3.2. The “Top-Down” Approach
5.2. The “Top-Down” Approach
A “top-down” approach for investigating the diversity and complexity of the soil microbiome is to create low-complexity consortia
[33][86]. This method utilizes dilution and cultivation on complex carbon sources (e.g., N-acetylglucosamine and chitin). Dilution promotes a reduction in species richness of the community, and a stabilization of the consortia (after about 3–5 weeks of incubation) yields several microbial communities. However, the resulting consortia are still comparatively complex and contain up to several hundred species
[34][87]. By adopting such an approach, the community can independently shape the species composition of a consortium and enhance its growth through necessary interactions. It should be noted that the type of carbon source has an impact on the rate and direction of consortium development
[35][88]. The “top-down” approach involves identifying the community function to understand the community structure and dynamics.
The “top-down” approach outperforms a “bottom-up” approach in generating representative communities
[36][90]. Moreover, the larger community allows more soil functional potential and species interactions to be captured and studied. For example, applying the “top-down” approach resulted in 35 species being detected, with approximately 13 being the dominant ones compared to 2–3 dominant ones detected using the “bottom-up” approach
[34][87].
The “top-down” approach proves useful for studying relationships between key community properties, such as diversity, function, and stability, while also providing a mechanistic understanding of community structure
[37][89]. It is not unlikely that difficult-to-cultivate species can be studied exclusively using this approach due to their need for interaction with other members and their inability to exist independently without additional biochemical information
[29][76].
It is worth noting that employing the two approaches considered above has resulted in valuable discoveries in the plant microbiome
[35][88]. Combining the strengths of both approaches to study one model community can be highly effective. The “top-down” approach can reduce the soil microbiome to a more manageable size and identify interacting members.
3.3. Practical Applications of Synthetic/Artificial Microbial Communities
5.3. Practical Applications of Synthetic/Artificial Microbial Communities
Synthetic consortia are small consortia of microorganisms designed to mimic and analyze the microbiome function and structure in vivo. Such consortia represent a new frontier for synthetic biology as they allow more complex problems to be solved compared to monocultures.
The purpose of creating synthetic consortia is to reduce the complexity of the natural microbial community while preserving some of the original interactions between microbes and hosts, providing a repertoire of functions that cannot be achieved by a single microorganism
[38][39][40][91,92,93]. Creating synthetic microbial communities in the laboratory involves selecting certain microorganisms according to their ability to stimulate plant growth, protect plants from pathogen infestation, or provide nutrition to plants.
It has been suggested that microbial communities with increased metabolic activity should be modeled by selecting species that are not functionally too close or too distant
[41][95]. However, the universality of this hypothesis has yet to be confirmed experimentally. Strain selection is assumed to be based, among other things, on functional genes rather than on taxonomic classification
[42][96].
Three consortia were developed based on paired and triple interactions of phosphate-solubilizing bacteria for wheat inoculation, with the first consortium comprising
Enterobacter sp. and
Ochrobactrum sp., the second consortium comprising
Pantoea sp.,
Enterobacter sp., and
Ochrobactrum sp., and the third consortium comprising
Ochrobactrum sp.,
Pseudomonas sp., and
Bacillus sp. Rhizosphere analysis revealed a significant increase in linear root growth after inoculation with these consortia
A key factor in developing a microbial consortium, which is essential for the successful functioning of the included microorganisms, is the compatibility of the individual microorganisms. Bacteria of the genera Bacillus and Trichoderma were found to perform well both in consortia and in individual inoculation, and Pseudomonas was reported to perform better in synthetic consortia than when inoculated individually
[43][104]. These properties encountered when creating consortia are likely to be the clue to utilizing PGPB for agroecosystems. The potential contribution of individual microorganisms can be assessed by altering the composition of a synthetic community through the addition, removal, or replacement of microorganisms
[10].
3.4. Identification of Microbes with Key Characteristics
5.4. Identification of Microbes with Key Characteristics
Selecting microbes with important properties for agricultural applications mainly involves in vitro screening and sampling of well-known taxa or activities favorable to plant growth and development, such as atmospheric nitrogen fixation, phosphorus solubilization, phytohormone, and siderophore production
[44][45][26,27]. Unfortunately, inoculating plants with preparations of microorganisms obtained using these traditional approaches often fails to result in long-term stable interactions with plants under field conditions and subsequently in satisfactory results
[46][47][108,109]. For a strain to be considered successful, it must effectively compete with existing microorganisms in the soil, establish a strong presence in the plant root system, and form stable and sustainable associations, even in the face of potential changes in the environment and soil microbial composition throughout the growing season.
