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Veterinary antibiotics ( VAs) administered to livestock are introduced into the soil through livestock manure and compost. These antibiotics can run off to surface water or leach into groundwater during rainfall, causing problems such as anti‑ biotic contamination or the occurrence of antibioticr ‑ esistant bacteria. In this study, an analytical method for detecting four classes of VAs (penicillin, tetracyclines, macrolides, and sulfonamides) in river water and soil was developed, and the occurrence of residual antibiotics in the agricultural environment was monitored. Soil samples were extracted with the McIlvain buffer solution and pretreatment was conducted using solidphase ex ‑ traction, followed by liquid chromatog‑ raphytandem mass spec ‑ trometry to quantify target VAs. The results of this study showed that the recovery ranged from 62 to 121% in river water and 40.2–149.3% in soil. Among the other VAs, amoxicillin and spiramycin were observed to −1 have low recoveries in all the samples. The method detection limit (MDL) was calculated in the range of 2.1–12.3 ng L −1 −1 −1 in river water and 1.2–13.2 ng kg in soil, and the limit of quantification was 6.6–39.2 ng L and 4.0–42.0 ng kg , respectively. This optimal method was then applied to measure the residual concentrations of VAs in river water, sedi‑ ment, and soil samples around the Muhan watershed in Korea. A total of seven antibiotics were detected, and their −1 −1 concentrations ranged from 0.014 to 0.309 μg L in river water, and 1.45–9.04 μg kg in sediment and arable soil. This method can be used to screen VAs in river water and soil and is expected to be used as primary data for examining the occurrence and fate of antibiotics in agricultural environments. Keywords Tetracyclines, Sulfonamides, Analytical method, Water, Sediment, Soil . However, these pharmaceuticals are regarded as new Introduction emerging contaminants due to their intensive use result- Veterinary antibiotics (VAs), which are widely con- ing in production of antibiotic resistance in the environ- sumed to treat and prevent bacterial infections and dis- ment . Moreover, the scale of the livestock industry eases, have played an essential role in livestock health has increased over the past few decades, owing to global population growth and increased demand for livestock products. *Correspondence: Sung Chul Kim Antibiotics administered to livestock are not com- firstname.lastname@example.org pletely metabolized in the body and are excreted in feces Department of Bio‑Environmental Chemistry, Chungnam National in the form of parent compounds . Un-metabolized University, Daejeon 34134, Korea National Institute of Agricultural Sciences, Rural Development forms of VAs remaining in manure, compost, and liquid Administration, Wanju 55365, Republic of Korea fertilizer can be introduced into soil , surface water, or Biogas Research Center, Hankyong National University, Anseong 17579, be leached into groundwater via rainfall [5, 6]. In addi- Korea Department of Applied Life Chemistry, Gyeongsang National University, tion, released VAs in the environment can be transferred Jinju‑si 52828, Korea and accumulated to crops or cause toxic effects, such as © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. Kim et al. Applied Biological Chemistry (2023) 66:20 Page 2 of 11 growth inhibition [7–9], reduction of soil bacterial activ- surface water and soil adjacent to confined animal feed - ity or diversity [10, 11]. The most important adverse ing operations. The target analytes for this research effect of VAs released into the environment is that they include 12 antibiotics belonging to four different groups, may cause the production of antibiotic resistance genes penicillins, tetracyclines, macrolides, and sulfonamides, (ARGs) and eventually threaten human health [12, 13]. contributing to approximately 60% of the total amount Faced with these ecological concerns, many research- of VA sales in South Korea. Although these compounds ers have become interested in the occurrence, fate, and reported that they have the potential hazard of the spread distribution of residual VAs in agricultural environments. of ARGs in the agricultural environment due to their The United States Environmental Protection Agency higher usage than other VA classes in Korea, less research (US EPA) developed and published Method 1694 (Phar- has been conducted on monitoring residual VAs in agri- maceuticals and Personal Care Products in Water, Soil, cultural environments [21–23]. The results of this study Sediment, and Biosolids by HPLC/MS/MS) to determine can be used to monitor the residual concentrations of antibiotics in the environment . Many European VAs in different environmental