Drilling into the physiology, transcriptomics, and metabolomics to enhance insight on Vallisneria denseserrulata responses to nanoplastics and metalloid co-stress

代谢组学 代谢组 水生植物 转录组 叶绿素 生物 生物信息学 植物 生态学 生物化学 基因表达 基因
作者
Na Tang,Wenmin Huang,Xiaowei Li,Xueyuan Gao,Xiaoning Liu,Lei Wang,Wei Xing
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:448: 141653-141653 被引量:24
标识
DOI:10.1016/j.jclepro.2024.141653
摘要

Co-contamination of nanoplastics (NPs) and arsenic (As) in aquatic environments poses a serious threat to the growth of aquatic plants, but the molecular toxicity mechanism leading to this joint effect on submerged macrophytes is still unclear. Here, we investigated the physiological, transcriptomic, metabolomic responses, and organelle changes in submerged macrophyte, Vallisneria denseserrulata (V. denseserrulata), to single/combined exposure to NPs and As. Our results showed that co-exposure alters physiological traits in V. denseserrulata including chlorophyll, sugars, proteins, malondialdehyde, and antioxidant enzymes. The presence of NPs exacerbated As distribution 36.2–47.2% higher than the control in plant tissues, thus enhancing combined pollution to plants. Integration of physiological traits and differentially expressed genes via weighted correlation network analysis implicated stress-responsive candidate modules related to key enzymes, such as ribulose-bisphosphate carboxylase, alanine transaminase, aspartate aminotransferase, phosphofructokinase-1, and phenylalanine ammonia-lyase. Metabolomics profiling identified carbohydrates, amino acids, organic acids, and fatty acids. Conjoint transcriptome and metabolome analysis revealed that photosynthetic systems, energy conversion, and oxidative and antioxidant regulation are the key defensive response mechanisms for V. denseserrulata under NPs-As co-exposure. Taken together, our multi-omics study provided new molecular insights into submerged macrophytes tolerance mechanisms against combined NPs and As toxicity, highlighting potential targets for stress mitigation and biomonitoring in contaminated aquatic ecosystems.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
羊羊羊发布了新的文献求助10
刚刚
Hello应助一二三采纳,获得10
刚刚
dove发布了新的文献求助30
刚刚
1秒前
2秒前
2秒前
3秒前
科研通AI6.2应助Archie采纳,获得10
3秒前
4秒前
大模型应助晨chen采纳,获得20
4秒前
cyu完成签到 ,获得积分10
4秒前
Fr9nk完成签到,获得积分10
5秒前
淡淡的人达应助plh采纳,获得20
5秒前
恒弟弟完成签到,获得积分20
5秒前
江屿发布了新的文献求助10
5秒前
6秒前
庸人自扰发布了新的文献求助10
6秒前
6秒前
爱笑的听云完成签到,获得积分10
6秒前
6秒前
123发布了新的文献求助10
6秒前
樂意发布了新的文献求助10
7秒前
7秒前
拉拉完成签到,获得积分10
7秒前
故渊丶发布了新的文献求助10
8秒前
夏目完成签到 ,获得积分10
9秒前
热心起眸发布了新的文献求助10
9秒前
9秒前
欢喜夏寒发布了新的文献求助10
9秒前
周鑫鑫周发布了新的文献求助10
9秒前
10秒前
10秒前
11秒前
温柔的芸发布了新的文献求助10
11秒前
情怀应助最强兰博探险家采纳,获得10
11秒前
老实惜海发布了新的文献求助10
11秒前
一二三发布了新的文献求助10
12秒前
12秒前
科研通AI6.4应助樂意采纳,获得10
13秒前
Lin发布了新的文献求助10
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Great Hymn to Šamaš 500
Positive Obsession: The Life and Times of Octavia E. Butler 500
Interpolation and Regression Models for the Chemical Engineer: Solving Numerical Problems 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7693141
求助须知:如何正确求助?哪些是违规求助? 9254064
关于积分的说明 19987200
捐赠科研通 7266306
什么是DOI,文献DOI怎么找? 3291489
关于科研通互助平台的介绍 2447564
邀请新用户注册赠送积分活动 2296919