- Data Article
- Open Access
Chemical assessment of mycotoxin contaminants and veterinary residues in Costa Rican animal feed
International Journal of Food Contaminationvolume 6, Article number: 5 (2019)
When present in animal feedstuff, mycotoxins contaminants and antibiotic residues can have negative implications for animal production and Public Health, including the transmission of carcinogenic compounds and the selection of antibiotic resistant bacteria, respectively. So far there are no available methods in which both mycotoxins and antibiotic residues are analyzed using a parallel extraction approach. To address this issue, we developed a LC/MS methodology with high sensitivity (0.005 to 6.42 and 24.55 to 132.73 μg kg− 1 for mycotoxins and antimicrobials) and specificity (unique target ion mass/charge) that allows the detection of 26 mycotoxins and 23 antibiotic residues in animal feedstuff and validated it through the determination of these analytes in 294 animal feed and feed ingredient samples in the framework of a country-wide surveillance program. Two hundred and five of these samples were analyzed for mycotoxins and 89 for antibiotics.
Fumonisin was the most frequently toxin found, with FB1 and FB2 presenting prevalences of 50 and 52% and maximum concentrations of 14,927.61 and 8646.67 μg kg− 1, respectively. Other toxins, including diacetoxyscirpenol n = 4/101 (3.96%), fusarenon-X n = 2/101 (1.98%), citrinin n = 2 (1.98%), and patulin n = 1 (0.99%) were rarely found. Toxicologically relevant concentrations of toxin metabolites, such as HT-2 (6.38–485.49 μg kg− 1) and 3−/15-acetoxydeoxynivalenol (877.89–3236.56/5.44–1685.3 μg kg− 1), were also found. Few samples exceeded threshold mycotoxin concentrations defined in current EU guidelines. Dairy cattle and swine feeds included the higher number of samples exceeding guideline values (n = 6 and n = 5, respectively). From the total of samples analysed for antibiotics, 7.7% (n = 7/89) were classified as medicated for poultry and pigs. Unexpectedly, 57% of these medicated samples contained no detectable antibiotics (n = 4/7). The remaining 43% of the samples (n = 3/7) presented inconsistencies regarding the concentration of analytes declared on the labels or the antibiotics found. Likewise 74.6% (n = 50/67) of the non-medicated feed samples analyzed had antibiotic residues. Additionally, we analyzed commercial monensin standards for purity and evaluate batch-to-batch flushing feed industry practices.
Herein we report the results for a year-wide analysis for mycotoxins and antibiotics in feed samples. Mycotoxins, several metabolites, and the occurrence of these emerging contaminants were evaluated and antibiotic residues in non-medicated feed samples were found using a targeted MS-based LC approach. This validated multi-analyte method is expected to facilitate the monitoring and surveillance of contaminants, from natural and anthropogenic origin, in animal feed.
Mycotoxins and antibiotics represent natural and intentional contaminants of animal feed (Pinotti et al. 2016; Tang et al. 2017), respectively. The former group of compounds are produced by several fungal species that grow, during the pre- and postharvest stages of the food chain, on cereals, grains, nuts, spices, fruits and by-products commonly used as raw material in animal feed elaboration (Pinotti et al. 2016; Alshannaq and Yu 2017).
The most important mycotoxins contaminating animal feed include the aflatoxins B1, B2, G1, and G2, patulin, citrinin, ochratoxin A and B, fumonisin B1, Fumonisin B2, Type A trichothecenes, zearalenone, and emerging mycotoxins such as enniatins (Eskola et al. 2018; Marín et al. 2013; Wu et al. 2014). Most of these substances are stable and cannot be eliminated by common feed and food production processes (Karlovsky et al. 2016; Pinotti et al. 2016), hence they can diminish animal productivity or exert toxic effects on animals (Bezerra da Rocha et al. 2014; De Ruyck et al. 2015; Zain 2011), such as cancer (i.e. aflatoxin B1 and fumonisin B1, Ostry et al. 2017). Moreover, since they can accumulate in meat, milk, or eggs, they have the potential to reach and affect the health of end consumers (Bozzo et al. 2011; Alshannaq and Yu. 2017). For these reasons national and international agencies regulate the presence of mycotoxins in animal feedstuff and good manufacturing practices have been implemented to avoid or reduce mycotoxin contamination in food and feed (Ndemera et al. 2018; CODEX 2014).
In contrast to mycotoxins, which are natural contaminants and therefore difficult to avoid in raw materials and animal feed, antibiotics such as monensin and tetracycline are intentionally added to animal feed for prophylaxis and metaphylaxis purposes (Anadón et al. 2018; Rojek-Podgórska 2016) or as growth promoters to improve feed efficiency (Cancho Grande et al. 2000; Rojek-Podgórska 2016). It has been shown that the exposure of food-producing animals to antibiotics leads to allergic reactions and the selection of antimicrobial resistant bacteria (FAO 2002; WHO 2015). Consequently, strict vigilance, tutelage, follow-up, and regulation protocols have been established in feed manufacturing and animal production (COMIECO 2012; European Commission 2001; European Commission 2004; FAO 2002; FDA 2018; MAG 1985; WHO 2015).
