For future targeted screening in National Residue Control Programmes, the metabolism of seven SARMs, from the arylpropionamide and the quinolinone classes, was studied in vitro using S9 bovine liver enzymes. Metabolites were detected and identified with ultra-performance liquid chromatography (UPLC) coupled to time-of-flight mass spectrometry (ToF-MS) and triple quadrupole mass spectrometry (QqQ-MS). Several metabolites were identified and results were compared with literature data on metabolism using a human cell line. Monohydroxylation, nitro-reduction, dephenylation and demethylation were the main S9 in vitro metabolic routes established. Next, an in vivo study was performed by oral administration of the arylpropionamide ostarine to a male calf and urine samples were analysed with UPLC-QToF-MS. Apart from two metabolites resulting from hydroxylation and dephenylation that were also observed in the in vitro study, the bovine in vivo metabolites of ostarine resulted in glucuronidation, sulfation and carboxylation, combined with either a hydroxylation or a dephenylation step. As the intact mother compounds of all SARMs tested are the main compounds present after in vitro incubations, and ostarine is still clearly present in the urine after the in vivo metabolism study in veal calves, the intact mother molecules were selected as the indicator to reveal treatment. The analytical UPLC-QqQ-MS/MS procedure was validated for three commercially available arylpropionamides according to European Union criteria (Commission Decision 2002/657/EC), and resulted in decision limits ranging from 0.025 to 0.05 µg l⁻¹ and a detection capability of 0.025 µg l⁻¹ in all cases. Adequate precision and intra-laboratory reproducibility (relative standard deviation below 20%) were obtained for all SARMs and the linearity was 0.999 for all compounds. This newly developed method is sensitive and robust, and therefore useful for confirmation and quantification of SARMs in bovine urine samples for residue control programmes and research purposes.

Current contaminant and residue monitoring throughout the food chain is based on sampling, transport, administration, and analysis in specialized control laboratories. This is a highly inefficient and costly process since typically more than 99% of the samples are found to be compliant. On-site simplified prescreening may provide a scenario in which only samples that are suspect are transported and further processed. Such a prescreening can be performed using a small attachment on a cellphone. To this end, a cellphone-based imaging platform for a microsphere fluorescence immunoassay that detects the presence of anti-recombinant bovine somatotropin (rbST) antibodies in milk extracts was developed. RbST administration to cows increases their milk production, but is illegal in the EU and a public health concern in the USA. The cellphone monitors the presence of anti-rbST antibodies (rbST biomarker), which are endogenously produced upon administration of rbST and excreted in milk. The rbST biomarker present in milk extracts was captured by rbST covalently coupled to paramagnetic microspheres and labeled by quantum dot (QD)-coupled detection antibodies. The emitted fluorescence light from these captured QDs was then imaged using the cellphone camera. Additionally, a dark-field image was taken in which all microspheres present were visible. The fluorescence and dark-field microimages were analyzed using a custom-developed Android application running on the same cellphone. With this setup, the microsphere fluorescence immunoassay and cellphone-based detection were successfully applied to milk sample extracts from rbST-treated and untreated cows. An 80% true-positive rate and 95% true-negative rate were achieved using this setup. Next, the cellphone-based detection platform was benchmarked against a newly developed planar imaging array alternative and found to be equally performing versus the much more sophisticated alternative. Using cellphone-based on-site analysis in future residue monitoring can limit the number of samples for laboratory analysis already at an early stage. Therewith, the entire monitoring process can become much more efficient and economical.

Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay procedure, the 48 microspots were labelled with Quantum Dots (QD) depending on the protein biomarker levels in the sample. QD-fluorescence was subsequently detected by the smartphone camera under UV light excitation from LEDs embedded in a simple 3D-printed opto-mechanical smartphone attachment. The somewhat aberrant images obtained under such conditions, were corrected by newly developed Android-based software on the same smartphone, and protein biomarker profiles were calculated. The indirect detection of recombinant bovine somatotropin (rbST) in milk extracts based on altered biomarker profile of anti-rbST antibodies was selected as a real-life challenge. RbST-treated and untreated cows clearly showed reproducible treatment-dependent biomarker profiles in milk, in excellent agreement with results from a flow cytometer reference method. In a pilot experiment, anti-rbST antibody detection was multiplexed with the detection of another rbST-dependent biomarker, insulin-like growth factor 1 (IGF-1). Milk extract IGF-1 levels were found to be increased after rbST treatment and correlated with the results obtained from the reference method. These data clearly demonstrate the potential of the portable protein microarray concept towards simultaneous detection of multiple biomarkers. We envisage broad application of this ‘protein microarray on a smartphone’-concept for on-site testing, e.g., in food safety, environment and health monitoring.

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