Introduction
While water is a basic requirement for plants, too much or too little can have drastic consequences. As global climate changes, the frequency and severity of extreme weather events have increased (Dethier et al. 2020; Davenport et al. 2021; Chiang et al. 2021; Balting et al. 2021), decreasing plant primary productivity and resulting in billions of dollars of losses to crop species (Rosenzweig et al. 2002). Plant roots are the point of interaction between plants and soils, serving as the front line in response to dramatic changes in soil water content. Roots under water stress display stunning amounts of phenotypic plasticity, altering their architecture and undergoing dramatic changes in anatomical structure (Karlova et al. 2021). Given the role roots play in the absorption of nutrients and water, anchorage, and interactions with soil microorganisms, it will be paramount to further our understanding of their anatomical response to water stress and how this response alters these roles. An impediment to anatomical analysis at the plant phenomics scale (hundreds of samples or more) is the time required to create anatomical sections; therefore, increased sample throughput can be achieved by targeting the particular regions of a root with the greatest response to water stress. However, this would require an increased resolution of where, along the length of a root, phenotypic responses to water stress are the strongest, as well as the commonalities and differences in these responses among root sections.
Water stress for plant roots includes both over-abundance (i.e., flooding, either submergence or waterlogging) and deficiency (i.e., drought). Parallels and contrasts exist for plant responses between these stressors (S. Chen et al. 2023; Haverroth et al. 2024). Changes in root porosity, particularly of the root cortex, are among the most visually conspicuous anatomical responses to water stress. Greater porosity in the root cortex can be achieved by the formation or enlargement of intracellular spaces in the root cortex, termed root cortical aerenchyma (Armstrong 1971; Colmer 2003). Under waterlogging, roots quickly enter a hypoxic state due to decreased gas diffusion with soil. Root cortical aerenchyma can assist in this critical state by allowing diffusion to occur between the root and shoot system (Jackson and Armstrong 1999). This diffusion can result in higher O2 levels in the root tip and allow a route for the release of stress-induced volatiles (e.g., ethylene, salicylic acid, ethanol, methyl jasmonate) from the shoot (Colmer 2003; Voesenek and Bailey-Serres 2015). The increase in cortex porosity is often accompanied by suberization of the root endo/exodermis, which seals the root in a waxy hydrophobic layer decreasing radial oxygen and water loss (Enstone et al. 2002; A. Chen et al. 2022). For instance, root exodermal suberin production in Solanum improved stem water content and performance under water-deficit conditions (Cantó-Pastor et al. 2024). Under drought conditions, increased porosity of roots is hypothesized to decrease the metabolic cost of soil exploration by decreasing the number of living cells to sustain (Zhu et al. 2010; Jaramillo et al. 2013). As many plant species need to be able to survive both periods of excess and limited water, we sought to understand both commonalities and differences in root anatomy between these extremes and where they manifest along the length of a root. Addressing this question is essential for understanding how root function varies spatially under stress conditions and for designing experiments that leverage this information.
