahiu, 2 Narok, 3 Mount Suswa Conservancy, 4 Juja)

5 Occurrence, composition and risk assessment of antibiotics in soils from Kenya, Africa Table 2 Concentrations of antibiotics in soils worldwide (lg kg -1 dw) Compounds Antibiotic Concentration and sites SAs SD 0.11 (Beijing, China) a, 13.4 (Guangdong, China) b, nd (Malaysia) c, nd (Austria) d, nd-3.85 (Kenya, this study) SMZ 0.37 (Beijing, China) a, 5.5 (Guangdong, China) b, nd (Kenya, this study) SMX 0.06 (Beijing, China) a, 23.5 (Guangdong, China) b, nd (Kenya, this study) SME 51.4 (Guangdong, China) b, nd-5.79 (Kenya, this study) SAs 400 (Turkey) e TETs OTC 80 (Beijing, China) a, 9.6 (Guangdong, China) b, nd (Austria) d, nd (Kenya, this study) TC 5.2 (Beijing, China) a, 44.1 (Guangdong, China) b, nd (Austria) d, nd (Kenya, this study) CTC 17 (Beijing, China) a, 31.1 (Guangdong, China) b,10 15 (Denmark) f, nd (Kenya, this study) DC (Malaysia) c, nd-3.85 (Kenya, this study) FQs NOR 13 (Beijing, China) a, 61.9 (Guangdong, China) b, nd-96 (Malaysia) c, 55.7 (Shandong, China) g, nd (Kenya, this study) CIP 23 (Beijing, China) a, 26.9 (Guangdong, China) b, nd (Turkey) e, (Shandong, China) g, nd-9.88 (Kenya, this study) ENR 47 (Beijing, China) a, 99.4 (Guangdong, China) b, (Malaysia) c, 50 (Austria) d, 50 (Turkey) e, 18.6 (Shandong, China) g, nd (Kenya, this study) SAs sulfadiazine? sulfathiazole? sulfamethoxazole, nd not detected a g Noted the following references: Li et al. (2011), (2014), (2015), Ho et al. (2014), Martínez-Carballo et al. (2007), Karcı and Balcıoğlu (2009) and Jacobsen et al. (2004), respectively Mai Mahiu (26.70 lg kg -1 dw), Juja (24.41 lg kg -1 dw) and Mount Suswa Conservancy (12.21 lg kg -1 dw). ANOVA analysis indicated statistical difference existed between concentrations of total 12 antibiotics in the four sites at p \ 0.05 level. For SAs, soils in Narok had highest mean concentration of total SAs among the tested four sites, followed by Mai Mahiu, Mount Suswa Conservancy, and Juja. For TETs, highest mean concentration of total TETs was also observed in Narok (19.47 lg kg -1 dw), followed by Juja (9.32 lg kg -1 dw), Mai Mahiu (7.74 lg kg -1 dw) and Mount Suswa Conservancy (3.11 lg kg -1 dw). The trend for the mean concentration of total FQs was Narok (13.11 lg kg -1 dw) [ Juja (12.25 lg kg -1 dw) [ Mai Mahiu (8.57 lg kg -1 dw) [ Mount Suswa Conservancy (4.65 lg kg -1 dw). The soils in Narok experienced serious pollution of antibiotics compared to Mai Mahiu, Mount Suswa Conservancy and Juja. In Narok, application of organic residues has been recommended as a more feasible and sustainable alternative as fertilizers (Vincent et al. 2011). The organic residues may play an important role in the pollution of antibiotics in Narok. Composition of antibiotics in soils from Kenya For individual antibiotic in Mai Mahiu, OTC had the highest detect frequency (83.33 %), followed by SMZ (77.78 %), SMX (77.78 %) and ENR (72.22 %). The other eight antibiotics had low frequency less than 70 % (Table 1). SMZ had the highest average concentration (5.34 lg kg -1 dw) among the tested 12 antibiotics, followed by SMX (4.78 lg kg -1 dw), ENR (4.05 lg kg -1 dw) and OTC (3.62 lg kg -1 dw). In suburban soils from Narok, SMZ, SMX, TC, OTC, CTC, and ENR had the detect frequency more than 70 %, while the detect frequency of other 6 antibiotics was less than 50 %. OTC had the highest mean concentration (9.17 lg kg -1 dw), followed by CTC (6.49 lg kg -1 dw), ENR (6.02 lg kg -1 dw) and SMX (5.10 lg kg -1 dw). In soils of Mount Suswa Conservancy, only three antibiotics (SMZ, SMX and ENR) had detected frequency