Microbial Virulence Factors, Antimicrobial Resistance Genes, Metabolites, and Synthetic Chemicals in Cabins of Commercial Aircraft.
Xi FuMei ZhangYiwen YuanYang ChenZheyuan OuZailina HashimJamal Hisham HashimXin ZhangZhuohui ZhaoDan NorbackYu SunPublished in: Metabolites (2023)
Passengers are at a higher risk of respiratory infections and chronic diseases due to microbial exposure in airline cabins. However, the presence of virulence factors (VFs), antimicrobial resistance genes (ARGs), metabolites, and chemicals are yet to be studied. To address this gap, we collected dust samples from the cabins of two airlines, one with textile seats (TSC) and one with leather seats (LSC), and analyzed the exposure using shotgun metagenomics and LC/MS. Results showed that the abundances of 17 VFs and 11 risk chemicals were significantly higher in TSC than LSC ( p < 0.01). The predominant VFs in TSC were related to adherence, biofilm formation, and immune modulation, mainly derived from facultative pathogens such as Haemophilus parainfluenzae and Streptococcus pneumoniae . The predominant risk chemicals in TSC included pesticides/herbicides (carbofuran, bromacil, and propazine) and detergents (triethanolamine, diethanolamine, and diethyl phthalate). The abundances of these VFs and detergents followed the trend of TSC > LSC > school classrooms ( p < 0.01), potentially explaining the higher incidence of infectious and chronic inflammatory diseases in aircraft. The level of ARGs in aircraft was similar to that in school environments. This is the first multi-omic survey in commercial aircraft, highlighting that surface material choice is a potential intervention strategy for improving passenger health.
Keyphrases
- antimicrobial resistance
- biofilm formation
- mental health
- pseudomonas aeruginosa
- staphylococcus aureus
- microbial community
- physical activity
- genome wide
- randomized controlled trial
- healthcare
- antibiotic resistance genes
- public health
- candida albicans
- oxidative stress
- risk factors
- gene expression
- type diabetes
- dna methylation
- skeletal muscle
- cross sectional
- cystic fibrosis
- genome wide identification
- metabolic syndrome
- climate change
- polycyclic aromatic hydrocarbons
- health information
- bioinformatics analysis
- genome wide analysis
- drug induced
- health risk