Abstract

The misuse of antibiotics in the cattle sector can lead to milk contamination, with concomitant effects on the dairy industry and human health. Biosensors can be applied in this field; however, the influence of the milk matrix on their activity has been poorly studied in light of the preanalytical process. Herein, aptamer-conjugated gold nanoparticles (nanoaptasensors) were investigated for the colorimetric detection in raw milk of four antibiotics used in cattle. The effect of milk components on the colorimetric response of the nanoaptasensors was analyzed by following the selective aggregation of the nanoparticles, using the absorption ratio A520/A720. A preanalytical strategy was developed to apply the nanoaptasensors to antibiotic-contaminated raw milk samples, which involves a clarification step with Carrez reagents followed by the removal of cations through dilution, chelation (EDTA) or precipitation (NaHCO3). The colorimetric signals were detected in spiked samples at concentrations of antibiotics as low as 0.25-fold the maximum residue limits (MRLs) for kanamycin (37.5 μg/L), oxytetracycline (25 μg/L), sulfadimethoxine (6.25 μg/L) and ampicillin (1 μg/L), according to European and Chilean legislation. Overall, we conclude that this methodology holds potential for the semiquantitative analysis of antibiotic residues in raw milk obtained directly from dairy farms.

Highlights

  • Bovine milk is one of the most important nutrient-rich food sources in the human diet [1], the global production of which reached 540,925 million tons in July 2021 [2].The quality and safety of milk and dairy products are of paramount importance for the food industry and public health [3]

  • The NAS developed are based on previously reported aptamers specific to four antibiotics used in cattle

  • Numerous works in the nanobiosensor field are based on aptamers bound to the nanoparticles through electrostatic interactions, which is a suitable approach for the detection of antibiotics in a saline buffer solution or highly clarified matrices

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Summary

Introduction

Bovine milk is one of the most important nutrient-rich food sources in the human diet [1], the global production of which reached 540,925 million tons in July 2021 [2]. The quality and safety of milk and dairy products are of paramount importance for the food industry and public health [3]. Bacterial multidrug resistance to antibiotics is today among the biggest threats to global health, accounting for over 700,000 deaths each year due to infections caused by antibiotic-resistant bacteria (ARB) [7]. ARB are expected to cause 10 million deaths per year by 2050 at an economic cost of USD 100 trillion [8]. Antibiotic-contaminated raw milk may interfere with fermentation processes of dairy products by inhibiting the growth of lactic acid bacteria (starter cultures) [9]

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