media and to understand countries developed analytical methods for identifying the occurrence of VAs in arable areas. the presence of antibiotics in aqueous environments such as river water, wastewater, and groundwater . These Materials and methods efforts of antibiotic management in the environment are Chemicals and reagents also carried out actively in Asia countries [16, 17]. Twelve reference standards (amoxicillin, ampicillin, peni- In Korea, many studies have focused on the develop- cillin G sodium salt, chlortetracycline hydrochloride, oxy- ment and distribution of residual antibiotics in agricul- tetracycline hydrochloride, tetracycline hydrochloride, tural and livestock products; however, there is still a lack spiramycin, tylosin tartrate, sulfadiazine, sulfamethaz- of interest in and research on environmental media. Cur- ine, sulfamethoxazole, and sulfathiazole) were purchased rently, standard analytical methods and maximum resi- from Sigma-Aldrich (St. Louis, MO, USA), and their due limits (MRLs) for VAs in agricultural, marine, and physicochemical properties are shown in Additional livestock products are established and managed under file 1: Table S1. The internal standards (simeton) were the supervision of the Ministry of Food and Drug Safety, obtained from AccuStandard (New Haven, CT, USA). and monitoring of residual antibiotics in foods has been All the organic solvents (methanol and acetonitrile) and actively conducted in various regions and institutions in water used for sample pretreatment and instrumental Korea [18, 19]. In contrast, there are currently no stand- analysis were of HPLC grade (J. T. Baker, Philipsburg, ard analytical methods for antibiotics in environmental NJ, USA). Sodium phosphate, citric acid, formic acid, media, such as river water and soil. In addition, research and ethylenediaminetetraacetic acid disodium salt dihy- on the simultaneous analysis of multiple classes of VAs drate (Na -EDTA) were acquired from Sigma-Aldrich. −1 was lacking. Stock solutions (100 mg L ) were prepared by accurately Because environmental media are the primary sink weighing each antibiotic standard in a 100 ml volumetric of VAs and the main transmission route for antibiotic flask, dissolved in methanol, and stored in an amber glass resistance , the development and monitoring of VAs bottle at − 20 °C. The working solutions were prepared is important. Liquid chromatography-tandem mass spec- by mixing and diluting each stock solution appropriately trometry (LC–MS/MS) is often used to analyze VAs in HPLC-grade water at concentrations varying from −1 in various samples because of its high analytical per- 0.01 to 1.0 mg L and were stored in an amber glass bot- formance and low limit of detection (LOD). However, tle at − 20 °C until analysis. environmental samples, such as river water and soil, con- sisting of a very complex matrix, may be affected by vari - Sample preparation ous coexisting substances present in the sample during River water samples were filtered through a 0.2 μm cellu - instrument analysis. These problems can reduce the sen - lose acetate membrane filter and stored at 4 °C until anal - sitivity of qualitative and quantitative analyses. In addi- ysis. For antibiotic extraction in water samples, 120 mL of tion, due to differences in the physicochemical properties the filtered sample was taken into a 250 mL Erlenmeyer of each antibiotic group, it is challenging to determine flask and the pH was adjusted to 2.5 ± 0.1 using 40% various antibiotics simultaneously through single sample (v/v) sulfuric acid. Then, 500 μL of 5% (w/v) Na -EDTA preparation and instrumental analysis. was added and the samples were shaken at 150 rpm for Therefore, this study aimed to develop an optimal ana - 15 min at room temperature (25 ℃), followed by purifi - lytical method for quantifying different classes of VAs in cation by solid phase extraction (SPE). The collected soil river water and soil. In addition, the developed analyti- samples were air-dried under dark conditions and sieved cal method was applied to measure the residual VAs in through a 2.0 mm mesh. For antibiotic extraction, each K im et al. Applied Biological Chemistry (2023) 66:20 Page 3 of 11 soil sample of 1.0 g was weighed in a centrifuge tube, and for 3 min. Finally, the extract was transferred to an amber 20 mL of McIlvain buffer solution (pH 4.0) and 250 μL of glass HPLC vial and stored at − 20 °C until analysis. Sam- 5% Na -EDTA were added. This mixture was shaken for ple preparation diagram is shown in Fig. 1. 