more than 70 %. SMX had the highest average concentration (3.09 lg kg -1 dw), followed by ENR (2.68 lg kg -1 dw) and SMZ (1.37 lg kg -1 dw). In soils of Juja, the detected frequency of ENR, DC, OTC and SMX was more than 80 %, while the detected frequency of the other 8 tested antibiotics was no more than 30 %. ENR had the highest average concentration (10.98 lg kg -1 dw), followed by OTC (5.02 lg kg -1 dw), and TC (2.79 lg kg -1 dw). Figure 2 shows the composition of SAs, TETs and FQs in the four sites. In group of SAs (Fig. 2a), SMX and SMZ were the main pollutants accounting for more than 80 % of total SAs in soils of the four sites. SMZ also found to be an important antibiotic pollutant in chicken eggs in Africa (Mubito et al. 2014). In group of TETs, OTC was the priority pollutant which is responsible for more than 40 % of total TETs. DC had the lowest percentage in the composition of total TETs (Fig. 2b). OTC also had the most detection rate among TETs in the beef samples collected in and around the city of Nairobi (Darwish et al. 2013). For the group of FQs,

6 Y. Yang et al. soils from Africa should be done. The composition pattern of SAs, TETs and FQs in Mai Mahiu and Mount Suswa Conservancy was similar (Fig. 2d). In Juja, the TETs and FQs had higher percentage compared to SAs (Fig. 2d). In conclusion, SMX, SMZ, OTC and ENR should be paid more attention in soils of Kenya. To understand the status of antibiotics in soils of Kenya, the concentrations of antibiotics in soils from other sites worldwide were summarized in Table 2. The concentrations of SD, SMZ, SME and SMX in soils of Kenya were lower than those in vegetable farmland soil in the Pearl River Delta, Southern China (Li et al. 2011), and higher than soils from greenhouse vegetable production in Beijing (Li et al. 2015) and soils in Austria (Martínez-Carballo et al. 2007). OTC, TC, CTC concentrations in this study were lower than those in soils in Beijing (Li et al. 2015) and Guangdong (Li et al. 2011) of China and Denmark (Jacobsen et al. 2004), but higher than those in Austria (Martínez-Carballo et al. 2007). ENR, NOR and CIP concentrations in soils of this study were lower than those in soils of China (Li et al. 2011, 2014, 2015) and Malaysia (Ho et al. 2014), but higher than those in soils from Turkey (Karcı and Balcıoğlu 2009). The adsorption process of antibiotics onto soils was influenced by many factors, such as ph, salinity, TOC and metals (Tolls 2001; Zhang et al. 2011). The correlation relationship between TOC and concentrations of SAs, TETs, and FQs was studied using Pearson correlation analysis. The results showed that no significant correlation relationship was found between TOC and concentrations of SAs, TETs, and FQs in soils from Mai Mahiu and Mount Suswa Conservancy. In Narok, TOC only had significantly positive correlation relationship with concentrations of SAs (r = 0.744, p = 0.022). In Juja, only the concentrations of FQs were found to be significantly positive with the TOC (r = 0.789, p = 0.011). So, TOC may influence the distribution of SAs in Narok and FQs in Juja. Risk assessment of antibiotics in the suburban soils of Kenya Fig. 3 RQ values of antibiotics in soils of Kenya, Africa. (1 Mai Mahiu, 2 Narok, 3 Mount Suswa Conservancy, 4 Juja) ENR was the main pollutant accounting for % of the total TETs in the four sites. CIP had the lowest mean percentage in the composition of total FQs (Fig. 2c). There is a steady increase in consumption of quinolones since 1998 in Kenya (Mitema et al. 2001) and the concentration of ENR in Juja even exceeded 10 lg kg -1 dw. So, more