Abstract

Antibiotic resistance genes (ARGs) have emerged as a global health concern. A large volume of work has already been devoted to ARGs in aquatic ecosystems. However, ARG dispersal patterns in air remain to be largely unknown despite of its greater role in transmission. This work aims to investigate time-resolved airborne spread of ARGs and their corresponding subtype bacterial carriers in highly polluted air. Time-resolved air samples (20 m3 each with three samples) were collected using a high volume sampler (1 m3/min) every 4 h continuously (both day and night) during low (14–93 μg/m3) and high PM2.5 (36–205 μg/m3) pollution times (over 6 days with a total of 69 air samples) in Beijing. All air samples were subjected to 16S rRNA sequence analysis for 39 ARG subtypes. Pure culturable bacterial isolates from Beijing and Shijiazhuang were Sanger sequenced for species identification and also subjected to high throughput ARG subtype detection. ARG and its subtype relative abundances in the air were observed to differ greatly (up to 3 folds for abundance) both day and night, and the blaTEM gene was found to lead the ARG abundance. For an early morning time, the multi-drug resistant NDM-1 gene was detected up to 30% of total ARG abundance in highly polluted air. Identified as a major NDM-1 and vanB gene carrier, Bacillus halotolerans were also shown to disseminate more ARG subtypes. On another front, tnpA and intI1 were shown to vary greatly in abundance, while the sul3 gene was found widespread among the culturable Bacillus isolates in the air. Principal component analysis (PCA) showed different gene co-occurrence networks for different PM2.5 pollution episodes, e.g., tnpA and intI1 for gene transfer and integration, respectively, were found more abundant for the high PM2.5 pollution episode. This study highlights a serious yet previously unidentified public health threat from time-resolved airborne spread of ARGs. Further work is urgently warranted to track the sources of ARGs for their optimized control during high PM2.5 pollution episodes.

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