Despite the paramount importance of contaminant monitoring on feed quality and Public Health (van der Fels-Klerx et al. 2016a, b), there is scarce data on the occurrence and co-occurrence of mycotoxins and antibiotics in feed ingredients and animal feed produced in developing economies.
LC-MS methods have been used for screening, preparative, and confirmation purposes; in animal feed different LC-MS methods have been developed for multiple antibiotic residues analyses (Boix et al. 2014; Granados-Chinchilla and Rodríguez 2017). Also, multiple-mycotoxin methods have been applied in animal feed (Njumbe et al. 2015; Granados-Chinchilla 2017). So far few available methods can assess both antibiotic residues and mycotoxins using a single extraction approach and a solvent system during chromatography. To tackle this gap, we developed a LC/MS-based methodology that allows the analysis of 26 mycotoxins and 23 antibiotic residues in these matrices with high sensitivity and specificity. We applied our method to 294 samples collected in a country-wide surveillance program and found mycotoxins and antibiotics that are not in accordance with the respective regulations.
Selection of feed and feed ingredients to be tested, number of samples, and sampling sites were chosen by feed control officials. Selection considered the most common feedstuffs used in Costa Rica, import and export regulations, contamination risk factors, the productivity of the feed industry, and the risk for human and animal health associated with each feed or feed ingredient. Sampling was performed following the Association of American Feed Control Officials recommendations for mycotoxin test object collection (AAFCO 2017). Samples were analyzed immediately upon arrival at the laboratory. Samples were quartered and sieved to a final particle size of 1 mm.
A total of n = 205 animal feed and feed ingredient samples of about 5 kg were received in the laboratory for analysis. The samples collected represent n = 57 Costa Rican feed manufacturing plants during 2018 with the collaboration of government official inspectors as part of an annual countrywide surveillance program. Samples included dairy cattle feed (n = 64; 31.2%), swine feed (n = 19; 9.3%), corn meal (n = 18; 8.8%), beef cattle feed (n = 14; 6.8%), soybean meal (n = 12; 5.9%), calf feed (n = 11; 5.4%), poultry feed (n = 11; 5.4%), poultry layer feed (n = 9; 4.4%), forage (n = 8; 3.9%), wheat middlings (n = 6; 2.9%), horse feed (n = 4; 2.0%), dog dry food, cat dry food, fish feed (Tilapia and Trout feed), shrimp feed (n = 3; 1.5% each), palm kernel meal, rice meal, sheep feed, and almond meal (n = 2; 1%, each), banana peel, cassava meal, citrus pulp, distillers dried grains, rice bran, and rodent feed (n = 1; 0.5%, each).
In the same fashion, as mycotoxin analysis, n = 89 samples were collected from n = 33 Costa Rican feed manufacturing plants for antibiotic residue analyses. This subset of samples included feed for swine feed (n = 29; 32.6%; n = 5/29 starter, n = 22/29 growers, and n = 2/29 finishers), poultry layer feed (n = 20; 22.5%), poultry feed (n = 17; 19.1%; n = 4/17 finishers, n = 6/17 growers, and n = 7/17 starters), fish feed (Tilapia and Trout feed, n = 4 and n = 1; 4.5 and 1.1%, respectively), shrimp feed (n = 3; 3.3%), dairy cattle feed (n = 3; 3.3%), and horse feed (n = 1; 1.1%). Additionally, 7.9% (n = 7), of the samples correspond to feed ingredients (i.e., a calcium salt and ground corn) used during batch flushing. Finally, 4.5% (n = 4) commercial imported feed grade monensin samples were subjected to test for conformity.
LC grade acetonitrile (ACN, catalog number 100029, LiChrosolv®), methanol (MeOH, catalog number 106035, LiChrosolv®) and ethanol (EtOH, catalog number 111727, LiChrosolv®) formic acid (FA, catalog number 100241, 98–100%, EMSURE® ACS, Reag. Ph Eur) were acquired from Merck Millipore (Merck KGaA, Darmstadt, Germany). Sodium chloride (catalog number 31434), potassium chloride (catalog number P3911), sodium phosphate dibasic (catalog S9763), and potassium phosphate monobasic (catalog number 1551139) were acquired from Sigma-Aldrich (St. Louis, Mo, USA). Ultra-High Pure Nitrogen was purchased from Praxair Technology Inc. (Alajuela, Costa Rica). Ultrapure water [type I, 0.055 μS cm− 1 at 25 °C, 5 μg L− 1 TOC] was obtained using an A10 Milli-Q Advantage system and an Elix 35 system (Merck KGaA, Darmstadt Germany). Trilogy® (Washington, MO, USA) solutions for ochratoxin A (catalog number TSL-504), zearalenone (catalog number TSL-401), HT-2 toxin (catalog number TSL-333), citrinin (catalog number TS-904), T-2 toxin (catalog number TSL-314), fumonisin B1 and B2 (catalog number TSL-202), patulin (catalog number TSL-601), and trichothecenes (catalog number TS-307) were used as standards. Analytical pure standards for fumonisin B3 (catalog number 32606), ennantin B1 (catalog number E5286), ennantin B (catalog number E5411), β-zearalenol (catalog number Z2000), α-zearalenol (catalog number Z0166), sterigmatocystin (catalog