15 min and centrifuged for 15 min at 4000 rpm, and the supernatant was transferred into a 250 mL Erlenmeyer flask. Soil samples were extracted twice (40 mL), to which LC–MS/MS analysis 80 ml of ultrapure water was added. The extracted sam - The instrument analysis for the detection and quantifica - ples were filtered with a 0.2 μm cellulose acetate mem - tion of residual antibiotics was performed using HPLC brane filter and purified by SPE. (1290 Infinity II, Agilent, Santa Clara, CA, USA) coupled The SPE was conducted using a Visiprep SPE vacuum with triple quadrupole mass spectrometry (6500 Qtrap, manifold (Supelco, Bellefonte, PA, USA). Before load- SCIEX, Framingham, MA, USA) equipped with an elec- ing the samples, the SPE cartridge was activated by trospray ionization probe. All target antibiotics were ana- sequentially flowing methanol (0.5 M hydrochloric acid lyzed using multiple reaction monitoring (MRM) in the (3.0 mL) and ultrapure water (3.0 mL)) through the car- positive ion mode. Target analytes were separated using a tridge. The extracted samples were loaded into a Teflon Zorbax Eclipse Plus-C18 column (Agilent, 4.6 × 150 mm, −1 tube at a flow rate of 4 ml min . When all the samples 3.5 μm) protected by a security guard cartridge (Phenom- passed through the cartridge, the cartridge was washed enex, Torrance, CA, USA) at 25 °C. The gradient elution with flowing ultrapure water (3.0 ml of ultrapure water in system was set with mobile phase A (0.1% formic acid three divided portions). Further, a 15 ml glass centrifuge in HPLC-grade water) and mobile phase B (0.1% formic −1 −1 tube containing 50 μL of simeton (0.24 mg L ), an inter- acid in acetonitrile) at a flow rate of 0.7 ml min , and nal standard, was mounted on the SPE vacuum manifold, the total runtime was set to 15 min. The detailed HPLC and then 2.5 mL of methanol was passed to the cartridge and mass spectrometry conditions are presented in Addi- twice (5.0 mL in total) to extract antibiotics. The eluate tional file 1: Table S2. The analyzed MRM data were was concentrated to 50 µL at 40 °C using a nitrogen con- processed using the Analyst software version 1.5.1 and centrator (12-position N-EVAP nitrogen evaporation sys- MultiQuant software version 3.0.2 (SCIEX, Framing- tem, Organomation, MA, USA). Then, 70 μL of mobile ham, MA, USA). phase A was added and centrifuged using a 1.5 mL centri- fuge tube containing a 0.22 μm nylon filter at 13,000 rpm Fig. 1 Flow diagram of analytical method for veterinary antibiotics in river water and soil Kim et al. Applied Biological Chemistry (2023) 66:20 Page 4 of 11 Method validation Method validation was performed according to the US EPA method 1694 , and specificity, linearity, matrix effect, accuracy, precision, method detection limit (MDL), and limit of quantification (LOQ) were evalu - ated in the water and soil samples. Blank river water samples were collected from Gap stream, Daejeon, South Korea. The pH and electrical conductivity (EC) were 7.10 −1 and 0.22 dS m , respectively. Blank soil samples were collected from a research farm located at Chungnam National University, Daejeon, South Korea. The physico - chemical properties of soil samples are as follows: a sandy Fig. 2 Map of Muhan river with sampling sites and potential sources loam texture (56% sand, 16% silt, and 28% clay), pH 6.22, of antibiotics contamination −1 EC 0.38 dS m , and organic matter content 2.87%. All these properties were determined using water pollution standard method proposed by Ministry of Environment samples and the relative standard deviation (RSD) was and soil standard methods proposed by Rural Develop- calculated to evaluate precision. ment Administration (RDA) in South Korea. Before method validation, both blank samples were analyzed Method detection limit (MDL) and limit of quantification using the developed method to confirm that antibiotics (LOQ) were not present. The method detection limit (MDL) and limit of quantifi - cation (LOQ) for each analyte were evaluated using the Specificity standard deviation (SD) of seven spiked river water and To check the specificity of the instrumental analysis of soil samples. The MDL was calculated by multiplication target antibiotics in water and soil, we analyzed two types of the SD by the Student’s t-value for six degrees of free- of samples: blank samples and antibiotic mixture spiked dom at a 99% confidence level (3.143, α = 0.02). The LOQ −1 samples (at low concentration levels of 0.01 mg L ). was calculated by multiplying the SD by 10. Subsequently, specificity was verified by comparing the two types of chromatograms. Analysis of agricultural environmental samples To evaluate the optimal extraction method established in this study and monitor residual antibiotics in the agri- Linearity cultural environment, river water, soil, and sediment Linearity was evaluated by constructing matrix-matched samples were collected at five points around the Muhan calibration curves at seven concentration levels in the River