Detection Of Antibiotics In Milk Research Articles

Self-assembled sensing interface based on specific aptamer functionalized Ti3C2 MXene for ultrasensitive antibiotic detection in milk

A self-assembled sensing interface based on Ti3C2 MXene functionalized by aptamer had been successfully constructed in this work, which fully utilizes the electrical properties of Ti3C2 MXene and the specific recognition ability of the aptamer. Subsequently, we studied the performance of the sensing interface using two antibiotic residues as examples. Under the optimal conditions, the sensing interface showed a linear range of 100 fM–1 μM and a limit of detection of 1 fM to detect kanamycin and tetracycline, furthermore the recovery rates were 97.15%–103.00% and 99.559%–106.36%, respectively. In addition, the sensing behaviors of aptamers specific recognition of target can be perceived by the interface, thereby exhibiting different electrical responses. Therefore, the self-assembled sensing interface not only provided a new avenue for the development of ultrasensitive technology in the food analysis field but also for investigating aptamer configurational transformations.

Machine-learning-driven optical immunosensor based on microspheres-encoded signal transduction for the rapid and multiplexed detection of antibiotics in milk

Antibiotic residues are the most common contaminants in milk and other related dairy products. Simultaneous, convenient, and stable detection of antibiotic residues in foods is vital to secure public health. Herein, we proposed an optical immunosensor with easily-functionalized polystyrene nanoparticles differing in size and quantity, and bearing multiplex signal probes for the simultaneous detection of multiple antibiotics through a simple one-step signal conversion reaction. After the integration of the machine-learning-based transcoding analysis, this sensor is suitable for multiplexed detection of antibiotics in a broad linear range from pg/mL to ng/mL within 30 min, with an overall accuracy of >99 %. Compared to the conventional standard chemiluminescence immunoassays, this immunosensor is suitable for the accurate quantification of multiple antibiotics in milk, with improved accuracy, reduced costs, and simplified procedure. This ensures its applications in food safety monitoring when simultaneous detection of multiple hazardous substances in food matrices is needed.

Screening of broad-spectrum aptamers to construct an electrochemical aptasensor for the sensitive detection of tetracycline antibiotic residues in milk

Broad-spectrum aptamer has been shown to be an important probe for antibiotic multi-residue detection. In this study, we successfully screened a broad-spectrum aptamer (Apt-T1) that can recognize TCs with the same core structure using the graphene oxide (GO)-SELEX. Then Apt-T1 was truncated by molecular docking simulation to obtain an aptamer (Apt-T1–2) with higher specificity and affinity with a dissociation constant of 4.27–7.20 nM. On this basis, an electrochemical aptasensor based on Apt-T1–2 was constructed to achieve sensitive detection of TCs. Fe/ Zn-doped montmorillonite was synthesized by cation exchange technique for amplifying sensor signal. Under optimized conditions, the aptasensor showed a limit of detection of 0.46 nM and a linear range of 1–10,000 nM with a correlation coefficient (R2) of 0.989. Finally, the effects of the main components (fat, protein, Na+ and Ca2+) in milk on the electrochemical signal were investigated, and it was clear that fat and protein had a negative effect and so they were removed. The method was used to the determination of TCs in milk with recoveries of 98.26%− 104.15%, which revealed its potential application for sensitive analysis in food safety control and also provided a new method for multi-residue detection of antibiotics in milk.

Electrochemical Biosensors for the Detection of Antibiotics in Milk: Recent Trends and Future Perspectives.

