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
[111,116][49][51]. Some functional features of rhizobacteria (biofilm formation, bioremediation, resistance to soil salinity, and low temperatures) have an impact on plant survival under unfavorable conditions
[117,118][52][53]. 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
[119,120][54][55]. 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)
[121][56].
It is common for bacteria to produce exopolysaccharides under conditions of heavy metal stress and high salinity
[123][57]. However, high-quality exopolysaccharides can only be produced by halo- or drought-tolerant rhizobacteria that can tolerate and survive under harsh conditions
[124][58].
Soil salinity is regarded as the most significant among abiotic factors
[127][59]. Experiments on inoculation of salt tolerant PGPB have demonstrated remarkable results in increasing agricultural productivity of saline soils
[128,129][60][61]. The mechanisms contributing to plant growth stimulation have already been reviewed
[26,27][44][45]. 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
[136][62]. Cold-adapted PGPR, such as
Burkholderia and
Pseudomonas spp., have been described
[137,138][63][64].
5. Multi-Omics Approaches for Studying Microorganisms and Their Consortia
Traditional microbial culturing methods and modern methods such as pyrosequencing or NGS
[141,142][65][66] 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
[143,144][67][68]. 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
[145,146][69][70]. “Collective phenotypes” of interacting species within the soil microbiome are referred to as the metaphenome
[147][71].
Complete metagenomic sequencing provides information on the genomes of all microorganisms and allows the functional and metabolic potential of a community to be characterized
[150][72]. 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
[142,151][66][73], 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
[152,153][74][75]. Metaproteogenomic approaches enable the exploration of active functions and metabolic pathways
[154][76]. 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
[157][77] because proteins make up to 40–60% of bacterial cell biomass
[158][78] and have a linear correlation with cell mass and volume
[159][79]. 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
[160][80].
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
[168][81]. 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
[169][82]. 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
[172][83]. 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.