watershed in Yesan-gun, Chungcheongnam-do, −1 range of 0.01–1.0 mg L . South Korea (Fig. 2). The sampling sites for river water and sediment samples were selected as the points where the antibiotic contamination source was located, and soil Matrix effect samples were selected as arable soil where residual anti- To evaluate matrix effects (ME), a matrix-matched cali - biotics can flow into the Muhan River during rainfall. bration curve using blank samples and a standard solu- The Yesan public sewage treatment facility and livestock tion calibration curve was constructed (in the range of −1 manure public resource center are located at sites 2 and 0.01–1.0 mg L ), and the slopes between the two cali- 3, respectively, and the effluent from these facilities is dis - bration curves were compared (Eq. 1). Slope of matrix - matched regression line (1) Matrix eﬀect (% ) = −1 × 100 Slope of standard regression line Accuracy and precision charged into the Muhan River. Sites 4 and 5 are intensive Accuracy was determined through a recovery test at livestock farming areas (site 4 is a mixed cattle-pig farm, −1 two concentration levels (0.1 and 1.0 g L ). Each sam- and site 5 is a poultry farm), where livestock manure may ple containing the antibiotic mixture was analyzed and directly or indirectly runoff to surface water due to rain - compared with the calculated and expected concentra- fall. River water samples were collected in 1 L polyethyl- tions. A recovery test was performed with three duplicate ene collection bottles, placed in an icebox, transported to K im et al. Applied Biological Chemistry (2023) 66:20 Page 5 of 11 the laboratory, and stored at 4 °C until analysis. Sediment and acetonitrile (mobile B), and 0.1% of formic acid was samples were collected using a stainless-steel shovel and added as an acidic additive to increase the ionization effi - topsoil layer (0–15 cm) of soil samples were collected ciency and detection sensitivity in the mass spectrometer using a hand auger after removing the organic layer from . the surface. All sediment and soil samples in each loca- Validation of the separation method was confirmed −1 tion were composited to make one representative sample by injecting a 0.1 mg L antibiotic standard mixture after collecting from 5 different locations. solution into the HPLC, and all analytes were separated within 15 min of runtime (Additional file 1: Fig. S1). In addition, a calibration curve was constructed using a Statistical analysis −1 standard mixture in the range of 0.01–1.0 mg L , and Each sample was analyzed in triplicate, and antibiotic 2 coefficients of determination (R ) were calculated to be concentrations were expressed as mean values ± stand- more than 0.999 for all antibiotics, indicating good lin- ard deviation (SD). One-way ANOVA and post hoc test earity (Additional file 1: Table S3). (Duncan’s test, p < 0.05) were performed using the statis- tical package for social science (SPSS) version 26.0 (SPSS Extraction and clean‑up procedure optimization Inc., Chicago, IL, USA) for multiple group comparison. River water and soil samples are composed of a complex The Mann–Whitney U test (α = 0.05) was used to evalu- matrix, and most residual antibiotics in the environ- ate the efficiency of the antibiotic extraction method. ment are present at low concentrations . Therefore, an appropriate sample preparation process is needed, Results and discussion including extraction of the target analyte, adjustment of Method development the sample pH, removal of interfering substances, and LC–MS/MS analysis optimization sample enrichment. This study adjusted various sample For each target analyte, the MRM conditions of the mass preparation factors to develop an optimal extraction and spectrometer were optimized to provide the best perfor- cleanup procedure for target antibiotics. The selection of mance for VA quantification. To achieve high sensitivity, the extraction solvent is one of the primary parameters −1 each analyte prepared as a 0.1 mg L standard solution in the sample preparation process and affects the per - was individually injected directly into the mass spec- formance of the method for soil and sediment sample. trometer using a 1 mL Hamilton gas-tight syringe, and McIlvaine [29, 30] and phosphate buffers [31, 32] are the mass spectrum was identified in full scan mode. In often used as extraction solvents for solid samples. In this the Q1 mass spectrum, all analytes showed a high sig- study, the efficiency of each extraction solvent was evalu - nal intensity in the form of [M + H] , and this ion was ated by measuring the recovery rate of the spiked blank −1 selected as the precursor ion. To obtain the MRM condi- sample at concentrations of 0.1 mg L . tions, the m/z value of the precursor ion