Evidence map›Paper›PMID 39516921›Full record

ArticleJournal of nanobiotechnology2024

Manipulation in root-associated microbiome via carbon nanosol for plant growth improvements.

Lingtong Cheng, Jiemeng Tao, Peng Lu, Taibo Liang, Xutao Li, Dong Chang, Huan Su, Wei He, Zechao Qu, He Li and 6 more

Abstract read
In one paragraph

Article in Journal of nanobiotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review of Antimicrobial Properties of Carbon Nanomaterials.International journal of molecular sciences · 2026
    Review
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Lingtong ChengBeijing Life Science Academy, Beijing, 102200, China.
Jiemeng TaoBeijing Life Science Academy, Beijing, 102200, China.
Peng LuBeijing Life Science Academy, Beijing, 102200, China.
Taibo LiangKey Laboratory of Ecological Environment and Tobacco Quality, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou, 450001, China.
Xutao LiHenan Provincial Tobacco Company, Zhengzhou, 450001, China.
Dong ChangHenan Provincial Tobacco Company, Zhengzhou, 450001, China.
Huan SuBeijing Life Science Academy, Beijing, 102200, China.
Wei HeFujian Tobacco Industry Co., Ltd, Xiamen, 361001, China.
Zechao QuChina Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou, 450001, China.
He LiChina Tobacco Gene Research Center, Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou, 450001, China.
Wenjun MuBeijing Life Science Academy, Beijing, 102200, China.
Wei ZhangChina National Tobacco Quality Supervision & Test Center, Zhengzhou, 450001, China.
Nan LiuChina National Tobacco Quality Supervision & Test Center, Zhengzhou, 450001, China.
Jianfeng ZhangBeijing Life Science Academy, Beijing, 102200, China.
Peijian CaoBeijing Life Science Academy, Beijing, 102200, China. peijiancao@163.com.
Jingjing JinBeijing Life Science Academy, Beijing, 102200, China. jinjingjing1218@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundModulating the microbiome with nanomaterials has been proposed to improve plant growth, and reduce reliance on external inputs. Carbon Nanosol (CNS) was attracted for its potential to improve plant productivity. However, the mechanism between CNS and rhizosphere microorganisms remained largely elusive.

resultsHere, we tried to systematically explore the effects of CNS (600 and 1200 mg/L by concentration) on tobacco growth, soil physical properties, and root-associated microbiome. The influence of CNS on soil physicochemical properties and plant growth was significant and dose-dependent, leading to a 28.82% increase in biomass accumulation by 600 mg/L CNS. Comparison between the CNS-treated and control plants revealed significant differences in microbiome composition, including 1148 distinct ASVs (923 bacteria and 225 fungi), microbiome interactions, and metabolic function of root-associated microbiomes. Fungal and bacterial communities had different response patterns for CNS treatment, with phased and dose-dependent effects, with the most significant changes in microbial community structure observed at 1200 mg/L after 10 days of treatment. Microbial networks of CNS-treated plants had more nodes and edges, higher connectivity, and more hub microorganisms than those of control plants. Compared with control, CNS significantly elevated abundances of various bacterial biomarkers (such as Sphingomonas and Burkholderia) and fungi biomarkers (including Penicillium, Myceliophthora, and Talaromyces), which were potential plant-beneficial organisms. Functional prediction based on metagenomic data demonstrated pathways related to nutrient cycling being greatly enriched under CNS treatment. Furthermore, 391 culturable bacteria and 44 culturable fungi were isolated from soil and root samples. Among them, six bacteria and two fungi strains enriched upon CNS treatment were validated to have plant growth promotion effect, and two fungi (Cladosporium spp. and Talaromyces spp.) played their roles by mediating volatile organic compounds (VOCs). To some extent, the driving and shaping of the microbiome by CNS contributed to its impact on plant growth and development.

conclusionOur results revealed the key role of root-associated microbiota in mediating the interaction between CNS and plants, thus providing valuable insights and strategies for harnessing CNS to enhance plant growth.

Indexed as

BacteriaCarbonFungiMicrobiotaPlant DevelopmentPlant RootsRhizosphereSoil MicrobiologyBiomassNanostructuresNicotianaSoilCarbonSoilCarbon nanosolEngineered nanomaterialsMicrobiomePlant growthPlant growth-promoting rhizobacteria

Identifiers

PMID39516921
PMCPMC11549841

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.