number 53255), aflatoxin M1 (catalog number A6428), ochratoxin B (catalog number 32411), narasin (catalog number N1271), chloramphenicol (catalog number C0378), oxytetracycline (catalog number O4636), florfenicol (catalog number F1427), demeclocycline (catalog number D6140), tylosin (catalog number T6134), tetracycline (catalog number T3258), monensin (catalog number M5273), minocycline (catalog number M9511), erythromycin (catalog number 856193), chlortetracycline (catalog number 46133), doxycycline (catalog number D9891), sulfamethazine (catalog number S6256), penicillin G (P3032), lincomycin (catalog number 31727), spectinomycin (catalog number 46738), ciprofloxacin-d8 (VETRANAL™, catalog number 32982), flunixin-d3 (VETRANAL™, catalog number 34083), and virginiamycin S1 (catalog number V4140) and M1 (catalog number V2753) were purchased from Sigma-Aldrich. Methacycline (catalog number 3963-95-9), 4-epioxytetracycline, 4-epichlortetracycline, 4-epianhydrotetracycline, and 4-epitetracycline analytical standards were purchased from ACROS Organics (New Jersey, USA). All standards were used to construct five-point calibration curves (from 1.00 to 6.25 × 10− 2 mg L− 1 for each mycotoxin, Table 1). Likewise, a standard containing exactly 1.00 mg L− 1 was used to obtain response factors (Areastd/Concentrationstd) for each veterinary drug. Pure standards were used, as well, to assess the base, molecular and target ion of each compound for quantification purposes. TR-MT100 Trilogy® Multitoxin Reference Material MT-C-999-G (naturally contaminated cornmeal) was tested in parallel for quality control purposes during each batch of analyses. A sample of medicated dairy feed (AAFCO check sample 201,530) was used similarly during the veterinary drug assays. Chromatographic quality nitrogen was generated with a PEAK Scientific generator (NM32LA, Inchinnan, United Kingdom).
Feed sample extraction
The extraction method was adapted from a previously reported method for cornmeal testing (Wang et al. 2013). Briefly, 25 g of each sample was extracted for 2 min at 18000 rpm with 100 mL of an ACN:H2O:CH3CO2H solution with a volume ratio of 74:25:1 using an Ultra-turrax® homogenizer (T25, IKA, Werke GmbH & Co. KG, Staufen in Breisgau, Germany). Fresh material (e.g. forages) were processed using twice the solvent volume mentioned above. The supernatant was removed and filtered by gravity through Whatman® 541 ashless filters (GE Health Life Sciences Little Chalfont, Buckinghamshire, UK). Then, a 2 mL aliquot was pipetted to a 25 mL volumetric flask and filled with phosphate buffer solution (PBS at pH 7.4 containing NaCl, 150 mmol L− 1; KCl, 2.50 mmol L− 1; Na2HPO4, 4.50 mmol L− 1; KH2PO4, 1.50 mmol L− 1). For sample cleanup, Oasis® HLB columns (WAT094226, 3 cc, 60 mg, 30 μm particle size, Waters Corporation, Milford, MA, USA) were activated and conditioned with 2 mL MeOH and equilibrated with 2 mL of a MeOH/H2O solution (5:95 volume ratio) using a SPE 12 port vacuum manifold (57,044, Visiprep™, Supelco Inc., Bellefonte, PA, USA) operating at 15 mmHg. Sample extracts were then passed through the columns at a flow rate of 1 mL min− 1. Columns were washed with 2 mL MeOH/H2O (5:95) and 2 mL of MeOH was used to elute analytes. Eluates were concentrated to dryness under vacuum at 60 °C (Centrivap, LABCONCO, Kansas City, MO, USA), reconstituted with 300 μl of MeOH, and transferred to an HPLC vials with polypropylene inserts (5182–0549, Agilent Technologies, Santa Clara, CA, USA).
Extraction of antibiotics was performed based on a published protocol (Duelge et al. 2017). Briefly, 5.0 g from each sample were mixed into a 50 mL polypropylene centrifuge tube with 50 μL of a 400 μg mL internal standard mix composed of ciprofloxacin-d8 (for fluoroquinolones, sulfonamides and tetracyclines) and flunixin-d3 (for macrolides and β-lactams). This mixture was resuspended with 5 mL acetate buffer (1 mol L− 1, pH 5.0), 10 mL ACN and 10 mL MeOH and the resulting suspension was homogenized for 2 min at 18000 rpm using an Ultra-turrax® homogenizer. Debris and suspended solids were removed by centrifugation at 5000 g for 10 min (Thermo Scientific™ Sorvall™ ST 16R, Waltham, MA, USA) and supernatants were transferred to 50 mL volumetric flasks. The sample was re-extracted with 5 mL of acetonitrile and 5 mL of methanol, dispersed for an additional minute and centrifuged for another 10 min. Both supernatants were combined in the flask and the 50 mL volume was made up with water. A 4-fold dilution with water was performed to reduce organic solvent fraction. An Oasis® HLB SPE cartridge was placed on a 12-port vacuum manifold and conditioned with 2 mL ACN followed by 2 mL water. A 10 mL sample aliquot was loaded onto the reservoir and allowed to pass through the column at the rate of 1 mL min− 1. After drying for 5 min under vacuum (∼10 in Hg), the column was washed with 2 mL water and 2 mL of MeOH and dried again for 5 min under vacuum. Analytes were eluted with 1 mL of 50:50 MeOH:ACN into a 2 mL HPLC vial.
