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9.2: Soil-Plant Interactions - Biology

9.2: Soil-Plant Interactions - Biology



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Soil plays a key role in plant growth. Beneficial aspects to plants include providing physical support, water, heat, nutrients, and oxygen (Figure (PageIndex{1})). Mineral nutrients from the soil can dissolve in water and then become available to plants. Although many aspects of soil are beneficial to plants, excessively high levels of trace metals (either naturally occurring or anthropogenically added) or applied herbicides can be toxic to some plants.

The ratio of solids/water/air in soil is also critically important to plants for proper oxygenation levels and water availability. Too much porosity with air space, such as in sandy or gravelly soils, can lead to less available water to plants, especially during dry seasons when the water table is low. Too much water, in poorly drained regions, can lead to anoxic conditions in the soil, which may be toxic to some plants.

Nutrient Uptake by Plants

Several elements obtained from soil are considered essential for plant growth. Macronutrients, including C, H, O, N, P, K, Ca, Mg, and S, are needed by plants in significant quantities. C, H, and O are mainly obtained from the atmosphere or from rainwater. These three elements are the main components of most organic compounds, such as proteins, lipids, carbohydrates, and nucleic acids. The other six elements (N, P, K, Ca, Mg, and S) are obtained by plant roots from the soil and are variously used for protein synthesis, chlorophyll synthesis, energy transfer, cell division, enzyme reactions, and homeostasis (the process regulating the conditions within an organism).

Micronutrients are essential elements that are needed only in small quantities, but can still be limiting to plant growth since these nutrients are not so abundant in nature. Micronutrients include iron (Fe), manganese (Mn), boron (B), molybdenum (Mo), chlorine (Cl), zinc (Zn), and copper (Cu). There are some other elements that tend to aid plant growth but are not absolutely essential.

Micronutrients and macronutrients are desirable in particular concentrations and can be detrimental to plant growth when concentrations in soil solution are either too low (limiting) or too high (toxicity). Mineral nutrients are useful to plants only if they are in an extractable form in soil solutions, such as a dissolved ion rather than in solid mineral. Many nutrients move through the soil and into the root system as a result of concentration gradients, moving by diffusion from high to low concentrations. However, some nutrients are selectively absorbed by the root membranes, enabling concentrations to become higher inside the plant than in the soil.


9.2: Soil-Plant Interactions - Biology

Email: [email protected]
Website: https://biologicalsciences.leeds.ac.uk/school-of-biology/staff/403/tom-thirkell
Expertise: Barley, Field trials, Isotope tracing, Metabolomics, Microscopy, Molecular breeding, Wheat
Research Areas: Agri-ecosystems, Climate, Physiology- eco, Physiology- crop, Root microbiome, Root mycorrhiza, Soil carbon, Soil microbiome, Soil plant interactions, Symbiosis


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9.2: Soil-Plant Interactions - Biology

An International Journal on Plant-Soil Relationships

Plant and Soil publishes original papers and review articles exploring the interface of plant biology and soil sciences, and that enhance our mechanistic understanding of plant-soil interactions. This includes both fundamental and applied aspects of mineral nutrition, plant-water relations, symbiotic and pathogenic plant-microbe interactions, root anatomy and morphology, soil biology, ecology, agrochemistry and agrophysics. Articles discussing a major molecular or mathematical component also fall within the scope of the journal. All contributions appear in the English language.

The Editor-in-Chief is Hans Lambers, University of Western Australia, Crawley, Australia.

Why publish with us

  • We explore the interface of plant biology and soil sciences .
  • We provide high levels of author satisfaction , with 96% of our published authors reporting that they would definitely or probably publish with us again .
  • Through Springer Compact agreements , authors from participating institutions can publish Open Choice at no cost to the authors .

Microplastics in soil-plant system: effects of nano/microplastics on plant photosynthesis, rhizosphere microbes and soil properties in soil with different residues

To investigate the effects of polystyrene microplastics (PS-beads) on the soil properties, photosynthesis of Flowering Chinese cabbage, the rhizosphere microbial community and their potential correlation in soil with different residues.

