Characterizing sediment functional traits and ecological consequences respond to increasing antibiotic pollution.
Jiaqi LuHaonan ShaJiong ChenXianghua YiJinbo XiongPublished in: Applied microbiology and biotechnology (2023)
Current studies have shown that the taxonomic structures of ecologically important microbial communities are altered by antibiotic exposure, but the resulting effects on functional potentials and subsequent biogeochemical processes are poorly understood. However, this knowledge is indispensable for developing an accurate projection of nutrient dynamics in the future. Using metagenomic analyses, here we explored the responses of taxonomical and functional structures of a sediment microbial community, and their links with key biogeochemical processes to increasing antibiotic pollution from the pristine inlet to the outfall sites along an aquaculture discharge channel. We identified sharply contrasting sedimentary microbial communities and functional traits along increasing antibiotic pollution. Functional structures exhibited steeper distance-decay relationships than taxonomical structures along both the antibiotic distance and physicochemical distance, revealing higher functional sensitivity. Sediment enzyme activities were significantly and positively coupled with the relative abundances of their coding genes, thus the abundances of genes were indicative of functional potentials. The nitrogen cycling pathways were commonly inhibited by antibiotics, but not for the first step of nitrification, which could synergistically mitigate nitrous oxide emission. However, antibiotic pollution stimulated methanogens and inhibited methanotrophs, thereby promoting methane efflux. Furthermore, microbes could adapt to antibiotic pollution through enriched potential of sulfate uptake. Antibiotics indirectly affected taxonomic structures through alterations in network topological features, which in turn affected sediment functional structures and biogeochemical processes. Notably, only 13 antibiotics concentration-discriminatory genes contributed an overall 95.9% accuracy in diagnosing in situ antibiotic concentrations, in which just two indicators were antibiotic resistance genes. Our study comprehensively integrates sediment compositional and functional traits, biotic interactions, and enzymatic activities, thus generating a better understanding about ecological consequences of increasing antibiotics pollution. KEY POINTS: • Contrasting functional traits respond to increasing antibiotic pollution. • Antibiotics pollution stimulates CH 4 efflux, while mitigating N 2 O emission and may drive an adaptive response of enriched sulfate uptake. • Indicator genes contribute 95.9% accuracy in diagnosing antibiotic concentrations.
Keyphrases
- heavy metals
- human health
- risk assessment
- microbial community
- health risk assessment
- particulate matter
- genome wide
- antibiotic resistance genes
- high resolution
- healthcare
- magnetic resonance imaging
- gene expression
- climate change
- dna methylation
- mass spectrometry
- magnetic resonance
- polycyclic aromatic hydrocarbons
- computed tomography
- transcription factor
- quantum dots
- water quality