Soil Microbiomes and their Arsenic Functional Genes in Chronically High-Arsenic Contaminated Soils.
Prinpida SonthiphandNattanan RueangmongkolratPichahpuk UthaipaisanwongKanthida KusonmanoWuttichai MhuantongTeerasit TermsaithongChanida LimthamprasertSrilert ChotpantaratEkawan LuepromchaiPublished in: Bulletin of environmental contamination and toxicology (2024)
Microbial arsenic transformations play essential roles in controlling pollution and ameliorating risk. This study combined high-throughput sequencing and PCR-based approaches targeting both the 16 S rRNA and arsenic functional genes to investigate the temporal and spatial dynamics of the soil microbiomes impacted by high arsenic contamination (9.13 to 911.88 mg/kg) and to investigate the diversity and abundance of arsenic functional genes in soils influenced by an arsenic gradient. The results showed that the soil microbiomes were relatively consistent and mainly composed of Actinobacteria (uncultured Gaiellales and an unknown_67 - 14 bacterium), Proteobacteria, Firmicutes (particularly, Bacillus), Chloroflexi, and Acidobacteria (unknown_Subgroup_6). Although a range of arsenic functional genes (e.g., arsM, arsC, arrA, and aioA) were identified by shotgun metagenomics, only the arsM gene was detected by the PCR-based method. The relative abundance of the arsM gene accounted for 0.20%-1.57% of the total microbial abundance. Combining all analyses, arsenic methylation mediated by the arsM gene was proposed to be a key process involved in the arsenic biogeochemical cycle and mitigation of arsenic toxicity. This study advances our knowledge about arsenic mechanisms over the long-term in highly contaminated soils.
Keyphrases
- heavy metals
- drinking water
- risk assessment
- health risk assessment
- genome wide
- health risk
- genome wide identification
- clinical trial
- randomized controlled trial
- healthcare
- transcription factor
- microbial community
- human health
- gene expression
- air pollution
- antibiotic resistance genes
- drug delivery
- oxidative stress
- study protocol
- open label
- bioinformatics analysis
- bacillus subtilis
- anaerobic digestion