Methods

The influences of PS-beads (PS-MPs, M1, 5 μm PS-NPs, M2, 70 nm) on the plant photosynthesis and growth parameters, soil dissolved organic matter (DOM) and the characteristic functional groups, the microbial community and metabolism prediction were studied by a pot-experiment in soil without residues (N), with biochar (B), degradable mulching film (DMF) fragments (D), or biochar and DMF (BD).

Key results

Chlorophyll a was more susceptible to the exogenous substances than Chlorophyll b. In soil with different residues, PS-beads of different sizes could change different components, structures and functional groups in aromatic rings of DOM, might further change the microbial community and metabolism. M2 decreased TDN and NO3 − and increased the weight of the plant in group D. M2 increased the weight of the plant in group N. M2 decreased the net photosynthetic rate in group B. The different sizes of PS-beads affected the different parameters of plant growth and potentially changed the plant growth and photosynthetic parameters through altering the microbial metabolism and the correlation among microbes. The potential mechanisms of PS-beads changing the plant growth were different in soil with different residues.

Conclusions

Our results evidenced the PS-beads potentially changed the plant growth and photosynthesis by changing the microbial metabolism and the correlation among microbes.


Soil & Plant Science Classroom Investigations

We describe two classroom experiments that were codeveloped by K–12 educators and university researchers and conducted in classroom settings. The data shown here were collected by students. Prior to conducting the experiments, provide students with an introduction to biochar and its application in soils and agriculture. Ask students to observe biochar and different soil types under a microscope and discuss differences in properties such as porosity (Figure 1) and pH ( Appendix 1). Discuss how different properties of the biochar and soil they observed might influence plant growth and soil respiration.

Experiment 1: Plant Growth

Biochar is typically added to agricultural soils, and scientists are interested in how biochar will affect crop productivity. Here, students conduct an analogous experiment in which they ask the question “How does biochar affect plant growth in different soil types?” Prompt students to make a prediction about whether biochar will increase, decrease, or have no effect on plant growth and to explain their ideas about why ( Appendix 2). Ask them to list the dependent variables they would measure in order to answer this question ( Appendix 2). Variables may include plant height, plant biomass, stem diameter, and number of leaves, among others. Scientists typically assess crop productivity by measuring plant height and aboveground (shoot) and belowground (root) biomass, and compare the amount of biomass plants have allocated to roots in relation to total plant biomass (root mass ratio). Students could measure plant height and aboveground and belowground biomass, and other variables that emerge from your classroom discussions.

Supplies

Pots with holes at the bottom (3 in 2 [7.6 cm 2 ] recommended)

Commercial potting soil (fill to 80% volume of the pot)

Topsoil (collected locally fill to 80% volume of the pot)

Sand (fill to 80% volume of the pot)

Camera to document growth

Experimental Design & Protocols

The experiment is a comparative manipulative study with three soil types (potting soil, topsoil, and sand) and two biochar amendments (no biochar [control] and 10% biochar). Prior to the experiment, germinate the mung bean seeds by placing them between two damp paper towels for 24 hours. Prepare half the soil for biochar amendment by mixing in 10% biochar by volume this is a concentration that is typically used in laboratory experiments and agricultural fields (Biederman & Harpole, 2013). Leave the other half of the soil unamended as the control. Clearly label the pots with soils with the appropriate six experimental treatments (potting soil control potting soil biochar topsoil control topsoil biochar sand control sand biochar). Place germinated seeds on the soil surface and cover with 3–5 mm of soil. Place the potted plants under fluorescent grow lights (13–50 watt bulbs) and maintain them at room temperature. Each experimental treatment should be replicated at least three times to make it possible to investigate variability by calculating means and standard deviations. If necessary, use pipe cleaners or other wires to help keep plants upright during the experiment. Add more water immediately after planting and as needed.

