Evidence map›Paper›PMID 40719957›Full record

ArticleWorld journal of microbiology & biotechnology2025

Interaction characteristics of bacterial communities in water and sediment in the Yellow River based on high-throughput absolute quantification.

Ming Chen, Wenxiu Bao, Wen Zhang, Minshi Wang, Qingqing Zhao, Yujie Huang, Yuan Lu

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Article in World journal of microbiology & biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Ming ChenShandong Provincial Key Laboratory of Applied Microbiology, Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), No. 28789 Jingshi East Road, Licheng District, Jinan, Shandong, 250103, China.
Wenxiu BaoShandong Provincial Key Laboratory of Applied Microbiology, Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), No. 28789 Jingshi East Road, Licheng District, Jinan, Shandong, 250103, China.
Wen ZhangShandong Provincial Key Laboratory of Applied Microbiology, Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), No. 28789 Jingshi East Road, Licheng District, Jinan, Shandong, 250103, China. zw-sunshine@163.com.ORCID http://orcid.org/0000-0003-0859-6905
Minshi WangShandong Provincial Key Laboratory of Applied Microbiology, Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), No. 28789 Jingshi East Road, Licheng District, Jinan, Shandong, 250103, China.
Qingqing ZhaoShandong Provincial Key Laboratory of Applied Microbiology, Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), No. 28789 Jingshi East Road, Licheng District, Jinan, Shandong, 250103, China.
Yujie HuangShandong Provincial Key Laboratory of Applied Microbiology, Ecology Institute of Shandong Academy of Sciences, Qilu University of Technology (Shandong Academy of Sciences), No. 28789 Jingshi East Road, Licheng District, Jinan, Shandong, 250103, China.
Yuan LuCollege of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.

Funding

Major Innovative Projects in the Pilot Program for the Integration of Science, Education, and Industry of Qilu University of Technology in China 2024ZDZX10National Key Research and Development Program of China 2023YFC3709004National Natural Science Foundation of China U22A20615
6 · The paper itself

Abstract

Bacterial communities are crucial for connecting aquatic and sediment ecosystems. Water and sediment samples were collected from the Jinan section of the lower Yellow River, and absolute abundances of bacterial taxa were obtained via high-throughput absolute quantification. Integrating physicochemical properties, the water-sediment bacterial communities exhibited interactive characteristics of "high connectivity and strong heterogeneity". High connectivity was manifested in similar community and functional compositions and assembly mechanisms, along with shared core genera, in which high-concentration suspended particulates played a key role. Strong heterogeneity was reflected in distinct taxa abundances, diversity, co-occurrence network topologies, and functional specializations, all regulated by environmental factors. Sediments harbored total bacterial abundances and abundances of dominant phyla 1-2 orders of magnitude higher than those in water. Water community showed higher α-diversity and co-occurrence network complexity (edges, average degree, graph density). Eighteen shared genera (belonging to Pseudomonadota and Bacteroidota etc.) with cross-medium survival adaptability were identified. Functional connectivity was supported by 99.1% shared KOs, despite sediments had greater carbon/nitrogen cycling potential than that in water. Stochastic processes, mainly drift, dominated community assembly, contributing more in water (93.6%) than in sediment (75.5%). This study provides microbiological quantitative indicators for Yellow River ecological assessment, identifies cross-medium adaptive genera as potential bioremediation resources, and offers a microbiological perspective on ecosystem maintenance in adjacent river habitats.

Indexed as

BacteriaGeologic SedimentsMicrobiotaRiversWater MicrobiologyBiodiversityChinaEcosystemHigh-Throughput Nucleotide SequencingPhylogenyRNA, Ribosomal, 16SRNA, Ribosomal, 16SBacterial communityCommunity interactionHigh-throughput absolute quantificationSedimentWaterYellow River

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.