Here, we use the warm-season perennial bunchgrass
The objective of this study was to investigate the anatomical responses of
Methods
Experimental Design and Sampling
Seeds of
Every other day prior to the commencement of the stress treatments, seedlings were monitored and watered to saturation, and excess water was allowed to drain. Data on shoot height at 28 days after planting was used to distribute plants into treatment groups (n = 60 total, 12 replicates per treatment) such that the mean height of plants within each treatment group was equivalent. Treatments were as follows: 10 days without watering (Drought), 24, 48, and 72 h of soil waterlogging (Waterlogged 24, 48, 72, respectively), and normal watering conditions (Control; Figure 1). Our choice of drought treatment was based on pilot experiments in which we observed that soil drying and signs of drought stress (leaf rolling) were apparent within 10 days of water withholding in this species, which we also observed during this experiment. All treatment groups had a small amount of sand placed on top of the soil surface, which was necessary to stabilize soil and reduce perlite floating in the waterlogging treatments but was applied to all treatment groups for consistency. Treatment groups were arranged across an approximate 1.3 m2 area. Waterlogged treatments were arranged in three polypropylene tubs; 24, 48, and 72 were randomized across tubs (Figure 1B). Treatment groups were harvested directly following their stress treatment, with no recovery period. Upon harvesting, the shoot system was removed and dried, and roots were washed of soil. Care was taken to select a single nodal root (arising from the plant base) for anatomical analysis. At this stage of
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Root Sectioning and Image Analysis
Root segments were hand sectioned transversally using a Teflon coated razor blade. Transverse sections were stained with 1.25% toluidine blue (MilliporeSigma, Burlington, MA, USA) for 1 min, washed with 15% ethanol for 1 min, and wet mounted on a slide with coverslip using distilled water. Sections were imaged at 40x magnification on an upright microscope (3000-LED) with an attached camera module (ExcelisHD/4 K; ACCU-SCOPE Inc., Commack, NY, USA). For three plants per treatment, we made three sections per segment to assess the variation within the centimeter segment of root. The three sections were made by sectioning the majority of the 1 cm segment, floating in distilled water before selecting three representative sections for mount as described above. We found that little variation was captured by collecting multiple sections per segment (see Results), thus we elected to collect only one section per segment for the remainder of the plants. Section images were analyzed using ImageJ (Schindelin et al. 2012); measurements collected are described in Table S1. All images were scaled to convert from pixel measurements to μm.
Statistical Analysis
All statistical analysis was conducted in R v4.2.2 (R Core Team 2022), utilizing the following packages: tidyverse v2.0.0 (Wickham et al. 2019), lme4 v1.1–351 (Bates et al. 2015), emmeans v1.9.0 (Lenth et al. 2020), and ggpubr v0.6.0 (). To assess whether water stress treatments impacted the shoot system, we fit a linear mixed model both to shoot height and shoot dry weight, with treatment as a main effect and germination cohort as a random effect (accounting for transplant date). For each anatomical root trait, we fit the following linear mixed-effects model: Root Trait ~ Treatment + Segment + Treatment × Segment + (1|Plant_ID). All models were assessed using a Type III ANOVA framework. Post hoc comparisons of estimated marginal means were made using a Dunnett's test with each of the experimental treatments being compared to the control.
For the 15 plants for which we measured three replicate sections within each centimeter segment, we assessed whether using replicate sections improved model performance. We fit the above model using both the mean root trait value (averaged across replicates) or a randomized combination of sections (i.e., drawn from the three available technical replicates). We repeated the random selection process 1000 times, refitting the model each time and compared this distribution to the marginal R2 of the model fit to the averaged data (Figure S3). We also examined the amount of variance among plants, among segments, and among replicate sections. To do this, we fit the following linear mixed-effects model separately for each treatment group: Root Trait ~ (1|Plant_ID) + (1|Plant_ID:Segment). From this model, we extracted variance components to calculate percent variance explained (PVE). The “Plant_ID” term captured variation among plants, the “Plant_ID:Segment” term captured variation among segments within a plant, and the residual variance represented variation among replicate sections within a segment. For Metaxylem Vessel Number, zero variance was detected among replicate sections; thus, we dropped the “Plant_ID:Segment” term and interpreted the residual variance as capturing variation among segments within a plant.
Results
The Shoot Was Minimally Impacted by Short-Term Water Stress
The average dry weight of the shoot was 79.8 mg (SE = 4.74 mg) while the average height across treatments was 189.2 mm (SE = 6.5 mm). Water stress treatments did not significantly impact the height or dry weight of the shoot (Figure 2). This was expected, as the water stress treatments were short in duration, with no recovery period afterward, making a significant effect on shoot growth unlikely (Malik et al. 2002).