One strategy to overcome the challenges is to select microorganisms based on the diversity of plant microbiota. The analysis of 16S rRNA gene sequencing data has revealed that certain groups of soil bacteria can successfully colonize plant roots and establish and maintain permanent relationships with them, whatever the environmental changes or the plant developmental stages
[48][49][110,111]. Incorporating members of dominant groups referred to as the “core microbiome” into synthetic communities can mitigate the potential inefficiencies observed when strains are outcompeted by the natural soil microbiota.
3.5. Development and Stabilization of Microbial Communities
5.5. Development and Stabilization of Microbial Communities
Synthetic microbial communities can be stabilized in the short term, up to 36 h, and in the long term, up to two weeks
[48][50][110,115]. Given these data, consortia need to be given enough time to stabilize, e.g., several weeks, especially when using a “top-down” approach, before they can be maintained and revived.
Significant changes in the relative abundance of some taxa are observed during the first week of incubation in soil, followed by stabilization after two weeks
[34][87]. Stabilizing the soil microorganism community may require 3 to 5 weeks, with stability observed for several months afterward
[33][86]. Thus, when studying model consortia, it is worth considering the period required to achieve stability after inoculating the consortium into new soil.
4. Designing PGPB Consortia That Can Reduce the Response to Abiotic Stress
The design and creation of bacterial consortia is a non-trivial task that demands careful consideration. It is crucial to ensure the absence of antagonistic interactions among the members of the bacterial mixture to enable their coexistence. Moreover, bacteria selected for bacterial mixtures should be capable of enhancing plant growth, bioremediation, and tolerance of unfavorable conditions in crop fields.
Figure 24 summarizes the information on soil bacteria and their possible consortia that could favorably affect plant growth.
Figure 24.
Inoculation of plants with soil PGPB capable of reducing abiotic stress.
Food crop productivity is affected by various abiotic factors, such as salinity, drought, and temperature
[49][51][111,116]. Some functional features of rhizobacteria (biofilm formation, bioremediation, resistance to soil salinity, and low temperatures) have an impact on plant survival under unfavorable conditions
[52][53][117,118]. PGPR-based microbial strategies can be efficient in overcoming the negative effects of abiotic factors. Some bacteria are capable of forming a biofilm that can enhance resistance to antibiotics, heat, UV radiation, and other environmental stresses
[54][55][119,120]. When exposed to unfavorable conditions, soil bacteria secrete exopolysaccharides that form an organomineral envelope, also known as biofilm. These polysaccharides consist of complex mixtures of high-molecular-weight polymers (MW ≥ 10,000)
[56][121].
It is common for bacteria to produce exopolysaccharides under conditions of heavy metal stress and high salinity
[57][123]. However, high-quality exopolysaccharides can only be produced by halo- or drought-tolerant rhizobacteria that can tolerate and survive under harsh conditions
[58][124].
Soil salinity is regarded as the most significant among abiotic factors
[59][127]. Experiments on inoculation of salt tolerant PGPB have demonstrated remarkable results in increasing agricultural productivity of saline soils
[60][61][128,129]. The mechanisms contributing to plant growth stimulation have already been reviewed
[44][45][26,27]. Aside from the mechanisms inherent in PGPB, salt-resistant bacteria exhibit specialized mechanisms essential for salt stress tolerance and plant growth promotion
Temperature is another crucial factor affecting plant growth. Low temperature puts plants under stress and affects microbial growth and activity. Agricultural cultivation in cold regions requires biofertilizers that can work at low temperatures. Inoculation of cold-adapted microbial inoculants PGPB significantly promotes plant growth under low-temperature conditions
[62][136]. Cold-adapted PGPR, such as
Burkholderia and
Pseudomonas spp., have been described
[63][64][137,138].