Antibiotics have emerged as ground-breaking medications for the treatment of infectious diseases, but due to the excessive use of antibiotics, some drugs have developed resistance to microorganisms. Because of their structural complexity, most antibiotics are excreted unchanged, polluting the water, soil, and natural resources. Additionally, food items are being polluted through the widespread use of antibiotics in animal feed. The normal concentrations of antibiotics in environmental samples typically vary from ng to g/L. Antibiotic residues in excess of these values can pose major risks the development of illnesses and infections/diseases. According to estimates, 300 million people will die prematurely in the next three decades (by 2050), and the WHO has proclaimed "antibiotic resistance" to be a severe economic and sociological hazard to public health. Several antibiotics have been recognised as possible environmental pollutants (EMA) and their detection in various matrices such as food, milk, and environmental samples is being investigated. Currently, chromatographic techniques coupled with different detectors (e.g., HPLC, LC-MS) are typically used for antibiotic analysis. Other screening methods include optical methods, ELISA, electrophoresis, biosensors, etc. To minimise the problems associated with antibiotics (i.e., the development of AMR) and the currently available analytical methods, electrochemical platforms have been investigated, and can provide a cost-effective, rapid and portable alternative. Despite the significant progress in this field, further developments are necessary to advance electrochemical sensors, e.g., through the use of multi-functional nanomaterials and advanced (bio)materials to ensure efficient detection, sensitivity, portability, and reliability. This review summarises the use of electrochemical biosensors for the detection of antibiotics in milk/milk products and presents a brief introduction to antibiotics and AMR followed by developments in the field of electrochemical biosensors based on (i) immunosensor, (ii) aptamer (iii) MIP, (iv) enzyme, (v) whole-cell and (vi) direct electrochemical approaches. The role of nanomaterials and sensor fabrication is discussed wherever necessary. Finally, the review discusses the challenges encountered and future perspectives. This review can serve as an insightful source of information, enhancing the awareness of the role of electrochemical biosensors in providing information for the preservation of the health of the public, of animals, and of our environment, globally.

Lock-in Amplifier Dairy Sensor for Detection of Ciprofloxacin

This work introduces a sensor for dairy antibiotic detection of ciprofloxacin in milk. We provide an important tool for antibiotic detection in milk and the main contributions of this work are as follows. We introduce a technique based on florescence spectroscopy and lock-in amplification for sensing ciprofloxacin in milk that is capable of detection below the regulatory limit. We compare the system against one without the integrated lock-in amplification, as in traditional fluorescence sensors. We provide microchip capillary electrophoresis results and place our work in context for future integration with microchip capillary electrophoresis.

Novel Electrochemical Aptasensor Based on Floral Zinc Oxide/Reduced Graphene Oxide/Colloidal Gold Composite for the Detection of Tetracycline, Doxycycline and Oxytetracycline in Milk

In this research, an electrochemical aptamer sensor based on the specific recognition of tetracycline, doxycycline and oxytetracycline was developed through flower-like zinc oxide/reduced graphene oxide/nano-gold composites. Firstly, floral zinc oxide had a large contact area, which bound more gold nanoparticles, and bound more adapters through Au–S bonds. Next, due to the poor conductivity of floral zinc oxide, the combination of floral zinc oxide and rGO was able to improve the conductivity. Finally, the rGO–ZnO–AuNPs composite was used as a platform to improve the electron transport rate on the glassy carbon electrode surface, enhance the electrochemical strength, and provide enough active sites for the capture of aptamers. After condition optimization, the lowest detection concentrations for tetracycline, doxycycline and oxytetracycline were 0.33, 0.28 and 0.3 ng·ml−1 respectively. In addition, this aptasensor had good stability, selectivity, anti-interference and reproducibility. It would be further applied to the detection of antibiotics in milk.

An ultrasensitive NIR-IIa’ fluorescence-based multiplex immunochromatographic strip test platform for antibiotic residues detection in milk samples