Teacher Considerations

We grew fast-growing and easy-to-maintain mung beans in natural topsoil, commercial potting soil, and sand, but other plant species and soil types could be used. Have students work in groups to maintain one replicate of a soil type and biochar treatment combination (e.g., potting soil control and potting soil biochar).

Student Activities

Plant growth. Prepare and label each pot with the appropriate experimental treatment for your group as described above. Record the date of planting and the date that the plants break through the soil surface. After each watering, record visual observations about the plant. On day 7, select the tallest plant and measure the height (cm) with a ruler. Place a toothpick near your selected plant to mark which plant you will measure each week and record the height of this plant after each watering ( Appendix 3). Take a photo of your plants each week. Plants are delicate and must be handled carefully each time you measure them to prevent them from breaking.

Plant biomass harvest. After at least three weeks, take a final height measurement and then harvest plant biomass (Figure 4). Gently remove the plants and soil from the pot. Using forceps and a small paintbrush, carefully remove soil from the roots. You can rinse the roots with water to remove remaining soil. Separate the roots (belowground biomass) from the stems and leaves (aboveground biomass). Place the plant material into foil labeled with the experimental treatment and aboveground or belowground biomass. Fold the aluminum foil to minimize losses during transport. Dry the plant material in an oven at 60°C for at least 24 hours. You can leave the plant material in the oven over the weekend for up to 72 hours. Weigh dried biomass and record ( Appendix 3).

Example of aboveground and belowground biomass harvest from sand (control) and sand + biochar treatments for the classroom plant growth experiment. Aboveground biomass (shoots) and belowground biomass (roots) are separated, dried, and weighed. (Credit: photo by M. Hunter-Laszlo)

Example of aboveground and belowground biomass harvest from sand (control) and sand + biochar treatments for the classroom plant growth experiment. Aboveground biomass (shoots) and belowground biomass (roots) are separated, dried, and weighed. (Credit: photo by M. Hunter-Laszlo)

Soil pH. Students can also investigate the impact of biochar on soil pH as an indicator of the chemical and biological environment of the soil ( Appendix 1). Soil pH is considered the “master variable” in determining which soil organisms are present in the soil and how they function (Fierer & Jackson, 2006 Wu et al., 2011). Protocols for measuring soil pH are detailed in Appendix 1.

Data analysis. Students can graph plant growth over time using plant height data from each treatment over the experimental period (Figure 5). Plant biomass data can be plotted in a bar graph as shown in Figure 6. Students can then clearly see the differences between aboveground and belowground biomass production. Notice that belowground responses do not necessarily mimic aboveground responses to the same treatment. Plant and soil scientists commonly represent these data as ratios. Students can calculate and graph root mass ratios from their biomass data by dividing root biomass by the total plant biomass ( Appendix 3 and Figure 7). Students can also calculate means and standard deviations and add these to the graphs (Figures 5, 6, and 7).

Plant height data collected by students during plant growth experiment. Points represent means. Error bars represent one standard deviation from the mean. Numbers in legend are number of replicates within each treatment.

Plant height data collected by students during plant growth experiment. Points represent means. Error bars represent one standard deviation from the mean. Numbers in legend are number of replicates within each treatment.

Aboveground (A) and belowground (B) biomass data collected by students during plant growth experiment. Bars represent means. Error bars represent one standard deviation from the mean. Sample sizes shown above bars are number of plant replicates in each treatment.

Aboveground (A) and belowground (B) biomass data collected by students during plant growth experiment. Bars represent means. Error bars represent one standard deviation from the mean. Sample sizes shown above bars are number of plant replicates in each treatment.

Ratios of root mass to total plant biomass from data collected by students during plant growth experiment. Bars represent means. Error bars represent one standard deviation from the mean. Sample sizes shown above bars are number of plant replicates in each treatment.

Ratios of root mass to total plant biomass from data collected by students during plant growth experiment. Bars represent means. Error bars represent one standard deviation from the mean. Sample sizes shown above bars are number of plant replicates in each treatment.