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Variation Among Plants and Root Segments Greatly Exceeds Variation Among Technical Replicates
To determine whether technical replicates are necessary to accurately quantify root anatomical traits, we quantified the variation between replicate sections made from a single centimeter segment. That is, for three plants per treatment, we performed sectioning in triplicate and compared the variation among replicate sections within a segment to the variation among segments within a plant (i.e., from root tip to base) and among plants within a treatment. We found that modeling the average of the three technical replicate sections did not improve explanatory power compared to modeling a single randomly selected replicate section (Figure S3). For most traits, more variation was captured among root segments and among plants than among replicate sections (Figure 3). The mean percent variance explained (PVE) across all traits ranged from 34.6%–70.5% for variation among plants, 23.9%–51.9% among segments, and 6.2%–16.0% among replicates. This result motivated our decision to collect only a single section per segment of root for the remaining plants (N = 44), which allowed us to increase the number of plants for each treatment group (N ≥ 10 per treatment). However, root hair density and epidermis depth stood out as having relatively higher variation among replicate sections across treatments; for these traits, some caution should be taken as our segmentation design (1 cm resolution) may ignore a moderate amount of variation.
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Root Anatomical Responses Depend on Root Segment and Water Stress Treatment
Root trait responses differed according to which portion of the root was examined and the water stress treatment the plant experienced (Figure 4). Plant roots that had experienced drought showed a large increase in root hair number (Figures 4A and 5A), with an increase of 16.6 and 12.9 hairs/mm for the first two segments near the root tip, respectively. Waterlogged roots showed no significant deviation from the control plants in terms of root hair number (Figures 4B–D and 5A). In general, we observed that many trait responses were similar across all stresses; for example, the root area across segments was reduced under all stresses compared to the control, although this deviation was non-significant.
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For the root cortex we examined the cortical cell file number and the area of living cortex tissue. We found that under both drought and waterlogging, roots had a lower cortical cell file number across all root segments than control plants (13 vs. 16, respectively). This was particularly evident 5–7 cm from the root tip, where both drought and waterlogging caused a significant reduction in cortical cell file number relative to the control (Figures 4 and 5B). After normalizing the cortical cell file number by the cortex thickness, we found no significant difference between treatments (ANOVA; “Treatment” p = 0.60, F4,48 = 0.69). This indicates that the reduction in cortical cell files observed was primarily a result of a reduction in root size rather than a change in the size of cortical cell files (Cell files μm−1; Figure S3), although this measure assumes cortical cells across cell files change in equal proportions. In addition to fewer cortical cell files in the cortex, we observed the living cortical area (i.e., the area of the cortex made up of living cells) decreased in our most extreme water stress treatments (Figure 5C). Both drought and 72 h of waterlogging caused a significant reduction in living cortical area, but in different root segments (Figure 3A,D). Drought impacted the living cortical area most strongly 3 cm from the root tip while the 72-h waterlogging showed the largest impact at 5 cm from the root tip. In both cases the decreased living cortical area was due to an increase in aerenchyma tissue in the cortex.
Stele Anatomy Under Drought and Waterlogging
The stele contains the vascular tissue of the root and is an important conduit for both water and solute transport between roots and shoots. Stressed plants exhibited a higher metaxylem:stele ratio (ANOVA; “Treatment” p = 0.08, F4,51 = 2.20), with this effect particularly pronounced in waterlogged plants (Figure 6A). The number of metaxylem vessels was also reduced in stressed plants by ~1 to 1.5 vessels per plant (ANOVA; ‘Treatment’ p = 0.61, F4,51 = 0.61). Plants that were waterlogged for 72 h had the largest vessel areas (1977 μm2, SE = 187), suggesting a strategy of producing fewer but larger metaxylem vessels (Figure 6B,C). In contrast, drought-stressed plants had similar vessel counts to those waterlogged for 72 h but exhibited the smallest vessel areas (1429 μm2, SE = 181).