IntroductionWidely used in livestock breeding, residues of antibiotic drugs in milk have become a threat to food safety and human health. Current rapid detection technologies using colorimetric immunochromatographic strip tests (IST) lack the necessary sensitivity for on-site trace monitoring. Fluorescence-based detection in the near-infrared IIa’ (NIR-IIa’) region (1000 ∼ 1300 nm) has enormous potential due to greatly minimized auto-fluorescence and light scattering. ObjectivesThe aim of this work is to develop an ultrasensitive IST platform using NIR-IIa’ fluorescent nanoparticles as labels for multiplex antibiotic residues detection in milk. MethodsNIR-IIa’ fluorescent nanoparticles were assembled by encapsulating synthesized NIR-IIa’ fluorophores into carboxyl - modified polystyrene nanoparticles. The NIR-IIa’ nanoparticles were subsequently used as labels in an IST platform to detect sulfonamides, quinolones, and lincomycin simultaneously in milk. A portable fluorescent reader was fabricated to provide on-site detection. To further validate the developed IST platform, the detection was compared with LC-MS/MS in 22 real milk samples. ResultsFluorescent nanoparticles were synthesized with low energy emission (1030 nm) and large Stokes shift (>250 nm) showing a much higher signal-to-noise ratio compared with fluorophores emitting in the NIR-I region. The developed IST platform yielded a highly sensitive, simultaneous quantification of sulfonamides, quinolones, and lincomycin in milk with detection limits of 46.7, 27.6 and 51.4 pg/mL, respectively, achieving a wide detection range (up to 50 ng/mL). The IST platform showed good accuracy, reproducibility, and specificity with the portable fluorescent reader which could rapidly quantify in 10 s. These results were better than reported immunochromatographic assays using fluorescent labels, and remarkably, showed a higher recognition ability than LC-MS/MS for real samples. ConclusionThe utility of NIR-IIa’ fluorescence-based IST platform for the fast, sensitive, and accurate detection of antibiotics in milk was demonstrated, successfully verifying the potential of this platform in detecting trace materials in complex matrices.

ISOLATION, IDENTIFICATION AND USE OF STRAINS OF BACTERIA OF THE GENUS BACILLUS IN A MICROBIOLOGICAL TEST FOR THE DETERMINATION OF ANTIBIOTICS IN MILK

The use of antibiotics in the treatment of livestock has increased the productivity of the meat and dairy industry. The flip side of the effectiveness of drugs of this group is the presence of side effects, which have caused concern about the widespread use of antibiotics and cause the need to control the residual content of antibacterial agents in dairy products. From soil samples collected in 7 regions of Kazakhstan, 14 microbial isolates were isolated and identified as B. licheniformis, B. sonorensis, B. cereus, B. simplex, B. thuringiensis, B. pumilis, B. mojavensis, B. subtilis, B. atrophaeus, B. paralicheniformis. Sensitivity testing of the isolated strains showed that the strains were susceptible to 13 antibiotics belonging to lincosamide, ansamycin, quinolone, macrolide, fluoroquinolone, tetracycline, nitrobenzene, aminoglycoside, glycopeptide and beta-lactam antibiotics. The proteolytic strain Bacillus licheniformis T7 seems promising as a test culture. It is highly sensitive to antibiotics, grows rapidly on a variety of nutrient media, is alkaline and spore-forming and can be cultured at 37-55°C. The peculiarity of the strain to change the pH of the medium from 5.0 to 7.0 and above makes it possible to use bromcresol purple as a growth-detecting dye. This has been shown in experiments using antibiotic milk samples on LB agar and LB broth pH 5.0. In the absence of growth-inhibiting antibiotics, the culture of B. licheniformis T7 grows vigorously, which causes a pH shift to 7.99 and causes the color of bromocresol purple to change from yellow to purple. The results showed promise for the strain Bacillus licheniformis T7 to be used as a bacterial culture in the development of a microbiological test for the detection of antibiotics in milk.

Machine Learning-Driven 3D Plasmonic Cavity-in-Cavity Surface-Enhanced Raman Scattering Platform with Triple Synergistic Enhancement Toward Label-Free Detection of Antibiotics in Milk.