Experiment 2: Soil Respiration

Students conduct an experiment in which they add biochar to soil and compost and measure the response of soil respiration. Students ask, “How does adding biochar to soil and compost affect soil respiration?” Based on their observations of biochar, prompt your students to predict whether biochar will increase, decrease, or not affect soil respiration and to explain their ideas about why before they begin the experiment. Soil microbes metabolize organic and inorganic compounds via extracellular enzymes, respire carbon dioxide (CO2), and excrete nitrogen as byproducts of growth and reproduction (Schimel & Bennett, 2004 Paul, 2014). Scientists measure the flux of CO2, or “soil respiration,” to assess microbial activity and rates of CO2 entering the atmosphere. Scientists are also interested in the nitrogen released by microbial activity because nitrogen is necessary for plant growth.

Supplies

Buckets for soil collection

50 mL graduated cylinders

CO2 probe, sensor, or gas detecion tube

Sample container (200 mL minimum)

Experimental Design & Protocols

We collected garden soil and compost, but other soil types may be used. Compost supports high microbial activity and respiration and serves as a useful comparison with natural soils. Use half of each soil type as the unamended control and prepare the other half with biochar amendment by adding 10% biochar by volume. Label the soil and compost with the four experimental treatments (compost control compost biochar garden soil control garden soil biochar) and leave them open to air for a day before taking measurements to allow soils and microbial communities to re-equilibrate after the disturbance of setup. Prepare the soil or compost sample by filling the sample container to the 150 mL mark with your assigned soil. Label the bottle with your group name, soil type (compost or garden soil), and experimental treatment (control or biochar). Using a graduated cylinder, moisten the soil with 20 mL of water. Set up the experiment away from windows to maintain stable temperature conditions (ideally around 25–30°C). Replicate each treatment at least three times to calculate means and standard deviations. Prepare the CO2 measurement instrument for data collection. For probes or sensors, allow the instrument to warm up until the readings begin to stabilize. Calibrate the sensor before setting up the experiment. Set up the data collection device to take a measurement every 1 minute for 24 hours (1440 measurements). Place the CO2 sensor in the sample container (Figure 8). For gas detection tubes, measure CO2 concentration at least three times: at the start, at 30 minutes, and at 24 hours. You can adjust intervals to fit your classroom and scheduling needs.


The effect of the host on the plant microbiome

The interactions between a plant and its microbiome are highly complex and dynamic. The plant immune system (Box 1) in particular is thought to have a key role in determining plant microbiome structure. Mutants of A. thaliana deficient in systemic acquired resistance (SAR) have shown differences in rhizosphere bacterial community composition compared with wild type [81], whereas chemical activation of SAR did not result in significant shifts in the rhizosphere bacterial community [82]. In the phyllosphere of A. thaliana, induction of salicylic-acid-mediated defense reduced the diversity of endophytes, whereas plants deficient in jasmonate-mediated defense showed higher epiphytic diversity [83]. These reports suggest that the effects of plant defense processes on the microbiome are variable and that SAR is responsible for controlling the populations of some bacteria.

Production of plant hormones such as indole-3-acetic acid (IAA) is widespread among plant-associated bacteria, particularly the rhizobia [84], and some Bacillus spp. can produce gibberellins [85]. Pseudomonas syringae produces hormone analogs that interfere with jasmonate and ethylene signaling, resulting in stomatal opening and pathogen entry [86]. Degradation of hormones or hormone precursors by bacteria is also documented. For example, microbial deamination of ACC prevents plant ethylene signaling, resulting in plants more tolerant to environmental stress [87].

Although some chemical signals released by plants facilitate specific interactions, many are recognized by other organisms. For example, flavonoids trigger diverse responses in rhizobia, mycorrhiza, root pathogens and other plants [88]. Strigolactones induce hyphal branching in mycorrhizal fungi and promote seed germination of parasitic plants [89]. Some plant genes and pathways have roles in establishment of multiple interactions with different microbes examples include the developmental pathways that are shared between mycorrhizal and rhizobial symbioses [90], the mycorrhizal symbiosis and infection by oomycetes [91] and the rhizobial symbiosis and infection by nematodes [92]. It is not yet known whether and how these pathways interact with other members of the microbiome.