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We observed a pattern in the ratio between the stele and root area where, at either end of the water stress extreme (drought vs. 72-h waterlogging), the portion of the root composing the stele was either reduced or enlarged (Figure 4A,D). To examine our two most extreme treatments (drought and 72-h waterlogging) in greater detail, we removed the less intense waterlogging durations. We found a significant interactive effect (p = 0.02, F14,157 = 2.01), with the water stress treatments impacting different portions of the root (Figure 7). However, post hoc comparisons did not reveal any statistically significant pairwise segment by treatment comparisons. At the tip of the root, droughted plants showed a reduced stele size in relation to the root size (Drought vs. control; p = 0.26, d = −1.38) while the control and waterlogged treatments were equivalent (14.5% of the root area vs. 16.5% and 16.3% for control and waterlogging, respectively). The opposite was the case for the segment furthest from the root tip, where the waterlogged treatment showed a reduction in stele size (Drought vs. control; p = 0.42, d = −1.23; 1.8%–2.3% reduction from control and drought treatments, respectively).
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Discussion
Despite all that is known about root anatomical responses to stress, a lack of resolution along the root for where different phenotypic responses are the strongest hinders integration with other data types where sampling effort is limiting (e.g., microbiome, transcriptome, proteome). Integrative approaches such as these typically utilize tens to hundreds of plants per experiment, creating a considerable barrier, as root anatomical measurements require considerable time to acquire. Here, we detail for
Commonalities exist in root anatomical traits at water stress extremes. While reduced cortical cell file number has been observed previously for Poaceae under drought stress (Fraser et al. 1990; Chimungu et al. 2014a; Colombi et al. 2019; Schneider et al. 2020), we observed this same phenomenon not only in droughted roots but also in waterlogged roots (Figure 5B). The reduction in cortical cell file number occurred consistently around 5–7 cm from the root tip and was evident after just 24 h of waterlogging, though more variable in intermediate treatments. This indicates a more general stress response, whereby plants suppress root enlargement by reducing cortical cell file addition under water stress. A reduced cortical cell file number and increased cortical cell diameter have been correlated with reduced energy costs for roots in wheat (Colombi et al. 2019). Maize genotypes with reduced cortical cell file numbers and larger cortical cell sizes also exhibited improved yields under water limitation in field settings (Chimungu et al. 2014a, 2014b). Cortical aerenchyma formation also showed a common response between water stress extremes in
Other traits, however, showed contrasting responses to the water stress extremes. For instance, droughted plants—but not waterlogged plants—had significantly more root hairs in the first 1–2 cm of the root. This is in line with previous research on drought stress in plants (Mackay and Barber 1985; Carminati et al. 2017; Marin et al. 2021), with a hypothesized role for root hairs in water uptake, although this is dependent on both soil texture and species (Cai et al. 2021; Duddek et al. 2022). In contrast, root hair density of waterlogged plants was similar to that of control plants. We note that although we were able to count root hairs in most cross-sections, some images presented difficulty due to lack of focus at the periphery of the root endodermis and occlusion in samples with copious root hairs, both of which made exact enumeration challenging. In these cases, we enumerated them as well as possible. Droughted plants tended to have the most occluded root hairs due to high densities in certain segments. It would be preferable in future experiments to measure root hair density by imaging the root section longitudinally, either prior to cross sectioning or on another suitable root, to allow for a greater area to be measured. Given that our results match what has been observed in other species, however, we believe this methodological issue does not invalidate our data.
Moving past the epidermis and cortex, we found that vascular structures were less impacted by the water stress treatments. While the number of metaxylem vessels was reduced to a similar extent across treatments, droughted roots tended to exhibit smaller vessel areas in comparison to the most extreme waterlogging treatment. Plasticity in metaxylem vessel diameter is associated with increased performance under drought stress as narrower vessels are better able to conduct water under as soils dry and water potential becomes increasingly negative (Richards and Passioura 1989; Vasellati et al. 2001; Kadam et al. 2015; Prince et al. 2017). In monocots, metaxylem of the seminal roots with smaller diameters have been found to be less susceptible to cavitation (Klein et al. 2020; Harrison Day et al. 2023). Compared to drought stress, less is known about the response of metaxylem vessels to waterlogging. We found that roots that experienced the longest duration of waterlogging had an increase in the ratio of metaxylem to stele area and tended to have largest metaxylem vessels, but this contrasts with other studies that have found an opposite pattern or no effect of waterlogging on metaxylem vessel size in other species (Huang et al. 1994; Vasellati et al. 2001). It should be noted that statistical support was not as strong for metaxylem mean area and number as metaxylem:stele ratio. It is likely that our sample size was too small to provide statistical confirmation. In the future, expanded sampling of metaxylem vessel area could aim for higher replication by focusing on a single, consistent segment of the root, given that most of the variance in this trait was attributable to differences among plants.