was input into Extraction efficiencies using the McIlvaine buffer did the tuning programs of the mass spectrometer, and the not satisfy the requirements for amoxicillin (32.5%) and product ion was identified according to the precursor ampicillin (43.2%). The phosphate buffer was also tested ion. Subsequently, the detection sensitivity of the product using the same extraction process for comparison with ions was increased by adjusting the declustering poten- the McIlvaine buffer. When using a phosphate buffer, the tial energy (DP), entrance potential energy (EP), colli- recoveries of the amoxicillin and ampicillin increased to sion energy (CE), and collision cell exit potential energy 120.4–101.7%, respectively, compared with the McIlvaine (CXP); three optimal product ions were selected. Among buffer. However, sulfonamide antibiotics showed poor the three product ions, the ion with the highest signal extraction efficiency in phosphate buffer, and the recov - strength was selected as the quantitative ion, and the ery of sulfamethazine showed a decrease from 81.4 to remaining two product ions were chosen as qualitative 18.9%. Furthermore, it is widely known that nonvolatile ions (Table 1). phosphate buffer contaminates the electrospray ioniza - To get the best separation of VAs with different phys - tion source owing to its strong ionization suppression, icochemical properties using HPLC, a method was devel- which decreases the sensitivity of the LC–MS/MS analy- oped with reference to Kim and Carlson (2007) . sis . Therefore, the McIlvaine buffer was used as the Most of the penicillin, tetracycline, macrolide, and sul- extraction solvent for the analyzed soil samples. fonamide group antibiotics have polar functional groups River water and soil contain various organic and inor- [25, 26], so a reverse phase C18 column, which is effective ganic matter, as well as target analytes. These co-exist - for analyzing polar compounds was used. For optimal ing substances can block the HPLC column, and during gradient conditions and obtaining a good peak shape, the the sample preparation process, these materials are mobile phase consisted of HPLC-grade water (mobile A) co-extracted with the target compounds and behave as Kim et al. Applied Biological Chemistry (2023) 66:20 Page 6 of 11 Table 1 LC–MS/MS parameters with MRM transitions for analysis of 12 antibiotics 1) 2) 3) 4) Class Compound (abbreviation) Precursor ion Product ion (m/z) DP (V) EP (V) CE (V) CXP (V) (m/z) 5) 6) Simeton 124.1 27 6 198.1 128.1 71 10 27 22 100.1 39 18 Penicillins Amoxicillin 349.1 11 8 (AMO) 365.9 114.0 6 10 23 8 134.0 37 12 Ampicillin 106.1 41 14 (AMP) 349.9 192.0 6 10 21 24 113.9 41 8 Penicillin G 217.0 19 12 (PNG) 334.9 202.0 136 10 31 24 91.0 67 16 Tetracyclines Chlortetracycline 444.0 31 24 (CTC) 479.0 462.1 66 10 23 12 260.0 73 18 Oxytetracycline 426.1 27 18 (OTC) 461.1 443.2 36 10 19 22 201.1 49 12 Tetracycline 410.1 29 20 ( TC) 445.1 427.1 26 10 19 28 154.2 37 14 Macrolides Spiramycin 174.2 27 8 (SPM) 843.5 540.3 101 10 19 14 101.0 23 10 Tylosin 772.4 45 4 ( TYL) 916.5 174.2 61 10 45 22 83.1 129 2 Sulfonamides Sulfadiazine 156.0 21 8 (SDZ) 251.0 92.0 1 10 33 12 65.0 61 6 Sulfamethoxazole 186.0 23 10 (SMX) 279.0 124.0 1 10 29 12 65.0 67 8 Sulfamethazine 156.0 21 14 (SMZ) 254.0 92.0 1 10 33 10 65.0 61 6 Sulfathiazole 155.9 21 18 (STZ) 255.9 92.0 21 10 33 12 65.0 63 6 1) 2) 3) 4) 5) 6) DP decluttering potential, EP Entrance potential, CE Collision energy, CXP Collision Cell Exit Potential, simeton internal standard, Bold product ion was used for quantification interfering substances in the ionization of the analytes in The selection of an adequate cartridge is the most mass spectrometry. For these reasons, the SPE method critical step in the SPE process, and we selected the was used to improve the efficiency of quantification using Oasis HLB (Hydrophilic-lipophilic balance) sorbent LC–MS/MS, and the SPE method was optimized by con- cartridge to extract target analytes based on previous sidering factors such as cartridge type, sample loading literature [34–36]. The HLB sorbent comprises two mon - volume, and loading flow rate. omers (hydrophilic N-vinylpyrrolidone and lipophilic K im et al. Applied Biological Chemistry (2023) 66:20 Page 7 of 11 divinylbenzene) that effectively absorb polar compounds target analytes, and sensitivity analysis was possible even [37, 38]. at low concentrations. Furthermore, to adjust the sample volume parameter, the SPE loading volume was set to 120 ml and 240 ml Linearity and tested at two different final concentrations of 0.1 and To evaluate the linearity of the method in river water and −1 1.0 mg L using blank river water and soil samples. The soil samples, we prepared a matrix-matched calibration volume parameter