5. Multi-Omics Approaches for Studying Microorganisms and Their Consortia
Traditional microbial culturing methods and modern methods such as pyrosequencing or NGS
[65][66][141,142] are used to characterize and compare microbial communities and identify individual functions in different ecological niches. These methods ha
ve specific advantages and limitations that should be taken into account when designing consortia. It is essential to isolate pure cultures of bacteria in order to study them in detail, identify specific traits, and directly determine the genetic components that underlie useful phenotypes
[67][68][143,144]. However, only some soil microorganisms can be cultured in laboratory conditions. Metagenomic analysis approaches and omics technologies allow the structure of the microbial community and the functions of its individual components to be determined
[69][70][145,146]. “Collective phenotypes” of interacting species within the soil microbiome are referred to as the metaphenome
[71][147].
Complete metagenomic sequencing provides information on the genomes of all microorganisms and allows the functional and metabolic potential of a community to be characterized
[72][150]. However, not all genes are expressed at any given time, and the total DNA extracted from soil may contain sequences from currently inactive populations. Nevertheless, high-throughput approaches have identified functional signatures of some rhizosphere and endosphere communities
[66][73][142,151], and it is this approach that can answer the question of which microbial genes are enriched in a particular microhabitat.
The soil metatranscriptomics is used to determine the functions performed by individual members of the soil microbiome
[74][75][152,153]. Metaproteogenomic approaches enable the exploration of active functions and metabolic pathways
[76][154]. These two approaches provide insight into the timing and location of specific gene expression. However, such studies are usually based on relatively shallow metatranscriptomes with read depths insufficient to cover all the members of a community; thus, these studies investigate only the most abundant and transcriptionally active species and genes
Metaproteomic measurements of microbial communities do provide reliable and reasonably accurate estimates of microbial population sizes
[77][157] because proteins make up to 40–60% of bacterial cell biomass
[78][158] and have a linear correlation with cell mass and volume
[79][159]. Estimates of relative cell population sizes in the organism community, based on the summation of protein abundance or content, suggest that the habitat has achieved population equilibrium and stabilization. Metaproteomics allows large-scale identification and quantification of microbial community proteins, facilitating the characterization of microbial identity, functional roles, and interspecific interactions in the community
[80][160].
6. Analysis of Metabolic Networks of Microbial Communities
Reconstructing metabolic networks of microbial communities is a challenging task. Even when dealing with a single species, the iterative process of genome-wide reconstruction of the metabolic network demands a substantial amount of time
[81][168]. Modeling a community is a more challenging process due to the increased complexity associated with interactions between species. The traditional practice of designing community metabolic networks focuses on reconstructing high-quality individual networks so that their combination may provide quantitative predictions of metabolic interactions and community behavior
[82][169]. However, in practice, such an approach does not take into account possible microbial interactions. The minimum information required includes the genome sequence determining the key metabolic functions and physiological data, such as growth conditions for more accurate modeling of networks.
Current sequencing methods fail to read the entire genome at a time. Therefore, all sequencing protocols start by cutting DNA into smaller fragments that the sequencer can read
[83][172]. The sequences of overlapping fragments resulting from sequencing are called contigs. If the sequencing coverage is deep enough, contigs can be assembled into one or more scaffolds covering the complete genome. Subsequently, it is essential to ascertain the location of the genes and comprehend their respective functions. The most important genes for metabolic reconstruction are those that function as enzymes and transport proteins.
7. Conclusions
Modern agricultural practices commonly make use of inoculants consisting of a single strain isolated through in vitro screening of plant growth stimulation activity or inoculation experiments under controlled conditions. Although these strategies are widely used, they neglect important aspects of plant–microbe interactions. Due to the highly diverse and complex nature of the plant rhizosphere microbiome, which is sustained through extensive interactions between microbes and their hosts, a more comprehensive understanding can only be achieved by implementing sophisticated research methodologies.
In recent years, the studies of the plant rhizosphere microbiome have provided new insights into microbial diversity, abundance, distribution, dynamics, and functions. The emergence of various microbiome-related phenotypes is attributed not to the impact of a single species but to the cooperative interaction of multiple species that effectively execute a common function. Microbial interaction networks in soil are often analyzed to detect the co-occurrence among community members and to identify the key taxa. These taxa may be critical to microbial communities, and their removal can cause dramatic shifts in microbial community structure and function. Given the complexity and context-specific nature of ecological interactions among microorganisms, which involve both structural and random interactions, it is often difficult to discern the contributions of different members within a microbial consortium to a particular function or phenotype.