DNA metabarcoding and its potential in microbial risk assessment in waste sorting plants

TL;DR

This study uses DNA metabarcoding to assess microbial risks in waste sorting plants, identifying potential human pathogens in the air.

Contribution

The study demonstrates the use of DNA metabarcoding for microbial risk assessment in waste sorting environments.

Findings

Microbial community composition varied significantly within and between waste sorting plants.

Potential human pathogens like Aspergillus sp., Fusarium sp., and Enterobacteriaceae were identified in air samples.

Seasonality did not affect microbial community composition in waste sorting plants.

Abstract

Exposure to hazardous microorganisms during waste handling is a potential health concern. Molecular biological techniques provide means of profiling the microbial community at high taxonomic resolution, allow the identification of critical human pathogens on the species level and thereby aid the risk assessment of work tasks. The present study used high-throughput sequencing to characterise the microbiome in personal full-shift air samples collected at contemporary waste sorting plants (WSPs) and identified large variations in community composition within (alpha diversity) and between (beta diversity) WSPs. Seasonality did not contribute to differences in the community composition. Cladosporium sp. was dominant among fungi, whereas Aerococcus sp. was dominant among bacteria. The personal air-samples contained potential human pathogens, such as Aspergillus sp., Fusarium sp. and Enterobacteriaceae, that encompass strains with the potential to develop drug-resistance. This study provided characterization of the microbial community composition of personal bioaerosol samples and provided evidence for the occurrence of potential human pathogens in contemporary waste sorting plants. Furthermore, this study highlighted the potential of microbial metabarcoding to detect critical human pathogens that may be encountered in working environments.

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