was evaluated by comparing the aver- curve for each target analyte at seven different concentra - −1 age recovery rate (Mann–Whitney U test, n = 6), and the tion levels ranging from 0.01 to 1.0 mg L and obtained results showed no significant difference in the recovery the correlation coefficient (R ). The linearity values in rate between the sample volume factors. However, since river water and soil ranged between 0.9933 and 0.9995 the analysis time also increased as the sample volume and 0.9916 and 0.9998, respectively, indicating good lin- increased from 120 to 240 mL, a 120 mL sample volume earity (R more than 0.99, Additional file 1: Table S4). was adopted to achieve the effective SPE method. To assess the efficiency of the SPE process according Matrix effect to the sample loading flow rate, a recovery test was per - The slopes of these two calibration curves (matrix- formed by spiking the target analytes with two known matched and standard solution calibration curves) were −1 concentration levels (0.1 and 1.0 mg L ) into ultrapure compared to evaluate the matrix effect (ME, %). Based water. During SPE extraction, the loading flow rate at on the calculated percentage values, the matrix effect was which the sample passed through the cartridge was set classified into two categories: ion enhancement (ME > 0%) −1 to 2 and 4 ml min , and the mean recovery rate was and ion suppression (ME < 0%). The percentage range compared (Mann–Whitney U test, n = 6). In the statis- of ± 0–20% is considered a soft matrix effect, but the tical analysis of the two different flow rates, the p-value range of 20–50% or > 50 and < − 50% is considered to suf- was calculated to be higher than 0.100 for both 0.1 and fer a medium and strong matrix effect, respectively . −1 1.0 mg L for all target analytes. These results indicated In the river water and soil samples, the matrix effect was that the sample loading flow rate during the SPE step calculated in the ranges of − 62.9–124.9% and − 72.7– did not affect the extraction process. However, although 198.9%, respectively (Additional file 1: Table S5). Among there was no significant difference in the recovery rate penicillin antibiotics, amoxicillin and ampicillin showed when the sample loading flow rate was reduced from insignificant matrix effects (ranging from − 11.1 to −1 −1 4 mL min to 2 mL min , the extraction time was 26.1%), but penicillin G revealed medium ion suppres- approximately doubled. Therefore, a loading flow rate of sion (ranging from − 53.4 to − 39.5%). All tetracycline −1 4 mL min was used in the subsequent experiments to antibiotics showed ion enhancement, and oxytetracycline minimize the sample extraction run time. showed a range of up to 198.9% in soil. Macrolide and sulfonamide antibiotics showed medium or strong ion Method validation suppression from -29.0 to − 72.7%. Most target antibiot- The developed analytical method was validated in terms ics suffered medium or strong matrix effects, so we used of sensitivity, linearity, matrix effect, accuracy, precision, simeton as an internal standard (adjusted ion suppres- method detection limit (MDL), and limit of quantita- sion) or applied matrix-matched calibration (adjusted tion (LOQ) according to the US EPA method 1694 . ion enhancement) to compensate for matrix effects and Validation was carried out using blank river water and improve the sensitivity of the quantitative analysis. soil samples with the addition of appropriate amounts of mixed antibiotic standard solution. MDL and LOQ The values of MDL and LOQ were calculated according Specificity to "Method detection limit (MDL) and limit of quan- Blank samples of each matrix (river water and soil) and tification (LOQ)" and are presented in Table 2. The −1 −1 fortified samples (low concentration level of 0.01 mg L ) MDLs ranged from 2.1–12.3 ng L in river water and −1 were analyzed to evaluate the presence of interference. 1.2–13.2 ng kg in soil, and the LOQs ranged from −1 −1 After LC–MS/MS analysis, peaks observed near the 6.6–39.2 ng L and 4.0 to 42.0 ng kg , respectively. The retention time of each analyte were checked, and chro- MDL and LOQ of all target analytes were calculated at −1 −1 matograms of the blank and fortified samples were com - the ng L or ng kg level. Thus, this method was con - pared. No significant interference peaks were observed sidered sufficient to quantify trace amounts of VAs in the for any of the antibiotics (Additional file 1: Fig. S1). environment. Therefore, this method was considered specific for the Kim et al. Applied Biological Chemistry (2023) 66:20 Page 8 of 11 Table 2 MDL and LOQ for the target analytes in river water and soil sample Class compound River water Soil −1 −1 −1 −1 MDL (μg L )LOQ (μg L )MDL (μg kg ) LOQ (μg kg ) Penicillins