LC equipment and analysis conditions
All assays were performed using an Agilent Technologies LC/MS system equipped with a 1260 infinity quaternary pump (61311C), a column compartment (G1316A), an automatic liquid sampler module (ALS, G7129A) and a 6120-single quadrupole mass spectrometer with electrospray ionization ion source (Agilent Technologies, Santa Clara, CA, USA).
Mycotoxin contaminant analysis
The gradient analysis was performed at 0.15 mL min− 1 using as solvents A ACN and B H2O, both acidified with FA at 0.1 mL/100 mL. The gradient was set as follows: at 0 min 10% A, at 4 min 10% A, at 22 min 100% A, at 25 min 10% A and finally at 35 min 10% A, obtaining a complete chromatographic separation for 26 toxins (Fig. 1a). A volume of 10 μL was injected into the system. Column compartment was kept at 40 °C during analysis.
Antimicrobial residue analysis
The gradient analysis was performed at 0.8 mL min− 1 using as solvents A ACN, B MeOH, and C water, all acidified with FA at 0.1 mL/100 mL. Gradient was set as follows: at 0 min 100% C, at 20 min 35% A and 65% C, at 23 min 95% B and 5% C, at 24 min 95% B and 5% C, at 28 min 95% B and 5% C, at 29 min 100% C and finally at 38 min 100% C, obtaining a complete chromatographic separation for 23 antibiotics (Fig. 1b). A volume of 1 μL was injected into the system. Column compartment was kept at 20 °C during analysis.
Chromatographic column and MS detection
Considering the variability in structures, functional groups, and chemical moieties of the target analytes, a reverse phase C18-based chromatographic column (Zorbax Eclipse Plus, 3.0 mm ID × 100 mm, 3.5 μm, P/N 959961–302, Agilent Technologies, Santa Clara, CA, USA) was used for analytical separation. For each analyte, the cone electrical energy was cycled (i.e., from 20 to 280 V) to determine the voltage that yielded the highest sensitivity (Table 1). Drying gas, nebulizer pressure, drying gas temperature and capillary voltage was set, respectively, to 10.0 L min− 1, 50 psi, 350 °C, and 4000 V for positive ion mode electrospray ionization (ESI+). Total ion chromatographs (scan mode: mass range, cone voltage and detector gain set to 50–750 m/z for mycotoxins or 50–1000 m/z for antibiotics, 120 V and 10.0, respectively) of individual standards were used for choosing the ion that would later be used for selected ion monitoring (SIM mode, peak width and cycle time set to 0.1 min, and 0.60 s cycle− 1). The molar mass, target ions, retention times, cone voltage, and obtained limits of detection and quantification of each analyte are presented in Table 1. During MS molecular ion analysis, signals to be monitored were clustered into time programmed SIM groups to minimize the number of ions acquired at any one time (Table 1 and Fig. 1a, b).
Method validation was performed according to US FDA (2015) and ICH (Borman and Elder, 2018) validation criteria. Quality assurance materials, both for mycotoxin and antimicrobial assays, were tested several times under reproducibility conditions (see footnote for Table 2). Standard deviation certified by the manufacturer or calculated z values were used as method performance parameters. Acceptable z values (i.e., from − 2 to 2) were considered as proof of the method acceptable bias, accuracy, and recovery. In this scenario, z values indicate the number of standard deviations from the mean a data point is. Mathematically, z = (x – μ)/σ. Then, z values are calculated as follows: robust mean concentration (obtained from the method/analyte performance agreed among several laboratories) subtracted by the result obtained by the laboratory divided by the robust standard deviation. To assess intraday repeatability, n = 3 reference materials were extracted and quantified by the same analyst, equipment, and environmental conditions. As an additional quality parameter, reproducibility data must coincide with HorRat values (i.e., ranging from 0.3 ≤ x ≤ 1) and predicted values within those expected by Horwitz Trumpet function (Horwitz and Albert 2006; Thomson 2007). A certified sample devoid of any of the analytes of interest; equine, cat and beef non-medicated and mycotoxin feed blanks were obtained (i.e., AAFCO check samples 2018–21, 2018–25, 2018–28). Blank samples and additional solvent blanks were used as chromatographic backgrounds during quantification to remove artifacts, if present. Limits of detection and limits of quantification were assayed using the resulting signal-to-noise ratio obtained from blank matrices. Theoretical limits were assessed by measuring the signal to noise ratio and multiplying it by 3.3 or 10, respectively. Additionally, each compound was verified experimentally, using a dilution-to-extinction method. As a simple precision component, retention times shifts were also studied using another batch of the same chromatographic column (SN USUXR16343), shifts ± 0.2 min were considered acceptable.