Plants produce a wide variety of antimicrobial compounds both constitutively and in response to pathogens [93]. Phenolics, terpenoids and alkaloids are widespread in the plant kingdom, whereas others are restricted to particular groups [94] glucosinolates, for example, are produced only by members of the order Brassicales. Arabidopsis produces glucosinolates naturally, but transgenic Arabidopsis producing an exogenous glucosinolate altered the bacterial and fungal communities in the rhizosphere and root tissue [95]. Oat (Avena strigosa) produces triterpenoid saponins known as avenacins, which have broad-spectrum antifungal activity [96]. Oat mutants lacking avenacins have different culturable communities of root-colonizing fungi [97] and are more susceptible to fungal pathogens than isogenic wild-type oat [98, 99]. Surprisingly, however, a recent global analysis of the rhizosphere microbiome of these two genotypes found little difference between the fungal communities. The eukaryotic Amoebozoa and Alveolata were strongly affected by the lack of avenacins in the mutant, whereas bacterial communities were unaffected [29]. This highlights that a small change in plant genotype can have complex and unforeseen effects on the plant microbiome. Other studies have not found any significant differences in rhizosphere microbiomes between wild-type maize and maize genetically engineered to produce Bacillus thuringiensis (Bt) toxin [100, 101], although this may be due to Bt toxin being insecticidal rather than antibacterial. Also, in the wheat rhizosphere, introduction of the pm3b gene conferring resistance to mildew had minimal effect on pseudomonads and mycorrhizal fungi populations [102]. Disease resistance, including production of antimicrobial compounds, is a trait likely to be introduced as a result of molecular breeding or genetic modification in attempts to control diseases. These may or may not affect resident members of the microbiome, potentially with unforeseen effects on the plant, and should be assessed on an individual basis. This is particularly important given that the products of disease resistance genes are often unknown.


Adaptations to dry habitats [back to top]

Plants in different habitats are adapted to cope with different problems of water availability.

Mesophytes plants adapted to a habitat with adequate water

Xerophytes plants adapted to a dry habitat

Halophytes plants adapted to a salty habitat

Hydrophytes plants adapted to a freshwater habitat

Some adaptations of xerophytes are:

stops uncontrolled evaporation through leaf cells

less area for evaporation

conifer needles, cactus spines

stomata on lower surface of leaf only

more humid air on lower surface, so less evaporation

shedding leaves in dry/cold season

reduce water loss at certain times of year

maintains humid air around stomata

maintains humid air around stomata

maintains humid air around stomata


Background

The ecological outcomes of interactions between two species, such as mutualism and parasitism, often vary spatially among the different abiotic and biotic contexts in which those interactions occur the result of this spatial variation in ecological dynamics is that the pattern of natural selection that species exert on each others' traits will vary among populations, that is, there will be a geographic 'selection mosaic' [1, 2]. In addition, selection by species on each other may be strongly reciprocal in some populations, generating coevolutionary hotspots, and not in others, producing coevolutionary coldspots [3, 4]. Finally, the processes of migration and gene flow among populations and genetic drift within populations may vary over space and time, influencing the distributions of species traits in each population [5–7]. Together, these processes result in a geographic mosaic of coevolution, which acts to generate and maintain much of the genetic and ecological diversity within and among populations of species [1, 2].

