Emerging sensing, imaging, and computational technologies to scale nano-to macroscale rhizosphere dynamics - Review and research perspectives

Abstract

The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling can advance our understanding of the complex rhizosphere system. Particularly, we provide our perspectives and discuss future directions in developing in situ rhizosphere sensing technologies that could potentially correlate local-scale interactions to ecosystem scale impacts. We first review integrated multimodal imaging techniques for tracking inorganic elements and organic carbon flow at nano- to microscale in the rhizosphere, followed by a discussion on the use of synthetic soil and plant habitats that bridge laboratory-to-field studies on the rhizosphere processes. We then describe applications of genetically encoded biosensors in monitoring nutrient and chemical exchanges in the rhizosphere, and the novel nanotechnology-mediated delivery approaches for introducing biosensors into the root tissues. Next, we review the recent progress and express our vision on field-deployable sensing technologies such as planar optodes for quantifying the distribution of chemical and analyte gradients in the rhizosphere under field conditions. Moreover, we provide perspectives on the challenges of linking complex rhizosphere interactions to ecosystem sensing for detecting biological traits across scales, which arguably requires using the best-available model predictions including the model-experiment and image-based modeling approaches. Experimental platforms relevant to field conditions like SMART (Sensors at Mesoscales with Advanced Remote Telemetry) soils testbed, coupled with ecosystem sensing and predictive models, can be effective tools to explore coupled ecosystem behavior and responses to environmental perturbations. Finally, we envision that with the advent of novel high-resolution imaging capabilities at nano- to macroscale, and remote biosensing technologies, combined with advanced computational models, future studies will lead to detection and upscaling of rhizosphere processes toward ecosystem and global predictions.

Keywords: ModEx; Rhizodeposition; biosensors; carbon flow; image-based modeling; nutrients gradients.

Figure 1.

Representation of a multimodal imaging technologies for investigating and disentangling the heterogeneity and complexity of rhizosphere-integrated processes and reactions with increasing resolution, from millimeter to nanometer scale.

Figure 2.

Current cutting-edge and emerging mass spectrometry, imaging, tomography, and omics technologies (left panel) can be coupled with specific platforms like synthetic soil habit micromodels, rhizogrids, and ecotrons (right panel) to study rhizosphere processes at different scales. In many cases, multiple techniques can be applied to a single sample to enrich the resulting dataset and enable evaluation of complex questions (e.g., related to nutrient exchange, organic-inorganic interactions, or spatial organization of processes). Thus, these analytical techniques and platforms can provide critical mechanistic understanding of the rhizosphere processes and reactions associated with carbon fluxes, including rhizodeposition and root exudation.

Figure 3.

Biosensors for plant leaf and root imaging. A. Single-strand, DNA-coated, single-walled, carbon nanotube SWCNTs have been applied for NO detection in Arabidopsis leaves. B. Silver-coated gold nanostars (AuNS@Ag) have been used for microRNA detection in Arabidopsis leaves. C. Disulfide-modified aptamers have been developed for glucose detection in Arabidopsis leaves. D. Optical nanosensors and radio-frequency nanoelectronic could potentially be engineered for plant signaling molecule and volatile compound detection in roots, respectively.

Figure 4.

(Left) Grey-scale laboratory and false-color field images of [O₂] in sediment vegetated with Sporobolus alterniflorus, a dominant salt marsh intertidal grass on Atlantic and Gulf U.S. coasts. Quantification via color ratiometric imaging following (Larsen et al., 2011), except the oxygen-sensitive fluorophore was platinum (II) meso-tetra (pentafluorophenyl) porphine (PtTFPP). Horizontal grey arrow on false-colored field images denotes the water level, (Cardon pers. comm). (Right) Coupling of replicated field planar optode measurements with small- and large-scale process modeling, in the footprint of landscape-scale eddy covariance measurements, holds great promise for determining whether and how small-scale spatial heterogeneity in sediment environmental conditions affect aggregate larger scale biogeochemical process.

Figure 5.

A. Schematic setup of the SMART Soils testbed showing an arrangement of sensors deployed, including load cells, geophysical sensors, soil probes, energy, and mass flow sensors as well as micrometeorological sensors. B. A snapshot of 3D soil water content distribution and plant distribution on the SMART Soils testbed from geophysical and phenocam imaging. C. Evolution of soil water potential and the corresponding stress conditions for multiple plant species, e.g., grass, thistle, dock, or bare ground. D. Correlations between soil water content and soil CO₂ fluxes under different temperature conditions.

Figure 6.

Plant nitrogen uptake from mycorrhizae at the global scale. This is an example of multiple plant–soil–microbe processes now integrated into global models such as the E3SM Land Model (ELM), including nitrogen and phosphorus uptake partitioned between AM and ECM fungi, direct root uptake of nutrients, and biological nitrogen fixation (Braghiere et al., 2022).

Figure 7.

Envisioning the future of rhizosphere research by means of building a tiered sensing platform approach. This approach must ensure measurements of rhizosphere complex parameters and promote biosensing connectivity across components (soil, microbes, plant, atmosphere) and scales (omics to ecosystems). Development of advanced data retrieval, image-based modeling, analytical and computing tools, and integration with the ModEx approach should leverage our understanding of small-scale mechanistic processes to the large-scale field, ecosystem, and global sensing. This strategy will provide novel and important mechanistic understanding of key rhizosphere processes including nutrient cycle, root–microbe interactions, root exudation, signaling cascades, plant–plant interactions, and the global-scale impacts of climate change.