studies on the trend and transformation of FQs pollution in The RQ values of antibiotics are shown in Fig. 3. From Fig. 3a, RQ values of SMX and SMZ were more than 1.0 in more than 75 % soils samples from Mai Mahiu, Narok and Mount Suswa Conservancy, indicated a high ecological risk of SMX and SMZ in soils from these studied areas. RQ values of SMX and SMZ were more than 1.0 in only 40 and 20 % soils samples from the tested four sites of Juja, respectively, indicating less ecological risk in these regions. RQ values of SD in most % of samples were less than 0.1, suggesting that SD pose a low risk to soils from all sampling sites. For TETs, all RQ values were less than 1.0 (Fig. 3b). RQ values of TC and OTC were less

7 Occurrence, composition and risk assessment of antibiotics in soils from Kenya, Africa than 0.1 in more than 60 % soil samples of Mai Mahiu, Mount Suswa Conservancy and Juja, while RQ values of TC and OTC were more than 0.1 in more than 50 % soil samples from Narok. These results indicated TC and CTC pose a higher risk in Narok compared to the other three sites. RQ values of CTC were less than 0.1 in most samples in Narok, indicating that the risk of CTC was low in soils from Narok. For groups of FQs (Fig. 3c), all the RQ values were less than 1.0 except one sample in Juja, indicated medium risk of FQs exist in the studied areas. More than 65 % samples in all sites had low RQ values (\0.1) of NOR and CIP, but the percentage of samples for RQ values of ENR exceeding 0.1 ranged from 44.4 to %. This suggested that ENR had a higher ecological risk compared to NOR and CIP. In summary, the SAs detected in soils have a higher ecological risk compared to TETs and FQs in all sampling sites. Conclusion The pollution levels of antibiotics in soils of Mai Mahiu, Narok, Mount Suswa Conservancy, and Juja from Kenya were assessed in this study. Statistical difference existed between concentrations of total 12 antibiotics. Narok had the highest levels of antibiotics with a mean concentration of lg kg -1 dw. Compared to soils from other sites worldwide, the pollution levels of TETs and FQs were relatively low in Kenya. Risk analysis showed more than 75 % soils samples of Mai Mahiu, Narok and Mount Suswa Conservancy had higher RQ values of SMX and SMZ, indicating these soils may have a high risk of SMX and SMZ. While all TETs and most FQs had low RQ values, indicating the ecological risk of TETs and FQs were lower than SAs. So, SAs should be given more attention to reduce the misuse of SAs in livestock and increase the treatment efficiency of SAs in the wastewater plant. Funding This study was funded by Funding Project of Sino-Africa Joint Research Center, Chinese Academy of Sciences (Y623321K01), Youth Innovation Promotion Association of Chinese Academy of Sciences (NO ) and the Hundred Talents Program of the Chinese Academy of Sciences (Y329671K01). Compliance with ethical standards Conflict of interest Yuyi Yang declares that he has no conflict of interest, Anita Awino Owino declares that he has no conflict of interest, Yan Gao declares that he has no conflict of interest, Xue Yan declares that he has no conflict of interest, Chen Xu declares that she has no conflict of interest, Jun Wang declares that he has no conflict of interest. Ethical approval This article does not contain any studies with human participants or animals performed by any of the authors. References Darwish WS, Eldaly EA, El-Abbasy MT, Ikenaka Y, Nakayama S, Ishizuka M (2013) Antibiotic residues in food: the African scenario. 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