Patterns and drivers of microbiome in different rock surface soil under the volcanic extreme environment

Chen, Jin; Li, Zishan; Xu, Daolong; Xiao, Qiang; Liu, Haijing; Li, Xiaoyü; Chao, Lumeng; Qu, Hanting; Zheng, Yinhe; Li, Xinyan; Wang, P.; Bao, Yulong

doi:10.1002/imt2.122

Cited by 21 publications

(3 citation statements)

References 57 publications

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“…Additionally, nitrate reductase ( NarG ) was in class 0 and can be represented by landmark genes that encode superoxide dismutase ( SOD ) and 4‐hydroxy‐tetrahydrodipicolinate synthase ( DapA ), both of which were critical enzymes in antioxidant systems, mainly involved in superoxide scavenging. This was also supported by the domain role of SOD in determining the microbial network in a previous study [ 35 ].…”

Section: Resultssupporting

confidence: 79%

From mechanism to application: Decrypting light‐regulated denitrifying microbiome through geometric deep learning

Liao,

Zhao,

Bian

et al. 2024

iMeta

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Regulation on denitrifying microbiomes is crucial for sustainable industrial biotechnology and ecological nitrogen cycling. The holistic genetic profiles of microbiomes can be provided by meta‐omics. However, precise decryption and further applications of highly complex microbiomes and corresponding meta‐omics data sets remain great challenges. Here, we combined optogenetics and geometric deep learning to form a discover–model–learn–advance (DMLA) cycle for denitrification microbiome encryption and regulation. Graph neural networks (GNNs) exhibited superior performance in integrating biological knowledge and identifying coexpression gene panels, which could be utilized to predict unknown phenotypes, elucidate molecular biology mechanisms, and advance biotechnologies. Through the DMLA cycle, we discovered the wavelength‐divergent secretion system and nitrate‐superoxide coregulation, realizing increasing extracellular protein production by 83.8% and facilitating nitrate removal with 99.9% enhancement. Our study showcased the potential of GNNs‐empowered optogenetic approaches for regulating denitrification and accelerating the mechanistic discovery of microbiomes for in‐depth research and versatile applications.

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Section: Resultssupporting

confidence: 79%

From mechanism to application: Decrypting light‐regulated denitrifying microbiome through geometric deep learning

Liao,

Zhao,

Bian

et al. 2024

iMeta

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“…3 ). The network was constructed using the top 100 fungal ASVs of key soil microbial communities [ 27 ]. The CK network consists of 245 nodes and 6,681 edges.…”

Section: Resultsmentioning

confidence: 99%

Combined Application Effects of Arbuscular Mycorrhizal Fungi and Biochar on the Rhizosphere Fungal Community of Allium fistulosum L.

Xiao

et al. 2023

J. Microbiol. Biotechnol.

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Arbuscular mycorrhizal fungi (AMF) are widespread soil endophytic fungi, forming mutualistic relationships with the vast majority of land plants. Biochar (BC) has been reported to improve soil fertility and promote plant growth. However, limited studies are available concerning the combined effects of AMF and BC on soil community structure and plant growth. In this work, a pot experiment was designed to investigate the effects of AMF and BC on the rhizosphere microbial community of Allium fistulosum L. Using Illumina high-throughput sequencing, we showed that inoculation of AMF and BC had a significant impact on soil microbial community composition, diversity, and versatility. Increases were observed in both plant growth (the plant height by 8.6%, shoot fresh weight by 12.1%) and root morphological traits (average diameter by 20.5%). The phylogenetic tree also showed differences in the fungal community composition in A. fistulosum . In addition, Linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed that 16 biomarkers were detected in the control (CK) and AMF treatment, while only 3 were detected in the AMF + BC treatment. Molecular ecological network analysis showed that the AMF + BC treatment group had a more complex network of fungal communities, as evidenced by higher average connectivity. The functional composition spectrum showed significant differences in the functional distribution of soil microbial communities among different fungal genera. The structural equation model (SEM) confirmed that AMF could improve the microbial multifunctionality by regulating the rhizosphere fungal diversity and soil properties. Our findings provide new information on the effects of AMF and biochar on plants and soil microbial communities.

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“…In agricultural soils, the myriad of microbes lives together and form complex interconnected microbial networks, where microbes associate with each other directly or indirectly through processes, such as competition, predation, and mutualism ( de Vries et al, 2018 ; Wagg et al, 2019 ). It is theoretically expected that microbial communities with more complex associations will have more active metabolic processes and faster growth rates, resulting in improved community performance ( Brown et al, 2004 ; Chen et al, 2023 ; Jordan, 2009 ). Previous researchers have tried to link microbial network complexity to ecosystem multifunctionality ( Chen et al, 2022 ; Wagg et al, 2019 ), and Chen et al (2022) reported that soil microbial network complexity contributed more to multifunctionality than diversity.…”

Section: Introductionmentioning

confidence: 99%

Maize residue retention shapes soil microbial communities and co-occurrence networks upon freeze-thawing cycles

Yu,

Guo,

Zhang

et al. 2024

PeerJ

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Maize residue retention is an effective agricultural practice for improving soil fertility in black soil region, where suffered from long freezing-thawing periods and intense freeze-thawing (FT) cycles. However, very few studies have examined the influence of maize residue retention on soil microbial communities under FT cycles. We investigated the response of soil microbial communities and co-occurrence networks to maize residue retention at different FT intensities over 12 cycles using a microcosm experiment conditioned in a temperature incubator. Our results indicated that maize residue retention induced dramatic shifts in soil archaeal, bacterial and fungal communities towards copiotroph-dominated communities. Maize residue retention consistently reduced soil fungal richness across all cycles, but this effect was weaker for archaea and bacteria. Normalized stochastic ratio analysis revealed that maize residue retention significantly enhanced the deterministic process of archaeal, bacterial and fungal communities. Although FT intensity significantly impacted soil respiration, it did not induce profound changes in soil microbial diversity and community composition. Co-occurrence network analysis revealed that maize residue retention simplified prokaryotic network, while did not impact fungal network complexity. The network robustness index suggested that maize residue retention enhanced the fungal network stability, but reduced prokaryotic network stability. Moreover, the fungal network in severe FT treatment harbored the most abundant keystone taxa, mainly being cold-adapted fungi. By identifying modules in networks, we observed that prokaryotic Module #1 and fungal Module #3 were enhanced by maize residue retention and contributed greatly to soil quality. Together, our results showed that maize residue retention exerted stronger influence on soil microbial communities and co-occurrence network patterns than FT intensity and highlighted the potential of microbial interactions in improving soil functionality.

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Patterns and drivers of microbiome in different rock surface soil under the volcanic extreme environment

Cited by 21 publications

References 57 publications

From mechanism to application: Decrypting light‐regulated denitrifying microbiome through geometric deep learning

From mechanism to application: Decrypting light‐regulated denitrifying microbiome through geometric deep learning

Combined Application Effects of Arbuscular Mycorrhizal Fungi and Biochar on the Rhizosphere Fungal Community of Allium fistulosum L.

Maize residue retention shapes soil microbial communities and co-occurrence networks upon freeze-thawing cycles

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