Using a soil bacterial species balance index to estimate potato crop productivity

Engineering agricultural soil microbiomes and predicting plant phenotypes

Plant growth-promoting rhizobacteria (PGPR) can improve crop yields, nutrient use efficiency, plant tolerance to stressors, and confer benefits to future generations of crops grown in the same soil. Unlocking the potential of microbial communities in the rhizosphere and endosphere is therefore of great interest for sustainable agriculture advancements. Before plant microbiomes can be engineered to confer desirable phenotypic effects on their plant hosts, a deeper understanding of the interacting factors influencing rhizosphere community structure and function is needed. Dealing with this complexity is becoming more feasible using computational approaches. In this review, we discuss recent advances at the intersection of experimental and computational strategies for the investigation of plant-microbiome interactions and the engineering of desirable soil microbiomes.

The potato rhizosphere microbiota correlated to the yield of three different regions in Korea

We examined potato rhizosphere bacterial and fungal communities across three regions: Cheongju, Pyeongchang, and Gangneung. These regions have varying soil and climate conditions, resulting in different yields. We found that precipitation was the main limiting factor in our study while soil physiochemical factors affect bacterial and fungal microbiota in correlation with yield. Both bacterial and fungal microbiota showed distinct patterns according to the regions. ASVs positively correlated with yield were predominantly found in the Pyeongchang region which also produced the highest yields, while ASVs negatively correlated with yield were associated with Gangneung where the lowest yields were observed. The greatest bacterial and fungal diversity was detected in Pyeongchang consisting of Propionibacteriales, Burkholderiales, and Vicinamibacteriales. Gangneung, on the other hand primarily belong to Sordariales, Mortierellales, Cystofilobasidiales, and Tremellales. The putative yield-negative ASVs detected in Gangneung may have been influenced by drought stress. This work has highlighted key bacterial and fungal taxa as well as core taxa that may potentially be associated with high and low yields of potato in relation to metadata which includes soil chemical and physical parameters as well as weather data. Taken together we suggest that this information can be used to assess site suitability for potato production.

Traditional potato tillage systems in the Peruvian Andes impact bacterial diversity, evenness, community composition, and functions in soil microbiomes

The soil microbiome, a crucial component of agricultural ecosystems, plays a pivotal role in crop production and ecosystem functioning. However, its response to traditional tillage systems in potato cultivation in the Peruvian highlands is still far from understood. Here, ecological and functional aspects of the bacterial community were analyzed based on soil samples from two traditional tillage systems: 'chiwa' (minimal tillage) and 'barbecho' (full tillage), in the Huanuco region of the Peruvian central Andes. Similar soil bacterial community composition was shown for minimal tillage system, but it was heterogeneous for full tillage system. This soil bacterial community composition under full tillage system may be attributed to stochastic, and a more dynamic environment within this tillage system. 'Chiwa' and 'barbecho' soils harbored distinct bacterial genera into their communities, indicating their potential as bioindicators of traditional tillage effects. Functional analysis revealed common metabolic pathways in both tillage systems, with differences in anaerobic pathways in 'chiwa' and more diverse pathways in 'barbecho'. These findings open the possibilities to explore microbial bioindicators for minimal and full tillage systems, which are in relationship with healthy soil, and they can be used to propose adequate tillage systems for the sowing of potatoes in Peru.

Potato Microbiome: Relationship with Environmental Factors and Approaches for Microbiome Modulation

Every land plant exists in a close relationship with microbial communities of several niches: rhizosphere, endosphere, phyllosphere, etc. The growth and yield of potato-a critical food crop worldwide-highly depend on the diversity and structure of the bacterial and fungal communities with which the potato plant coexists. The potato plant has a specific part, tubers, and the soil near the tubers as a sub-compartment is usually called the "geocaulosphere", which is associated with the storage process and tare soil microbiome. Specific microbes can help the plant to adapt to particular environmental conditions and resist pathogens. There are a number of approaches to modulate the microbiome that provide organisms with desired features during inoculation. The mechanisms of plant-bacterial communication remain understudied, and for further engineering of microbiomes with particular features, the knowledge on the potato microbiome should be summarized. The most recent approaches to microbiome engineering include the construction of a synthetic microbial community or management of the plant microbiome using genome engineering. In this review, the various factors that determine the microbiome of potato and approaches that allow us to mitigate the negative impact of drought and pathogens are surveyed.