Calibration curves parameters (i.e., slopes and intercepts), coefficients of determination, limits of detection, and standard errors were computed as a linear fit model using SAS JMP 13 (Marlow, Buckinghamshire, England). Spearman rank order test was used to determine association with sampling date and toxin levels; variables with positive correlation coefficients and p < 0.050 tend to increase together (Sigma Plot 14.0 Systat Software, Inc., San Jose, CA, USA).
Results and discussion
Dynamic, working, and linear ranges were established at 1.15 to 1.25 × 10− 2, 1.00 to 6.25 × 10− 2, and 7.14 × 10− 1 to 4.46 × 10− 2 mg L− 1, respectively. Linearity was assessed as average of multiple calibration curves measured under reproducibility conditions. Regarding accuracy, bias, and reliability, our method only differed from those declared by the manufacturer by one standard deviation (Table 2). In this case, the calculated uncertainty ranged from 12.29 to 18.11% of the reported values. Reproducibility, expressed as relative standard deviations, ranged from 8.34 to 17.49%. No interferences were observed from 0 to 25 min (Fig. 2a). On the other hand, several non-specific signals arise from 25 to 30 min region even on blank matrix samples, which makes ennantin congener identification relatively more complex, though this does not hinders sensitivity for these mycotoxins (Table 1 and Fig. 2a). An unidentified signal with a 20.44 min retention time accompanied all samples in which fumonisin fractions were found. Background subtraction aid to simplify the integration and quantification steps. Based on its mass spectra and retention time comparison using an analytical standard, this signal was identified as fumonisin B3 (experimental ion obtained [M + H]+ 706.2 m/z while fumonisin B3 has a molar mass of 705.839 g mol− 1). Detector gain for all mycotoxins set at 10, except deoxynivalenol and nivalenol set at 15.
Limits of detection were established between 24.55 and 132.73 μg kg− 1. Average z values of − 0.13 and 0.26 were determined for monensin and chlortetracycline, respectively, indicating excellent accuracy and veracity (Table 2). Acceptable bias is also attained when the experimental data is compared to a known concentration (Table 2). The measured relative uncertainty ranged between 5.76 to 7.65% of the reported values. No injection-injection carryover was observed. Reproducibility values are within recommended values (Table 2). In the region where monensin and narasin elute some matrix interferences are observed; however, limits of detection are still relatively low and identification can be performed effortlessly (Fig. 2b). Target ions selected for each compound (see for example Fig. 3a, b) and selection of molecular ion is performed after pure standard complete mass spectra is obtained (see for example Fig. 3b, d). Interferences are screened considerably in SIM mode. Analysis of a 20 g monensin/100 g feed quality standard with our method indicated a concentration of (17.04 ± 0.98) g/100 g (Table 3). As our method is performed at 20 °C, retention times are susceptible to room temperature shifts. We observed 0.5 min retention time swings if room temperature was raised 2 °C (from 20 to 22 °C). Detector gain for all antimicrobials was set at 1.
Method application for mycotoxins in feed
Overall mycotoxin prevalence
In relative terms, among the assayed toxins, fumonisin contamination was the most frequent. Fumonisin fraction B1 and B2, exhibited prevalences of 49.76 and 53.66%, respectively; Table 4. Maximum concentrations reached 4554.36 and 8646.67 μg kg− 1 for FB1 and FB2, respectively (Table 4). However, with the exception of the two above-mentioned toxins, the rest of the toxins presented relatively low prevalence, as the majority of the toxins resulted below the method’s limit of detection (i.e.,; from n = 170/205 to n = 203/205) (Table 4). Less frequent toxins include fusarenone-X, patulin, β-zearalenol, neosolaniol, ochratoxin B, sterigmatocystin, diacetoxyscirpenol, and citrinin, which were found in n = 2/205 (0.98%), n = 2/205 (0.98%), n = 3/205 (1.46%), n = 4/205 (1.95%), n = 6/205 (2.93%), n = 6/205 (2.93%), n = 7/205 (3.41%) and n = 8/205 (3.90%) samples. The presence of sterigmatocystin in some samples should be an indicative of Aspergillus spp. metabolism [serves as a late intermediate in aflatoxin biosynthesis (Viegas et al. 2018; Díaz-Nieto et al. 2018)]. Patulin was found in a dairy cattle samples, which may be related to the inclusion within these feed formulations of citrus pulps (Zbyňovská et al. 2016); this toxin is usually related to fruits. Toxicologically relevant concentrations of toxin metabolites, including HT-2 (6.38–303.22 μg kg− 1), 3-acetoxydeoxynivalenol (1.88–3236.56 μg kg− 1), were found. By contrast, deoxynivalenol/15-acetoxydeoxynivalenol (15.06–364.10/1.74–355.60 μg kg− 1) concentrations were relatively low. Diacetoxyscirpenol is a trichothecene mycotoxin produced by a Fusarium mold found in temperate regions (Sospedra et al. 2010), said toxin was found in soybean meal and corn meal samples which are imported from countries such as the USA. Deoxynivalenol has been reported previously in marine animal feeds (Pietsch et al. 2013), though our data only found 3-acetyldeoxynivalenol, its incidence indicates that an original high concentration of deoxynivalenol was once present. Deoxynivalenol metabolites exhibit higher than the parent compounds, and co-occurrence of the latter and its acetylated relatives have been reported (Payros et al. 2016). Considerable concentrations of α/β-zearalenol (0.25–920.65/228.03–1900.62 μg kg− 1) were also found. On another hand, enniatin B was also relatively prevalent (15.12%) and exhibited levels of 143.11–3566.81 μg kg− 1. Interestingly, for the case of aflatoxins, the AFG2 fraction was found to be the most frequent among the samples tested samples 12.68% (n = 26/205) (Table 4). Maximum concentrations reach for aflatoxin are 22.39 (AFB2) and 21.84 (AFG2) μg kg− 1 (Table 4). Animal feed contaminated with mycotoxins can negatively impact health, productiveness and general well-being of the animal additionally, carry-over to other food matrices [e.g., milk (Fink-Gremmels 2008) and eggs (Lee et al. 2016)] is a real concern. Of special concern is aflatoxin prevalence in feeds as they are recognized as cytotoxic, teratogenic, and immunotoxic (Granados-Chinchilla et al. 2017).
