| Literature DB >> 29922245 |
Jesús Mercado-Blanco1, Isabel Abrantes2, Anna Barra Caracciolo3, Annamaria Bevivino4, Aurelio Ciancio5, Paola Grenni3, Katarzyna Hrynkiewicz6, László Kredics7, Diogo N Proença8.
Abstract
Trees are crucial for sustaining life on our planet. Forests and land devoted to tree crops do not only supply essential edible products to humans and animals, but also additional goods such as paper or wood. They also prevent soil erosion, support microbial, animal, and plant biodiversity, play key roles in nutrient and water cycling processes, and mitigate the effects of climate change acting as carbon dioxide sinks. Hence, the health of forests and tree cropping systems is of particular significance. In particular, soil/rhizosphere/root-associated microbial communities (known as microbiota) are decisive to sustain the fitness, development, and productivity of trees. These benefits rely on processes aiming to enhance nutrient assimilation efficiency (plant growth promotion) and/or to protect against a number of (a)biotic constraints. Moreover, specific members of the microbial communities associated with perennial tree crops interact with soil invertebrate food webs, underpinning many density regulation mechanisms. This review discusses belowground microbiota interactions influencing the growth of tree crops. The study of tree-(micro)organism interactions taking place at the belowground level is crucial to understand how they contribute to processes like carbon sequestration, regulation of ecosystem functioning, and nutrient cycling. A comprehensive understanding of the relationship between roots and their associate microbiota can also facilitate the design of novel sustainable approaches for the benefit of these relevant agro-ecosystems. Here, we summarize the methodological approaches to unravel the composition and function of belowground microbiota, the factors influencing their interaction with tree crops, their benefits and harms, with a focus on representative examples of Biological Control Agents (BCA) used against relevant biotic constraints of tree crops. Finally, we add some concluding remarks and suggest future perspectives concerning the microbiota-assisted management strategies to sustain tree crops.Entities:
Keywords: belowground microbiota; biological control agents; endophytes; mycorrhiza; phytoparasitic nematodes; plant-growth-promoting microorganisms; soil-borne pathogens; tree crops
Year: 2018 PMID: 29922245 PMCID: PMC5996133 DOI: 10.3389/fmicb.2018.01006
Source DB: PubMed Journal: Front Microbiol ISSN: 1664-302X Impact factor: 5.640
Figure 1Total world surface (triangles) and yield/hectar (solid squares) of main tree crops (citrus, fresh and tropical, pome and stone fruits) (source FAOSTAT: .
Figure 2A simplified food web describing main soil components and their relationships. The nodes are classified by roles as: primary root (dark green), beneficial soil components, organisms or promoters, including soil factors (blue), decomposers (brown), pathogens (orange) and biocontrol agents or antagonists (pale green). Arrows show negative effects (A), such as predation, parasitism, pathogenicity or (B) positive links, such as growth promotion, symbiosis or alimentary provision. Indirect factors such as those related to abundance, competition or other density-dependent effects are not included. Node labels and sizes are proportional to their connection level (number of edges). Analysis produced with Gephi (Bastian et al., 2009).
Methods to study belowground microbial communities.
