Citizen Science in Action: Harnessing Smartphone and Social Apps for Rapid On-Site Detection of Emerging Antibiotic Contaminants, Enrofloxacin and Ciprofloxacin as Paradigmatic Cases

Abstract

Citizen scientist-based environmental monitoring and public education are becoming increasingly popular. However, limited by detection methods and instrumentation, existing technologies for antibiotic-based new contaminant detection are still limited to sample collection and analysis done by laboratories. This study combines smartphone and social software with rapid detection to develop a field-based simultaneous detection method for enrofloxacin (ENR) and ciprofloxacin (CIP) that matches the results to geographic location and helps the public understand the potential level of antibiotic exposure in their environment and take appropriate measures to reduce risk. The method uses a portable, low-cost analytical kit with a smartphone app to build a field-based detection platform for the detection and analysis of ENR and CIP in water and fish. The methodological evaluation was good, with detection limits of 0.4 ng/ml and 0.5 ng/g for ENR in water and fish, and quantification limits of 1.2 ng/ml and 1.4 ng/g, with recoveries of 89.0%-101.0% and 78.0%-97.0%. For CIP in water and fish, the limits of detection were 0.3 ng/ml and 0.4 ng/ml, the limits of quantification were 0.9 ng/ml and 1.2 ng/ml, and the recoveries were 75.0%-91.0% and 72.0%-89.0%, both with coefficients of variation less than 15%, which were able to completely shield the two antibiotics from crossover during simultaneous detection. Validation of the assay on actual samples to determine the performance of the assay platform for field application showed results consistent with liquid chromatography-tandem mass spectrometry (LC-MS), enzyme-linked immunoassay (ELISA) methods, and with shorter time required for the assay process, more portable instrumentation required for the assay, and lower assay difficulty. This study provides a new scientific, accurate, and rapid detection method for antibiotic detection by citizen scientists, helping scientists to obtain a wider range of data and providing more opportunities to solve scientific problems.

Keywords: Citizen Science, Smart-phone, On-set detection, Antibiotics