Mycotoxin prevalence by feedstuff and legislative thresholds
From the feed ingredients examined, soybean and corn meal had the highest prevalence for deoxynivalenol (42.86%) and fumonisin B2 (25.00%), respectively (Table 5). When arranged by feed type, all feeds contaminated with fumonisin exhibited similar prevalence (i.e., 19.89–37.50%) (Table 5). Fumonisins, though found with the higher concentrations and frequency, are the toxins with laxer legislation or guideline values, except the case of for pigs which are set to 5000 mg kg− 1. Fumonisins have demonstrated particular toxicity toward pigs (prevalence of 25.43% for both FB1 and FB2, Burel et al. 2013; Schertz et al. 2018). Though, higher fumonisin prevalence was found in poultry feed and pet food. Toxins found herein in dry extruded pet food have been reported previously (Gazzotti et al. 2015). Citrin was found in pet food which is relevant since dogs are very susceptible to this molecule (EFSA 2012). Companion animal exposure to mycotoxin through feed is especially worrisome due to their closeness to humans. Ochratoxin A exceeded recommendations (i.e., > 50 μg kg− 1) in pig and sow feeds with n = 11 samples in this condition (Table 5). Ochratoxin group mycotoxins have been reported to be linked to serious animal diseases including poultry ochratoxicosis, and porcine nephropathy (Heussner and Bingle 2015). Overall, beef cattle, swine and dairy cattle feeds showed the most number of incidents with n = 51, 54, and 186 samples with some degree of mycotoxin contamination. Dairy cattle and swine feeds included the higher number of samples exceeding guideline values (n = 3 with zearalenone and n = 5 with zearalenone (n = 2), fumonisin B2 (n = 1), ochratoxin A (n = 1), and aflatoxin G1 (n = 1), respectively, Table 5). Interestingly, the two samples exceeded the 20 μg kg− 1 total aflatoxin legal threshold defined by the European Commission with just one fraction (Table 5). Enniantin B were found in significant concentrations in several matrices (up to 711.74, 914.05, 1115.50, and 2595.64 μg kg− 1 in calf, dairy cattle, beef cattle, and swine feeds, respectively) (Table 5). Overall, few samples exceeded threshold concentrations defined in current guidelines. Though legal bounds are set considering only one contaminant, synergy due to mycotoxin co-occurrence is to be considered (Streit et al. 2012; Alassane-Kpembi et al. 2017); this is possible through multi-toxin methods such as the one presented here (Malachová et al. 2017).
Using the toxin profile suggested here, toxin co-occurrence seems to be a fairly common event (n = 123 samples presenting 2+ toxins) (Table 6). Counterintuitively, finding 4 toxins in a feed seems to be more common (n = 34) followed by 5, 1, 2, and 3 with n = 28, 27, 25, and 24, respectively (Table 6). The diversity of mycotoxins found is higher in two specific groups of feed; with n = 20 (dairy cattle) and n = 13 (in swine feed) different analytes identified overall (Table 6). Also, dairy cattle was found to be the matrix most contaminated with multiple toxin simultaneously (i.e., up to 9 different toxins) (Table 6). The most common events of co-occurrence for samples with n = 2 toxins occurring simultaneously were FB1 + FB2 (n = 14/25, 56.00%) and FB2 + AFG2 (n = 5/25, 20.00%) (Table 6). Additive cytotoxic effects have already been reported in the presence of two or more mycotoxins (Fernandez-Blanco et al. 2018; Zhou et al. 2017). Similarly enniatin B has demonstrated adverse effects and changes in gene expression over different cell lines (Jonsson et al. 2016; Manyes et al. 2018). Along with toxins such as trichothecenes, fumonisins, and zearalenone are among the battery of metabolites biosynthezied by Fusarium spp. (Nesic et al. 2014; Liuzzi et al. 2017). The metabolic burden is also higher when several toxins are found in the same feed (Milićević et al. 2010; Alshannaq and Yu 2017). With mass-based methods, the analysis of masked toxins (Berthiller et al. 2013; Gratz 2017) and metabolites (Warth et al. 2012; Streit et al. 2013; Abdallah et al. 2017) in the feed is a real possibility. Furthermore, mycotoxin secondary product analysis in other related matrices food matrices is promising (Escrivá et al. 2017).