The surface-enhanced Raman scattering (SERS) technique with ultrahigh sensitivity has gained attention to meet the increasing demands for food safety analysis. The integration of machine learning and SERS facilitates the practical applicability of sensing devices. In this study, a machine learning-driven 3D plasmonic cavity-in-cavity (CIC) SERS platform is proposed for sensitive and quantitative detection of antibiotics. The platform is prepared by transferring truncated concave nanocubes (NCs) to an obconical-shaped template surface. Owing to the triple synergistic enhancement effect, the highly ordered 3D CIC arrays improve the simulated electromagnetic field intensity and experimental SERS activity, demonstrating a 33.1-fold enhancement compared to a typical system consisting of Au NCs deposited on a flat substrate. The integration of machine learning and Raman spectroscopy eliminates subjective judgments on the concentration of detectors using a single feature peak and achieves accurate identification. The machine learning-driven CIC SERS platform is capable of detecting ampicillin traces in milk with a detection limit of 0.1ppm, facilitating quantitative analysis of different concentrations of ampicillin. Therefore, the proposed platform has potential applications in food safety monitoring, health care, and environmental sampling.

A Short Review on Detection of Antibiotics in Milk Using Nanomaterial-Based Biosensor

A Short Review on Detection of Antibiotics in Milk Using Nanomaterial-Based Biosensor

A Novel Method for Antibiotic Detection in Milk Based on Competitive Magnetic Immunodetection

The misuse of antibiotics as well as incorrect dosage or insufficient time for detoxification can result in the presence of pharmacologically active molecules in fresh milk. Hence, in many countries, commercially available milk has to be tested with immunological, chromatographic or microbiological analytical methods to avoid consumption of antibiotic residues. Here a novel, sensitive and portable assay setup for the detection and quantification of penicillin and kanamycin in whole fat milk (WFM) based on competitive magnetic immunodetection (cMID) is described and assay accuracy determined. For this, penicillin G and kanamycin-conjugates were generated and coated onto a matrix of immunofiltration columns (IFC). Biotinylated penicillin G or kanamycin-specific antibodies were pre-incubated with antibiotics-containing samples and subsequently applied onto IFC to determine the concentration of antibiotics through the competition of antibody-binding to the antibiotic-conjugate molecules. Bound antibodies were labeled with streptavidin-coated magnetic particles and quantified using frequency magnetic mixing technology. Based on calibration measurements in WFM with detection limits of 1.33 ng·mL−1 for penicillin G and 1.0 ng·mL−1 for kanamycin, spiked WFM samples were analyzed, revealing highly accurate recovery rates and assay precision. Our results demonstrate the suitability of cMID-based competition assay for reliable and easy on-site testing of milk.

Functional Up-Conversion Nanoparticle-Based Immunochromatography Assay for Simultaneous and Sensitive Detection of Residues of Four Tetracycline Antibiotics in Milk.

An ultrahigh-sensitivity lateral flow immunochromatography (LFIC) assay based on up-converting nanoparticles (UCNPs) was developed to carry out a multi-residue detection of tetracycline in milk. The sensitivity of the immunoassay was greatly improved by the use of a broad-spectrum monoclonal antibody attached to UCNPs to form a signal probe. Under the optimal conditions, the UCNP-LFIC assay enabled sensitive detection of tetracycline (TC) as well as of oxytetracycline (OTC), chlortetracycline (CTC), and doxycycline (DOX) within 10 min, with IC50 values of 0.32, 0.32, 0.26, 0.22 ng/mL, respectively. There was no cross-reactivity with ten other antibiotics. Similarly, we evaluated the experimental results for matrix effects. Experiments involving spiking showed the four tetracycline antibiotics displaying mean recoveries ranging from 93.95 to 111.90% with relative standard deviations (RSDs) of < 9.95%. The detection results of actual samples using the developed method showed a good correlation (R2 ≥ 0.98) with the results using high-performance liquid chromatography (HPLC). Thus, the assay can achieve an ultrahighly sensitive detection of antibiotics in milk, and can hence promote human health and provides promising applications in the bio-detection field.

