Live spatial validation of plant-microbe interactions in the rhizosphere with light-sheet fluorescence microscopy
- 1State Key Laboratory for Quality and Safety of Agro-Products, Zhejiang Provincial Key Laboratory of Agricultural Microbiomics, Institute of Environment, Resource, Soil and Fertilizer, Zhejiang Academy of Agricultural Sciences
Abstract
Plant-microbe interactions in the rhizosphere are spatial events, yet mechanisms are often inferred from bulk samples, endpoint images, or community profiles averaged across heterogeneous root zones. Rather than surveying LSFM hardware or rhizosphere imaging broadly, this review evaluates light-sheet fluorescence microscopy (LSFM) as a platform for claim-level live spatial validation. Evidence is separated into four levels: A, direct LSFM evidence; B, an LSFM-compatible sample or device demonstrated with another modality; C, a correlative or validation modality; and D, a proposed future application. Within the verified full-text evidence set, direct evidence is concentrated in whole-rhizosphere tracking of Bacillus populations, plant reporter responses during early root-fungus interactions, and rhizobial attachment and infection of root hairs. Many arbuscular mycorrhizal and biocontrol applications remain prospective. We compare instrument and sample choices across field of view, numerical aperture, voxel sampling, time interval, spectral channels, and matrix realism; define root-centric metrics for arrival, residence, occupancy, growth, and persistence; and distinguish simultaneous, sequential in situ , and destructive endpoint validation. LSFM can identify where and when a candidate interaction occurs, but identity, activity, perturbation, and functional assays are still required before mechanism is assigned. A minimum reporting checklist is proposed to connect optical settings, environmental context, hierarchical sampling, registration error, and open analysis. The strongest role of LSFM in rhizosphere research is therefore targeted and evidence-bounded: resolving a live spatial prediction and directing independent tests of what the interaction does and why.
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BibTeX
@article{dong2026live,
title = {{Live spatial validation of plant-microbe interactions in the rhizosphere with light-sheet fluorescence microscopy}},
author = {Xingshui Dong and Qilu Cheng and Junwei Ma and Feng Wang and Hui Lin},
journal = {Frontiers in Plant Science},
year = {2026},
month = oct,
doi = {10.3389/fpls.2026.1953583},
url = {https://www.frontiersin.org/articles/10.3389/fpls.2026.1953583/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Live spatial validation of plant-microbe interactions in the rhizosphere with light-sheet fluorescence microscopy
AU - Xingshui Dong
AU - Qilu Cheng
AU - Junwei Ma
AU - Feng Wang
AU - Hui Lin
PY - 2026
DA - 2026/10/05
JO - Frontiers in Plant Science
DO - 10.3389/fpls.2026.1953583
UR - https://www.frontiersin.org/articles/10.3389/fpls.2026.1953583/full
AB - Plant-microbe interactions in the rhizosphere are spatial events, yet mechanisms are often inferred from bulk samples, endpoint images, or community profiles averaged across heterogeneous root zones. Rather than surveying LSFM hardware or rhizosphere imaging broadly, this review evaluates light-sheet fluorescence microscopy (LSFM) as a platform for claim-level live spatial validation. Evidence is separated into four levels: A, direct LSFM evidence; B, an LSFM-compatible sample or device demonstrated with another modality; C, a correlative or validation modality; and D, a proposed future application. Within the verified full-text evidence set, direct evidence is concentrated in whole-rhizosphere tracking of Bacillus populations, plant reporter responses during early root-fungus interactions, and rhizobial attachment and infection of root hairs. Many arbuscular mycorrhizal and biocontrol applications remain prospective. We compare instrument and sample choices across field of view, numerical aperture, voxel sampling, time interval, spectral channels, and matrix realism; define root-centric metrics for arrival, residence, occupancy, growth, and persistence; and distinguish simultaneous, sequential in situ , and destructive endpoint validation. LSFM can identify where and when a candidate interaction occurs, but identity, activity, perturbation, and functional assays are still required before mechanism is assigned. A minimum reporting checklist is proposed to connect optical settings, environmental context, hierarchical sampling, registration error, and open analysis. The strongest role of LSFM in rhizosphere research is therefore targeted and evidence-bounded: resolving a live spatial prediction and directing independent tests of what the interaction does and why.
SN - 1664-462X
ER -