인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
The accelerated decline in Arctic sea-ice cover and duration is enabling the opening of Arctic marine passages and improving access to natural resources. The increasing accessibility to navigation and resource exploration and production brings risks of accidental hydrocarbon releases into Arctic waters, posing a major threat to Arctic marine ecosystems where oil may persist for many years, especially in beach sediment. The composition and response of the microbial community to oil contamination on Arctic beaches remain poorly understood. To address this, we analyzed microbial community structure and identified hydrocarbon degradation genes among the Northwest Passage intertidal beach sediments and shoreline seawater from five high Arctic beaches. Our results from 16S/18S rRNA genes, long-read metagenomes, and metagenome-assembled genomes reveal the composition and metabolic capabilities of the hydrocarbon microbial degrader community, as well as tight cross-habitat and cross-kingdom interactions dominated by lineages that are common and often dominant in the polar coastal habitat, but distinct from petroleum hydrocarbon-contaminated sites. In the polar beach sediment habitats, <i>Granulosicoccus</i> sp. and <i>Cyclocasticus</i> sp. were major potential hydrocarbon-degraders, and our metagenomes revealed a small proportion of microalgae and algal viruses possessing key hydrocarbon biodegradative genes. This research demonstrates that Arctic beach sediment and marine microbial communities possess the ability for hydrocarbon natural attenuation. The findings provide new insights into the viral and microalgal communities possessing hydrocarbon degradation genes and might represent an important contribution to the removal of hydrocarbons under harsh environmental conditions in a pristine, cold, and oil-free environment that is threatened by oil spills.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.