With exception of levels for AFB2 (r2 = 10.762; p = 0.0212) and T-2 toxin (r2 = 31, p < < 0.0001), no other toxin seem to associate with the sampling date. For this two toxins the latter result indicates that as the year progresses (in Costa Rica, dry season and rainy season are defined as per mean precipitation, the former demarcated by the months between December and April where x < 80 mm rain) AFB2 and T-2 toxin increase. However, in general terms, toxin prevalence did increased during the month of September–November. Toxins 3-acetyldeoxynivalenol (Fig. 4a), T-2 toxin (Fig. 4b), enniatin B (Fig. 4c), both fumonisin fractions (Fig. 4d) aflatoxin fraction B2 and B1 (Fig. 4e) and zearalenone (Fig. 4f) showed this trend. In contrast, aflatoxin G fractions showed a more scattered behavior (Fig. 4f). Ample scattering was also true for deoxynivalenol (Fig. 4a) and enniatin B1 (Fig. 4b) and most metabolites such as 15-acetyldeoxynivalenol (Fig. 4a), HT-2 toxin (Fig. 4b), α-zearalenol (Fig. 4f). An increase in toxin prevalence in September could correspond to the start of the rainiest part of the season in the country. This specific month exhibited, for 2018, a precipitation ranging from 93.4 to 667.8 mm and 11 to 29 rainy days. However, we already established for aflatoxins alone that no clear association was found between aflatoxin prevalence and season, in a tropical country such as Costa Rica (Granados-Chinchilla et al. 2017). Although this contrasts with findings in other countries with more defined seasons for feed and ingredients alike (Abdou et al. 2017; Blandino et al. 2017). Furthermore, prediction of toxin behavior and seasonal variations are more challenging due to climate change (van der Fels-Klerx et al. 2016a).
Method application for antimicrobial residues in feed
Residues found in feed routine samples
Table 7 also shows the veterinary residues found in the feed samples, including some ionophores, tetracyclines, and florfenicol, among others. From the total of samples collected for veterinary residue assay, 7.9% (n = 7/89) belong to feed samples declared as medicated for poultry and pigs, mainly for starting and finishing stages. Antibiotics used in animal early life stages are intended to improve health and performance and diminish morbidity and mortality in the individuals who are referred to the next production stage (Anadón et al. 2018; Mehdi et al. 2018). On another hand, the use of antimicrobials at the end of the production cycle is designed to improve animal weight gain and feed efficiency (Cancho Grande et al. 2000). Concentrations higher than those guaranteed or failure to report the antibiotic as a feed ingredient may render withdrawal periods useless. Furthermore, evidence suggests that antibiotic performance enhancing capabilities is lost during the later stages of growth and at the time of commercial processing (Kumar et al. 2018). 57.14% of the medicated samples contained no detectable antibiotics (n = 4/7), though the label stated otherwise. The remaining 42.86% of the samples (n = 3/7) presented qualitative or quantitative incongruences regarding the concentration of analytes declared on the labels or the antibiotics found. On another hand, 74.6% (n = 50/67) of the non-medicated feed samples analyzed, exhibit veterinary residues (Table 7).
Permitted legal usage
Current European Union (Anadón et al. 2018) and US FDA (FAO 2002; FDA 2013; FDA 2018) regulations dictate antibiotic usage in the feed. In-feed therapeutic applications are allowed under some restrictions (European Comission 2001; European Comission 2004; FDA 2013; Anadón et al. 2018). Growth promotion under these circumstances is limited by withdrawal which ensures the reduction of drug persistence on food products for human consumption (Cancho Grande et al. 2000; Anadón et al. 2018; Tang et al. 2017) and resistant isolates in the animal (Beukers et al. 2015; Tang et al. 2017). We found antibiotic residues in medicated and non-medicated feed samples that conflict with said guidance. In medicated animal feeds, it is observed that narasin has concentrations of 44.03 and 227.68 mg kg− 1, in poultry feeds, the last value exceeds that allowed by the FDA (Table 7). In non-medicated feeds, the situation is more worrisome, since concentrations have been found that exceed the recommended values, including phases of production in which its use is prohibited, as in the case of feed for laying hens with 191.69 mg kg− 1 of monensin or dairy cattle with 3258.86 mg kg− 1 (Table 7, FDA, 2011). Monensin and narasin presence can be explained as, widespread since ionophore-based growth promotion is still allowed (Granados-Chinchilla and Rodríguez 2017) and they are commonly used to fight causative agents of coccidiosis in aviculture (specifically for broilers, and laying hens before starting the production period) in concentrations of 90–110 and 54–72 mg kg− 1 respectively (Table 7, FDA 2011; Kant et al. 2013). We also found tetracyclines in almost all sample types assayed (6.21 to 354.46 mg kg− 1, Table 7) including demeclocycline and doxycycline (antibiotics reserved for specific cases in human therapy, Granados-Chinchilla and Rodríguez 2017) and 4-epioxytetracycline (which may indicate feed has reached its shelf life, Granados-Chinchilla et al. 2012). Tetracyclines can be used in most production animals, have a prophylactic effect against C. perfringens and Escherichia coli, it is also used to control infections caused by Mycoplasma, in concentrations of 200–400 mg kg− 1 in aviculture with minimum withdrawal period of 24 h before the slaughterhouse (FDA 2011; Rojek-Podgórska 2016; Mehdi et al. 2018).