Selection mosaics in species interactions result from geographic differences in how the fitness of one species depends on the distribution of genotypes in another species. Such geographic variation in selection can be driven by variation in both abiotic environmental factors, such as the nutrient content or physical composition of soils, and biotic factors, such as the species composition of the surrounding ecological community. Thus, a selection mosaic can be defined as a genotype-by-genotype-by-environment interaction (G × G × E) on fitness, in which variation in the 'environment' (E) can be abiotic or biotic [2, 8, 9]. Selection mosaics have now been suggested or characterized in a variety of different species interactions, including pines and birds [10], ants and wild cotton [11], camellias and weevils [12], and wild parsnips and parsnip webworms [13]. Most studies, however, have not been able to control for genotypes of the interacting species across environments to assess the strength of the G × G × E interaction.

Interactions between plants and mycorrhizal fungi have high potential to exhibit selection mosaics. Mycorrhizal fungi form a relationship with plants by colonizing the plant root system and extending their hyphae into the surrounding soil. Classically, this interaction has been considered a mutualism whereby fungal colonization greatly increases plant access to mineral nutrients in the soil, and the fungus receives organic nutrients synthesized by the plant [14, 15]. In recent years, however, it has become evident that the ecological outcomes of plant-mycorrhizal fungus interactions are highly variable, ranging from mutualism to parasitism depending on a variety of biotic and abiotic environmental factors, especially ambient soil nutrient availability [16, 17]. If environmental factors interact with plant and/or fungal genetics to change the outcome of plant-mycorrhizal interactions among populations, then selection mosaics could emerge as a consequence, driving the evolution of diversification in these interactions. Although the effects of individual biotic and abiotic factors on plant-mycorrhizal interactions have been fairly well characterized [15], it is currently not known whether these interactions, which are so pervasive in terrestrial ecosystems, exhibit evidence of selection mosaics. That question, however, is becoming important for our understanding of rapid evolution in terrestrial ecosystems as environmental conditions in many ecosystems are changing quickly and plants and their mycorrhizal fungi are being transported between continents [18].

In the work reported here, our goal was to explore the potential for selection mosaics in the interactions between bishop pine seedlings (Pinus muricata D. Don) and an ectomycorrhizal fungus (Rhizopogon occidentalis Zeller and Dodge) by experimentally varying lineages of the plant and fungus, as well as one biotic environmental factor (non-mycorrhizal soil microbes) and one abiotic environmental factor (soil composition), and measuring the variability in the performance of the plant and fungus. Non-mycorrhizal soil microbial communities may have a substantial impact on the colonization of roots by mycorrhizal fungi, and may alter the effects that mycorrhizal fungi have on plant growth [19]. For example, recent work has suggested that 'mycorrhizal helper bacteria' are present in soil, and that they are important for the success of the plant-fungus interaction [15, 20, 21]. Alternatively, rhizosphere bacteria may act to decrease the benefits conveyed by mycorrhizal fungi on plant growth [22]. Physical soil structure and composition may also have substantial impacts on the plant-mycorrhizal interaction. For example, Chen et al. [23] found much faster growth and higher ectomycorrhizal colonization of Eucalyptus urophylla seedlings grown in a laboratory potting soil mix compared with various field soils.


Global analysis of protein-RNA interactions in SARS-CoV-2 infected cells reveals key regulators of infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19. SARS-CoV-2 relies on cellular RNA-binding proteins (RBPs) to replicate and spread, although which RBPs control SARS-CoV-2 infection remains largely unknown. Here, we employ a multi-omic approach to identify systematically and comprehensively which cellular and viral RBPs are involved in SARS-CoV-2 infection. We reveal that the cellular RNA-bound proteome is remodelled upon SARS-CoV-2 infection, having widespread effects on RNA metabolic pathways, non-canonical RBPs and antiviral factors. Moreover, we apply a new method to identify the proteins that directly interact with viral RNA, uncovering dozens of cellular RBPs and six viral proteins. Amongst them, several components of the tRNA ligase complex, which we show regulate SARS-CoV-2 infection. Furthermore, we discover that available drugs targeting host RBPs that interact with SARS-CoV-2 RNA inhibit infection. Collectively, our results uncover a new universe of host-virus interactions with potential for new antiviral therapies against COVID-19.


Watch the video: Plant. Soil Interactions (August 2022).