Optimization of microbiological plastic film test plate conditions for rapid detection of antibiotics in milk

Food safety and quality are issues of great concern to food producers and consumers. Key challenges towards achieving these include availability of rapid, user-friendly, economic and reliable techniques to detect problems such as antibiotic residues. Therefore, the present study was conducted to evaluate performance of plastic film test plate (PFTP) as influenced by antibiotic type, test bacterium, inoculum volume and concentration. Comparison was made to the microtiter test plate (MTP) and the National Standard method (SN/T 3979-2014). For this, antibiotic susceptibility testing was conducted on four bacterial types (Micrococcus luteus, Streptococcus thermophillus suspensions, Staphylococcus aureus and Coliform bacteria) against three antibiotics (penicillin G, sulfadiazine and tetracycline). Results showed high susceptibility of Micrococcus luteus to penicillin G with minimum inhibitory concentration of 3 µg L−1 and 1 µg L−1 via PFTP and MTP respectively. Optimum performance was realized at bacterial concentration of 104 CFU ml−1 with detection limit of 1 µg L−1, sensitivity and predictive positive value (PPV) of 81–83% and 97–100% respectively. Detection time was recorded as 6 and 9 h for MTP and PFTP respectively compared to the 18–24 h of the National Standard method (SN/T 3979–2014). The microbiological plastic film test plate under optimized bacterial culture conditions demonstrated tremendous potential for rapid and reliable detection of antibiotics in milk.

Fabrication of penicillin G portable microbiological test plate for on-farm antibiotic residues in milk

Antibiotic residues in animal-derived food products such as milk pose a potential health risk to consumers. A portable antimicrobial screening test plate was fabricated particularly for on-farm testing of milk. A cold-water soluble compound gelling agent composed of guar gum (GG) and konjac glucomannan (KG) was prepared and its properties were optimized for enhancing performance of the test plate. A ratio of 4:6 (GG:KG) showed improved gel strength, cohesiveness, transmittance, and water diffusion of the compound gel. Microbial colony number and size were also increased. The test plate displayed a minimum inhibition concentration of 4 µg/L penicillin G and clearer zone of inhibition. Detection time was also significantly reduced to approximately 9–15 h compared to the conventional agar plate method. The plastic film test plate with optimized compound gel demonstrated tremendous potential for detection of antibiotics in milk.

Detection of Chlortetracycline Hydrochloride in Milk with a Solid SERS Substrate Based on Self-assembled Gold Nanobipyramids.

This paper described how a high-yield, monodisperse Au nanobipyramids (Au NBs) sol was prepared by a seed-mediated method, and gold nanoparticles were assembled on the surface of a silicon wafer by self-assembly technology to obtain a solid SERS substrate. Scanning electron microscopy (SEM) showed that the average length of Au NBs was 34.31 nm, and the analysis enhancement factor (AEF) was approximately 7.3 × 105 with rhodamine 6G (R6G) used as a probe. SERS detection of chlortetracycline hydrochloride (CCH) in milk was performed utilizing the prepared Au NBs substrate, and the limit of detection was 0.01 mg/mL. In the range of 0.01 - 1 mg/mL, the mass concentration of CCH and the SERS signal intensity satisfied the linear relationship y = 258.467x + 150.501; the value of the correlation coefficient was 0.9785. In addition, the recovery of spiked samples fluctuated between 96.80 to 111.38%. These results proved that the method is simple and fast, and it is promising to be applied to the field detection of antibiotics in milk.

A Smartphone-Based Whole-Cell Array Sensor for Detection of Antibiotics in Milk.

We present an integral smartphone-based whole-cell biosensor, LumiCellSense (LCS), which incorporates a 16-well biochip with an oxygen permeable coating, harboring bioluminescent Escherichia coli bioreporter cells, a macro lens, a lens barrel, a metal heater tray, and a temperature controller, enclosed in a light-impermeable case. The luminescence emitted by the bioreporter cells in response to the presence of the target chemicals is imaged by the phone’s camera, and a dedicated phone-embedded application, LCS_Logger, is employed to calculate photon emission intensity and plot it in real time on the device’s screen. An alert is automatically given when light intensity increases above the baseline, indicating the presence of the target. We demonstrate the efficacy of this system by the detection of residues of an antibiotic, ciprofloxacin (CIP), in whole milk, with a detection threshold of 7.2 ng/mL. This value is below the allowed maximum as defined by European Union regulations.