Residues found in batch-to-batch cleaning or flushing samples
During feed production, shift between mediated and non-medicated batches, a two-step flushing is among the practices recommended (using a cheap excipient material; e.g., cornmeal, calcium carbonate) to reduce antimicrobial traces (FDA 2013; Rojek-Podgórska 2016; Martínez et al. 2018). During batch-to-batch cleanup, a reduction in the concentration of antibiotics can be observed in line with the cleaning cycles (Table 8). From the samples tested, four sets of data were collected regarding flushing (monensin in all four cases, and florfenicol, erythromycin and narasin in only one of the cases). In three of the four cases of monensin, the initial quantity of coccidiostat was reduced to undetectable limits. For example, in the first case a calcium salt was used as a vehicle for flushing the monensin salt, and the original concentration of monensin (907.40 mg kg− 1) was reduced to 2.07%. In the second case, three cleaning cycles were used, two with finished feed and a final cycle with ground corn, here the initial concentration reported (741.45 mg kg− 1), was reduced to 22.02% in the second cycle and reached undetectable levels in the third cycle. In the third case, another type of feed was used as a vehicle for flushing, with negative results, where the initial amount went from 26.82 mg kg− 1 to 20.11 mg kg− 1. In the last case, in which corn meal was used in the first cycle and feed for the next two, it was possible to reduce the initial concentration (13.82 mg kg− 1) to 1.88% (Table 8). Florfenicol reduction using the same strategy reduced 85.50% of the antibiotic. A second clean up cycle did not prove to be effective in reducing further the active ingredient. Florfenicol flushing seems to be challenging, probably due to interactions with the mixer, and cleaning batch vehicle as is a charged and halogenated molecule. Florfenicol residues do not comply even if the currently discussed thresholds expected after flushing are considered (i.e., maximum 3% carry-over) (Rojek-Podgórska 2016). Finally, erythromycin and narasin were reduced from the first cleaning cycle with corn meal (Table 8). Incongruences on residues found in feed labeled as medicated may result from poor homogenization or use of low-quality feed antibiotics (Granados-Chinchilla and Rodríguez 2017). Adequate mixing is a critical step during feed milling, especially for micro-ingredients. Mixer overfilling and deposits from the mixer, as well as, the sequence of ingredient addition and mixing time may influence the product (Stark and Jones 2009; Rocha et al. 2015; Huss et al. 2018; Martínez et al. 2018). Additionally, the antibiotic residue found in feed labeled as non-medicated can be attributed to errors in labeling or batch to batch cross-contamination (Stolker et al. 2013; Seró et al. 2015; Filippitzi et al. 2016). Contamination can also occur within the production flow (Martínez et al. 2018) or during the simultaneous transport and storage of medicated and non-medicated feed (Stark and Jones 2009). Antimicrobial under or overdosing can be equally damning as can generate adverse health effects and favors microbial resistance (Rojek-Podgórska 2016; Martínez et al. 2018).
During this survey, we found a worrisome prevalence of fumonisins in animal feed. Also, simultaneous contamination of feed with fumonisin fractions (e.g., B1, and B2) was quite frequent. Synergistic effect between toxins must be considered, especially as the co-occurrence of fumonisin with other Fusarium sp. toxins is a real possibility. In the case of antibiotics, we still encountered several practices that contravene antimicrobial stewardship policies. We found feed tabulated as non-medicated with considerable concentrations of antibiotics, even if certain antimicrobials (or their mixtures) are outlawed in feeds, we also found feed samples with a wrong antimicrobial dosage or incorrect compound. Methods used in this work for the analysis of mycotoxins and antibiotics in animal feeds, are versatile and can still be improved and extended to the identification of more analytes of relevance in the livestock industry. Mycotoxins epidemiological data, diagnostic ability and capability, and knowledge of the behavior of mycotoxins is among the first steps to reduce mycotoxins for compound feed manufacturing. Good manufacturing practices are the base to guarantee feed safety, therefore, the design and implementation of the procedures that help avoid deviations on the concentration of the declared veterinary antibiotic on the label, and prevent production and animal and human health issues. Current legislation does not seek to prohibit the use of antibiotics in livestock production, its primary objective is the prudent use of antibiotics and to strengthen biosecurity practices within the animal production unit. Constant programs for monitoring contaminants, both from the natural and anthropogenic origin, found in feed, must continue to be encouraged. Finally, it is unclear what consequence the presence of additional xenobiotic or additives have over other contaminants and residues such as mycotoxins and antibiotics or if further detrimental health effects are to be expected from samples with both types of substances.
Association of American Feed Control Officials
European Food Safety Authority
Food and Agriculture Organization of the United Nations
Food and drug administration
Solid phase extraction
United States of America
World Health Organization
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