In this study, we chose to examine nodal roots, which, although not the only root type in
Stress-induced differences in RER may partly explain why anatomical changes were restricted to specific segments of the root. If control plants elongate at a normal rate while water stress plants elongate more slowly, then a given root segment is likely younger in the control plants than in the stressed plants. For example, we observed a decrease in living cortical percentage (corresponding to an increase in root cortical aerenchyma) across the length of the root that plateaued at ~7–8 cm segment for all groups. However, the greatest reductions were located 3–5 cm from the root tip for water stress treatments which could result from an increased developmental age allowing for more lysigenous aerenchyma formation via programmed cell death (Drew et al. 2000; Yamauchi and Nakazono 2022). For other traits, we would expect RER to provide less explanatory power, notably traits whose development finished close to the root apical meristem. For instance, cortical cell file number was consistently reduced in plants subjected to all water stress treatments; we observed significant deviations from the control in most treatments at the 5–7 cm segment, but the trend of reduced cortical cell files is evident even within the first centimeter from the root tip. This is consistent with the fact that cortical cell files are generated through asymmetric periclinal divisions in the root apical meristem (Dolan et al. 1993; Baum et al. 2002; Coudert et al. 2010), and thus changes in their number should be reflected along the entire length of the root. However, given the conflicting results in terms of the number of roots 8 cm and greater in length for the control treatment (Figure S1), measurement of the RER of
Finally, we highlight the relevance of our results to future integrative studies in root biology, particularly those involving the root microbiome. Internal and external root phenotypes define the habitats available to potential root-colonizing microorganisms. Therefore, stress-induced changes in root anatomy can have large implications for interactions that take place at the microscopic level between plants and microorganisms, which in turn can have profound effects on plant responses to abiotic stressors (Xu et al. 2018a; Durán et al. 2018; Rolfe et al. 2019) including in
Author Contributions
J.F.S. and M.R.W. designed the experiment. J.F.S. performed experimental treatments and root harvesting. J.F.S., D.T., L.B., and S.A. performed root sectioning and image analysis. J.F.S. analyzed data. J.F.S. wrote the first draft of the manuscript, which all authors read, commented on, and edited.
Acknowledgments
We would like to thank Natalie Ford and Martel Ellis for assistance planting and caring for Tripsacum. This work was funded by the National Science Foundation. D.T. was funded as part of a research experience for undergraduates' internship made possible by an NSF Biology Integration Institute grant #2120153, and J.F.S. was funded by a postdoctoral research fellowship #2305703. M.R.W. was supported by NSF grant IOS-2016351.
Conflicts of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Data Availability Statement
Anatomical measurements and code to reproduce the analysis and figures are available on GitHub at . Light microscopy images of
Peer Review
The peer review history for this article is available in the Supporting Information for this article.
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Abstract
ABSTRACT
Plant roots are the critical interface between plants, soil, and microorganisms, and respond dynamically to changes in water availability. Although anatomical adaptations of roots to water stress (e.g., the formation of root cortical aerenchyma) are well documented, it remains unclear whether these responses manifest along the length of individual roots under both water deficiency and water overabundance. We investigated the anatomical responses of
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1 Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, USA, Kansas Biological Survey & Center for Ecological Research, University of Kansas, Lawrence, Kansas, USA
2 Department of Biology, Washburn University, Topeka, Kansas, USA
3 Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, Kansas, USA