Amoxicillin 7.1 22.5 9.1 28.9 Ampicillin 10.9 34.5 13.2 42.0 Penicillin G 12.0 38.1 8.5 27.0 Tetracyclines Chlortetracycline 7.7 24.5 2.9 9.3 Oxytetracycline 8.7 27.6 8.7 27.6 Tetracycline 12.3 39.2 8.2 26.3 Macrolides Spiramycin 2.2 7.0 1.2 4.0 Tylosin 2.1 6.6 4.9 15.6 Sulfonamides Sulfadiazine 8.8 28.1 5.9 18.9 Sulfamethazine 6.6 20.9 2.9 9.2 Sulfamethoxazole 6.1 19.3 11.9 37.8 Sulfathiazole 7.2 22.8 3.6 11.3 −1 Accuracy and precision ranged from 0.018 to 0.309 mg L (Table 4). Tylosin was The efficiency of the developed method was verified the most frequently detected compound, with values of −1 based on the recovery of the target analytes (Table 3). up to 0.251 μg L (site 4), whereas ampicillin and peni- Most antibiotics showed moderate recovery values in cillin G were not detected. Ampicillin and penicillin G, river water and soil, ranging from 61.9–115.8% and which are beta-lactam antibiotics, are not frequently 60.4–111.6%, respectively. However, amoxicillin (12.1– found in the environment because of the instability of 32.5%) and spiramycin (36.8–59.1%) showed low recov- the beta-lactam ring due to beta-lactamase or chemical eries in all the sample matrices. The precision calculated hydrolysis . Cha et al. also reported that almost all and expressed as relative standard deviation (RSD) β-lactam antibiotics were not detected in surface water ranged from 0.7–12.2% in river water and 1.0–12.7% in and wastewater in urban and agricultural areas in north- soil. Therefore, we excluded amoxicillin and spiramycin ern Colorado, USA, and ampicillin was found only once −1 from the target analytes in this study because these com- in 11 ng L out of 60 samples . pounds were not appropriate for quantitative analysis of Chlortetracycline, oxytetracycline, and tetracycline river water and soil using the developed method. were detected in the ranges of 0.107–0.173, 0.373–0.309, −1 and 0.080–0.135 μg L , respectively. In addition, sul- Applications to agricultural environmental samples fonamide group antibiotics were detected in the range −1 The developed method was applied to identify and quan - of 0.018–0.067 μg L , except for sulfadiazine, and they tify VAs in river water, sediment, and arable soil samples, were detected at lower concentrations than the tetracy- and these environmental samples were collected from the cline group antibiotics. It has been reported that sulfona- Muhan river in Yesan-gun, Chungcheongnam-do. In this mide antibiotics are detected more frequently in aquatic area, livestock farms and treatment facilities are adjacent environments than tetracycline antibiotics because of to the river, so it is easy to identify the pattern of residual their high water solubility and low sorption coefficient VAs that introduce directly or indirectly into the environ- (K ) values . Dong et al. detected sulfadiazine and ment by antibiotics pollution sources. sulfamethoxazole in river water near arable land and live- −1 Residual antibiotics can be introduced into river water stock farms up to 1.5 and 44.1 ng L , respectively, but −1 by rainfall runoff from nearby arable soil and livestock detected oxytetracycline up to 835.1 ng L with a fre- farms, or effluents from livestock wastewater treatment quency higher than sulfonamide antibiotics . These plants (WWTPs) [41, 42]. In this study, seven antibiot- results indicate the high possibility of leakage into the ics belonging to three classes were detected in river water agricultural environment due to the high sales volume samples, and the measured concentrations of the VAs and usage of tetracycline antibiotics . K im et al. Applied Biological Chemistry (2023) 66:20 Page 9 of 11 Table 3 Recovery and precision of the developed method for 12 antibiotics −1 Class compound Concentration (mg L ) River water Soil Recovery (%) RSD (%) recovery (%) RSD (%) Penicillins Amoxicillin 0.1 15.3 3.7 32.5 6.4 1.0 12.1 2.3 13.9 8.7 Ampicillin 0.1 97.7 10.9 72.5 2.6 1.0 82.1 1.7 62.4 9.3 Penicillin G 0.1 91.7 12.2 79.8 10.5 1.0 101.6 0.9 78.9 9.1 Tetracyclines Chlortetracycline 0.1 74.6 5.1 72.9 9.9 1.0 87.4 2.7 90.0 1.6 Oxytetracycline 0.1 82.9 2.8 86.4 7.2 1.0 92.2 6.6 110.0 12.7 Tetracycline 0.1 114.5 0.7 99.9 4.0 1.0 113.0 2.1 111.6 2.9 Macrolides Spiramycin 0.1 36.8 5.5 50.9 1.0 1.0 59.1 6.7 57.5 2.4 Tylosin 0.1 103.2 5.8 96.6 5.4 1.0 115.8 3.9 99.5 2.2 Sulfonamides Sulfadiazine 0.1 112.8 7.7 79.0 9.5 1.0 85.8 11.6 77.2 9.9 Sulfamethazine 0.1 80.7 3.1 77.4 8.1 1.0 112.4 5.0 74.3 11.1 Sulfamethoxazole 0.1 93.0 6.1 62.8 7.8 1.0 102.1 2.0 88.7 5.5 Sulfathiazole 0.1 61.9 4.7 60.4 7.5 1.0 63.3 1.3 65.9 7.0 Table 4 Concentrations of target analytes in river water samples Location CTC OTC TC TYL SMZ SMX STZ −1 1) River water (μg L ) Site 1 0.173 0.202 0.080 0.039 0.035 0.032 ND Site 2 ND ND ND 0.013 