| Growth on culture media, Enrichment cultures, | Microorganism isolation, pest control purposes, etc.; fast and low cost | Useful exclusively for cultivable microorganisms | Maritime pine ( | Islam and Ohga, |
| Enzymatic measurements | Functional activity; soil quality bioindicators; early indication of changes in soil; ecosystem disturbance estimate | Not necessarily linked to real ecological functioning and activity | Poplar ( | Winding et al., |
| Community level physiological profiling (CLPP), sole-carbon-source utilization (e.g., API and BIOLOG) | Versatile for bacteria, fungi and specific carbon sources (BIOLOG); fast, highly reproducible and relatively inexpensive | It reflects potential metabolic diversity of fast growing microorganisms and not of overall | Grapevine ( | Söderberg et al., |
| Phospholipid fatty-acid analysis (PLFA)/Total Ester-linked Fatty Acid (ELFA)/Fatty acid methyl ester (FAME) analysis | Indicator of active microbial biomass opposed to non-living biomass; fingerprint of overall microbial communities (Bacteria, Archaea, Fungi) | Limited number of microbial groups identified | Diverse | Hill et al., |
| Fluorescent | Direct identification and visualization of microbial groups based on the hybridization with a high number copies of their rRNA; it reflects microbial activity and makes it possible to quantify cell number; DNA extraction from soil is not required | Cells with low activity are not identified; it requires skill and experience in the case of low probe penetration and autofluorescence; information obtained is dependent on the availability of designed probe(s) | Hill et al., | |
| Total microbial abundance (DAPI counts); cell viability | Detection of all microbial cells independently from their physiological state | Overestimation of cell number if they are just dead but with an intact DNA | Poplar, rosemary | Barra Caracciolo et al., |
| Sensitive to variation in DNA sequences; | Multiple bands for a single species can be generated due to micro-heterogeneity: can be used only for short fragments; | Hill et al., | ||
| qPCR, RT-qPCR, dPCR | Quantitative and highly sensitive for species identification and functional genes; easy to implement and cheap; specific amplification confirmed by melting curve analysis | Can only be used for targeting of known DNA sequences; DNA impurities and artifacts may lead to false-positives or inhibit amplification | Poplar, switchgrass ( | Liang et al., |
| Next-generation sequencing (NGS) | Rapid to assess biodiversity and abundance of many species/organizational taxonomic units simultaneously | Massive amount of sequencing data of DNA (genomic or PCR amplified fragments) or RNA error distribution within reads of a library; | Maritime pine ( | Proença et al., |
| DNA sequence analysis of the internal transcribed spacer (ITS) region for mycorrhizal studies | Fast and accurate for the identification of mycorrhizal fungi and characterization of their distribution. | Relatively expensive, especially in case of metagenomic analyses | Ectomycorrhizas of poplar ( | Hrynkiewicz et al., |
A few illustrative examples of herbaceous plants are also given.
Figure 3Summary of the benefits that belowground microbiota (or some of their components) may confer to tree crops.
Figure 4Chlamydospores of the nematode parasitic and root endophytic hyphomycete Pochonia chlamydosporia showing their persistent cellular structure (A). Hyphae emerging from killed root-knot nematode eggs, in vitro (B). The aquatic fungus Catenaria anguillulae (C) is one of the most common parasites of nematodes (in the picture inside Xiphinema sp.) killing its hosts in a few hours. However, in spite of its ubiquity and polyphagy, and due to the zoospores dependence on water for host attachment, a persistent regulation of phytoparasitic nematodes is seldom observed.
Examples for the most relevant microorganisms affecting tree crops as soil-borne pathogens.
| Various fruit trees | Crown gall disease (tumor formation) | Hwang et al., | |
| Various fruit and nut crops, forest trees | Various diseases including stem, root and/or collar rot, ink disease, dieback | see Supplementary Table | |
| Tropical tree species | Damping off of seedlings | Augspurger and Wilkinson, | |
| Apple ( | Apple replant disease | Tewoldemedhin et al., | |
| Rubber tree ( | Patch canker | Zeng et al., | |
| Root rot | Weber et al., | ||
| Various | Douglas fir | Damping off of seedlings | Weiland et al., |
| Cork tree ( | Vascular wilt disease | Berlanger and Powelson, | |
| Passion fruit ( | Vascular wilt disease | Ploetz, | |
| Apple, apricot ( | White rot | Pérez-Jiménez, | |
| Elm | Dutch elm disease | D'Arcy, | |
| Chestnut ( | Chestnut blight | Anagnostakis, | |
| Conifers, fruit, and nut trees | Root disease | Baumgartner et al., | |
| Conifers | Root damage and damping-off of seedlings | Mazzola, | |
| Apple | Root rot | Mazzola, | |
| Conifers | Root and butt rot disease | Asiegbu et al., | |
Figure 5A strategy to manage biotic constraints affecting tree crops (i.e., pathogens, pests, invasive species) based on the identification, characterisation and harnessing of soil/root microbiota [based on a conceptual framework by Kowalski et al. (2015)].