Development of a multicomponent immunochromatographic test system for the detection of fluoroquinolone and amphenicol antibiotics in dairy products

Ciprofloxacin (CIP) and chloramphenicol (CAP) are relevant antibiotics of the fluoroquinolone (FQ) and amphenicol (AP) groups, respectively, widely used in veterinary practice and they contaminate agricultural products. In this study, a rapid and sensitive immunochromatographic assay (ICA) was developed for simultaneous detection of CIP and CAP in dairy products. The ICA was carried out in a direct competitive format using gold nanoparticles as a label. The ICA developed here allowed for the detection of CIP and CAP in Triton X-100-containing buffered saline (PBST) within 15 min with instrumental detection limits of 20 pg mL-1 and 0.5ng mL-1 , respectively, and with a visual detection limit of 5ng mL-1 for both antibiotics. The ICA showed cross-reactivity (69-160%) to 19 antibiotics in the FQ group and no cross-reactivity (<0.1%) to 2 antibiotics of the AP group. The ICA allowed detection of CIP and CAP in a panel of dairy products by employing a simple procedure of preliminary sample preparation. The detection limits for the two antibiotics were the same as in PBST. The analytical recoveries of CIP and CAP in dairy products ranged from 83% to 120%. The analytical characteristics of the test system allow its use for the detection of antibiotics in milk and dairy products during all steps of production. © 2019 Society of Chemical Industry.

Выявление антибиотиков в молоке и казеиновой сыворотке с использованием экспресс-тестов

Выявление антибиотиков в молоке и казеиновой сыворотке с использованием экспресс-тестов

Silver nanoparticles inkjet-printed flexible biosensor for rapid label-free antibiotic detection in milk

Inkjet printing is an established technology that has been revisited in recent years for the low-cost and easy production of electrical sensing and biosensing systems. With this technique, it is possible to produce flexible microsystems on eco-compatible substrates such as polymers and paper. In this sense, we investigated the printing performances of a common office inkjet printer and of a commercial conducting ink, to produce aptamer-based electrochemical biosensors for antibiotics detection. During our analysis we characterized both the morphological and electrical properties of the printed electrodes, considering also their stability over time and tuning all the parameters to obtain reproducible micrometric systems.The produced devices proved to be able to undergo aptamer functionalization and to detect Ampicillin, a common used antibiotic, in few minutes with a LOD of 10 μg/ml in milk. Therefore, in this preliminary work we demonstrated the feasibility of low-cost customized inkjet-printed biosensors, and their possible use to prevent both antibiotic contaminations and antibiotic resistance development.

Utilization of a lateral flow colloidal gold immunoassay strip based on surface-enhanced Raman spectroscopy for ultrasensitive detection of antibiotics in milk

An ultrasensitive method for the detection of antibiotics in milk is developed based on inexpensive, simple, rapid and portable lateral flow immunoassay (LFI) strip, in combination with high sensitivity surface-enhanced Raman spectroscopy (SERS). In our strategy, an immunoprobe was prepared from colloidal gold (AuNPs) conjugated with both a monoclonal antibody against neomycin (NEO-mAb) and a Raman probe molecule 4-aminothiophenol (PATP). The competitive interaction with immunoprobe between free NEO and the coated antigen (NEO-OVA) resulted in the change of the amount of the immobilized immunoprobe on the paper substrate. The LFI procedure was completed within 15min. The Raman intensity of PATP on the test line of the LFI strip was measured for the quantitative determination of NEO. The IC50 and the limit of detection (LOD) of this assay are 0.04ng/mL and 0.216pg/mL of NEO, respectively. There is no cross-reactivity (CR) of the assay with other compounds, showing high specificity of the assay. The recoveries for milk samples with added NEO are in the range of 89.7%–105.6% with the relative standard deviations (RSD) of 2.4%–5.3% (n=3). The result reveals that this method possesses high specificity, sensitivity, reproducibility and stability, and can be used to detect a variety of antibiotic residues in milk samples.