ND ND ND Site 3 ND 0.309 ND 0.01 ND 0.056 0.067 Site 4 0.109 ND 0.125 0.251 0.018 ND ND Site 5 0.107 0.173 0.135 0.014 ND ND ND −1 Sediment (μg kg ) Site 1 ND ND ND ND 3.70 ND ND Site 2 ND ND ND ND ND ND ND Site 3 9.04 ND 7.62 ND 4.27 ND 1.45 Site 4 8.86 ND ND 5.22 3.73 ND ND Site 5 ND ND ND ND 4.96 ND ND −1 Arable soil (μg kg ) Site 1 ND ND ND ND ND ND ND Site 2 ND ND ND ND ND ND ND Site 3 ND ND ND ND ND ND ND Site 4 ND ND ND ND ND ND ND Site 5 ND ND ND ND 3.66 ND ND 1) ND Not detected Kim et al. Applied Biological Chemistry (2023) 66:20 Page 10 of 11 RSD Relative standard deviation Five antibiotics (chlortetracycline, tetracycline, tylosin, SD Standard deviation sulfamethazine, and sulfathiazole) were detected in sedi- SDZ Sulfadiazine ment samples (Table 4). The identified antibiotics in sedi - SMX Sulfamethoxazole SMZ Sulfamethazine ment were less diverse than in river water; however, they SPE Solid phase extraction −1 have high concentrations ranging from 1.45 to 9.04 μg kg SPM Spiramycin when compared with river water samples. These results may STZ Sulfamethazine TC Tetracycline be associated with the continuous accumulation of residual TYL Tylosin antibiotics derived from effluents and runoff from arable VAs Veterinary antibiotics soils. Tetracycline antibiotics with a high adsorption capac- WWTP Wastewater treatment plant −1 ity to soil were detected from 7.62 to 9.04 μg kg , whereas sulfonamide antibiotics were detected in relatively low con- Supplementary Information −1 centrations in the range of 1.45–4.96 μg kg . The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s13765‑ 023‑ 00777‑3. Sulfamethazine was the only identified target antibiotic among all the arable soil samples and was detected at a con- Additional file 1: Table S1. Physicochemical properties of 12 antibiotics. −1 centration of 3.66 μg kg only once at site 5 (Table 4). This Table S2. LC‑MS/MS parameters for the analysis of antibiotics. Table S3. result suggests that the antibiotics detected in river water Standard solution calibration curves equations and coefficient of deter ‑ mination. Table S4. Linearity of matrix‑matched calibration curves for and sediment were not derived from arable soil. target analytes. Table S5. Matrix effect of 12 antibiotics in river water and An SPE-LC-MS/MS analytical method for the simulta- −1 soil sample. Fig. S1. Extracted ion chromatogram in spiked (0.025 mg L ) neous determination of 12 VAs in river water and soil was samples developed, and this method was successfully applied to moni- tor residual antibiotics in agricultural environments. This Acknowledgements method was validated according to the US EPA method 1694, This work was carried out with the support of “Cooperative Research Program for Agriculture Science and Technology Development (Project No. except for amoxicillin. It satisfactorily fulfilled the criteria of PJ01488502)” Rural Development Administration, Republic of Korea. linearity, accuracy, and precision for the 10 antibiotics in river water and soil. Additionally, the low values of MDL and LOQ Author contributions JW wrote original draft manuscript and conducted formal analysis; YK con‑ suggest that accurate quantitative analysis of trace antibiotics ducted and validated formal analysis; SH gave an idea and conducted data in river water and soil is possible. The analysis of environmen - analysis OK conducted data analysis and correction of context; YB corrected tal samples showed the presence of VAs in the river water, in the context and gave an idea; SC conceptualized and supervised whole manuscript. All authors have read and approved the final manuscript. sediment, and arable soil samples. The determined concen - −1 trations ranged between 0.013–0.309 μg L in river water Funding −1 and 1.45–9.04 μg kg in sediment and soil samples, and the This study was funded by Grant No. PJ01488502 from the Rural Development Administration, Korea. highest and most diverse antibiotics were detected at sites 3 and 4, which were affected by livestock activity. The detection Availability of data and materials of antibiotics demonstrates the necessity for systematic moni- All data generated or analysed during this study are included in this published article. toring in agricultural environments. In addition, these results are expected to be the primary data sources for developing Declarations analytical methods for VAs in livestock manure compost and liquid fertilizer. Competing interests The authors declare that they have no competing interests. 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Applied Biological Chemistry – Springer Journals
Published: Mar 24, 2023
Keywords: Tetracyclines; Sulfonamides; Analytical method; Water; Sediment; Soil
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