Ruihong Wang , Hao Qin , Zhijian Shi , Mengben Wang , Junjian Li
{"title":"通过简化原核生物和复杂真菌网络增强盐碱地微生物网络稳定性和生物地球化学循环","authors":"Ruihong Wang , Hao Qin , Zhijian Shi , Mengben Wang , Junjian Li","doi":"10.1016/j.apsoil.2025.106245","DOIUrl":null,"url":null,"abstract":"<div><div>Soil salinization has rapidly become a critical global environmental issue in the current century. Understanding the structure of microbial networks and their interactions with biogeochemical cycles is vital to maintaining the stability of microbial communities and predicting ecosystem responses to salinization under climate change scenarios. Using metagenomic sequencing focuses on analyzing microbial community characteristics, as well as the function genes responsible for the cycles of carbon (C), nitrogen (N), phosphorus (P), and sulfur (S), in four distinct natural saline-alkali gradients: Non-saline, Low salinity, Medium salinity, and High salinity. The result revealed that salinity significantly alters the structures of bacterial, fungal, and archaeal communities and influences the functional genes related to the biogeochemical cycles. Notably, the increase of relative abundance in Proteobacteria (0.20, 0.30, 0.36, 0.38) with salinity, suggest its utility as a salinity indicator. Linear regression model revealed a significant negative correlation between salinity and the network complexity of prokaryotic, with higher network complexity does not favor the structural stability. In contrast, fungi network complexity positively correlated with salinity and stability. Additionally, while the complexity of prokaryotic networks significant negatively correlated with the metabolic potential of C, N, and S cycles, fungal showed a significantly positive correlation with P cycling. Random forest results identified salinity as the top driver of microbial network complexity (bacteria: 8.28 %; fungi: 7.22 %, archaea: 9.28 %). These insights suggest that the structural differences between prokaryotes and fungi result in varying responses to salinity, network structure, and elemental cycles. The interplay between simplified prokaryotic networks and more complex fungal networks could enhance microbial network stability and improve biogeochemical cycling. This study newly identifies the divergent responses of prokaryotic and fungal networks to salinity, challenging previous assumptions about uniform microbial responses. Therefore, maintaining the appropriate complexity of belowground communities is essential for the effective management of saline-alkali ecosystems and sustainable agricultural development.</div></div>","PeriodicalId":8099,"journal":{"name":"Applied Soil Ecology","volume":"213 ","pages":"Article 106245"},"PeriodicalIF":4.8000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced microbial network stability and biogeochemical cycles in saline-alkali soil through simplified prokaryotes and complex fungal networks\",\"authors\":\"Ruihong Wang , Hao Qin , Zhijian Shi , Mengben Wang , Junjian Li\",\"doi\":\"10.1016/j.apsoil.2025.106245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Soil salinization has rapidly become a critical global environmental issue in the current century. Understanding the structure of microbial networks and their interactions with biogeochemical cycles is vital to maintaining the stability of microbial communities and predicting ecosystem responses to salinization under climate change scenarios. Using metagenomic sequencing focuses on analyzing microbial community characteristics, as well as the function genes responsible for the cycles of carbon (C), nitrogen (N), phosphorus (P), and sulfur (S), in four distinct natural saline-alkali gradients: Non-saline, Low salinity, Medium salinity, and High salinity. The result revealed that salinity significantly alters the structures of bacterial, fungal, and archaeal communities and influences the functional genes related to the biogeochemical cycles. Notably, the increase of relative abundance in Proteobacteria (0.20, 0.30, 0.36, 0.38) with salinity, suggest its utility as a salinity indicator. Linear regression model revealed a significant negative correlation between salinity and the network complexity of prokaryotic, with higher network complexity does not favor the structural stability. In contrast, fungi network complexity positively correlated with salinity and stability. Additionally, while the complexity of prokaryotic networks significant negatively correlated with the metabolic potential of C, N, and S cycles, fungal showed a significantly positive correlation with P cycling. Random forest results identified salinity as the top driver of microbial network complexity (bacteria: 8.28 %; fungi: 7.22 %, archaea: 9.28 %). These insights suggest that the structural differences between prokaryotes and fungi result in varying responses to salinity, network structure, and elemental cycles. The interplay between simplified prokaryotic networks and more complex fungal networks could enhance microbial network stability and improve biogeochemical cycling. This study newly identifies the divergent responses of prokaryotic and fungal networks to salinity, challenging previous assumptions about uniform microbial responses. Therefore, maintaining the appropriate complexity of belowground communities is essential for the effective management of saline-alkali ecosystems and sustainable agricultural development.</div></div>\",\"PeriodicalId\":8099,\"journal\":{\"name\":\"Applied Soil Ecology\",\"volume\":\"213 \",\"pages\":\"Article 106245\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2025-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Soil Ecology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S092913932500383X\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOIL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Soil Ecology","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092913932500383X","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOIL SCIENCE","Score":null,"Total":0}
Enhanced microbial network stability and biogeochemical cycles in saline-alkali soil through simplified prokaryotes and complex fungal networks
Soil salinization has rapidly become a critical global environmental issue in the current century. Understanding the structure of microbial networks and their interactions with biogeochemical cycles is vital to maintaining the stability of microbial communities and predicting ecosystem responses to salinization under climate change scenarios. Using metagenomic sequencing focuses on analyzing microbial community characteristics, as well as the function genes responsible for the cycles of carbon (C), nitrogen (N), phosphorus (P), and sulfur (S), in four distinct natural saline-alkali gradients: Non-saline, Low salinity, Medium salinity, and High salinity. The result revealed that salinity significantly alters the structures of bacterial, fungal, and archaeal communities and influences the functional genes related to the biogeochemical cycles. Notably, the increase of relative abundance in Proteobacteria (0.20, 0.30, 0.36, 0.38) with salinity, suggest its utility as a salinity indicator. Linear regression model revealed a significant negative correlation between salinity and the network complexity of prokaryotic, with higher network complexity does not favor the structural stability. In contrast, fungi network complexity positively correlated with salinity and stability. Additionally, while the complexity of prokaryotic networks significant negatively correlated with the metabolic potential of C, N, and S cycles, fungal showed a significantly positive correlation with P cycling. Random forest results identified salinity as the top driver of microbial network complexity (bacteria: 8.28 %; fungi: 7.22 %, archaea: 9.28 %). These insights suggest that the structural differences between prokaryotes and fungi result in varying responses to salinity, network structure, and elemental cycles. The interplay between simplified prokaryotic networks and more complex fungal networks could enhance microbial network stability and improve biogeochemical cycling. This study newly identifies the divergent responses of prokaryotic and fungal networks to salinity, challenging previous assumptions about uniform microbial responses. Therefore, maintaining the appropriate complexity of belowground communities is essential for the effective management of saline-alkali ecosystems and sustainable agricultural development.
期刊介绍:
Applied Soil Ecology addresses the role of soil organisms and their interactions in relation to: sustainability and productivity, nutrient cycling and other soil processes, the maintenance of soil functions, the impact of human activities on soil ecosystems and bio(techno)logical control of soil-inhabiting pests, diseases and weeds.