Development of rapid and precise approach for quantification of bacterial taxa correlated with soil health

The structure and dynamic of soil bacterial community play a crucial role in soil health and plant productivity. However, there is a gap in studying the un-/or reclaimed soil bacteriome and its impact on future plant performance. The 16S metagenomic analysis is expensive and utilize sophisticated pipelines, making it unfavorable for researchers. Here, we aim to perform (1) in silico and in vitro validation of taxon-specific qPCR primer-panel in the detection of the beneficial soil bacterial community, to ensure its specificity and precision, and (2) multidimensional analysis of three soils/locations in Egypt ('Q', 'B', and 'G' soils) in terms of their physicochemical properties, bacteriome composition, and wheat productivity as a model crop. The in silico results disclosed that almost all tested primers showed high specificity and precision toward the target taxa. Among 17 measured soil properties, the electrical conductivity (EC) value (up to 5 dS/m) of 'Q' soil provided an efficient indicator for soil health among the tested soils. The 16S NGS analysis showed that the soil bacteriome significantly drives future plant performance, especially the abundance of Proteobacteria and Actinobacteria as key indicators. The functional prediction analysis results disclosed a high percentage of N-fixing bacterial taxa in 'Q' soil compared to other soils, which reflects their positive impact on wheat productivity. The taxon-specific qPCR primer-panel results revealed a precise quantification of the targeted taxa compared to the 16S NGS analysis. Moreover, 12 agro-morphological parameters were determined for grown wheat plants, and their results showed a high yield in the 'Q' soil compared to other soils; this could be attributed to the increased abundance of Proteobacteria and Actinobacteria, high enrichment in nutrients (N and K), or increased EC/nutrient availability. Ultimately, the potential use of a taxon-specific qPCR primer-panel as an alternative approach to NGS provides a cheaper, user-friendly setup with high accuracy.

A sensitive soil biological indicator to changes in land-use in regions with Mediterranean climate

The demand for reliable indicators to quantify soil health has increased recently. We propose and test the use of soil microbial functional diversity as an indicator of multifunctional performance in agriculturally important areas. Agricultural fields in the Mediterranean and semiarid regions of Israel were selected as test sites and measured in Spring and Autumn seasons. Measurements included microbial parameters, basic soil abiotic properties and biological responses to agricultural management relative to measures of a natural ecosystem. Using a canonical correlation analysis we found that soil moisture was the most important basic soil property with different responses in Spring and Autumn. In Spring, it had a strongly negative relation with microbial biomass (MB), community level physiological profiling (CLPP) and the Shannon-Weaver index H', while in Autumn it had a strong relation with CLPP. We further show a significant interaction between CLPP and climate for land-use type "orchards". CLPP measured in the autumn season was thus identified as a useful and rapid biological soil health indicator, recommended for application in semiarid and Mediterranean agricultural regions. Apart from obtaining a better understanding of CLPP as the soil indicator, the study concludes that CLPP is well suited to differentiate between soils in different climates, seasons and land use types. The study shows a promising direction for further research on characterizing soil health under a larger variety of conditions.

The forecasting power of the microbiome

Microorganisms are informative biological integrators of past and present environmental abiotic and biotic conditions. At the same time, they are directly involved in ecosystem processes. Unfortunately, the complexity of microbial communities has so far resulted in most studies being descriptive. Here, we suggest that signals in the microbiome data can be used to forecast future ecosystem processes. The combination of omics with various statistical learning approaches, selected based on accuracy-interpretability and bias-variance trade-offs, will be key to attain this goal, as exemplified by recent studies. The time is ripe for microbial ecologists to fully exploit the forecasting power of microbiomes.

Diversity and composition of soil Acidobacteria and Proteobacteria communities as a bacterial indicator of past land-use change from forest to farmland

The land-use change from natural to managed farmland ecosystems can undergo perturbations and significantly impact soil environment and communities. To understand how anthropogenic land-use alteration determines in-depth relationships among soil environmental factors and soil bacterial communities, high-resolution characterization was performed using soil samples (27 spots × 3 depths; top 10-20 cm, middle 90-100 cm, bottom 180-190 cm) from a natural forest and a 50 year-old farmland. The soil bacterial community abundance (number of OTU's per sample) and diversity (Faith's phylogenetic diversity) was significantly higher in the top layer of farmland soil than in forest soil. However, the differences in bacterial community abundance between farmland and forest decreased with depth, suggesting that the effect of fertilization was limited to top and middle layers. The phyla Acidobacteria and Proteobacteria were distributed distinctively during the land-use change. The subgroups Gp1-3 of Acidobacteria were more abundant in the forest samples (pH 3.5-5), while Gp4-7 and Gp10 were predominant in the farmland (pH 4.5-9.5). Members belonging to α-Proteobacteria and Xanthomonadales in γ-Proteobacteria were dominant in the forest, whereas β-, δ-, and γ-Proteobacteria were relatively abundant in the farmland. Both multivariate and correlation network analyses revealed that Acidobacteria and Proteobacteria communities were significantly affected by soil pH, as well as toxic metals from pesticides (Zn, Cr, Ni, Cu, Cd, As) and terminal electron acceptors (NO₃, bioavailable Fe(III), SO₄). In line with the long history of anthropogenic fertilization, the farmland site showed high abundance of membrane and ATP-binding cassette transporter genes, suggesting the key for uptake of nutrients and for protection against toxic metals and environmental stresses. This study provides new insights into the use of both Acidobacteria and Proteobacteria community structures as a bacterial indicator for land-use change.

Local Network Properties of Soil and Rhizosphere Microbial Communities in Potato Plantations Treated with a Biological Product Are Important Predictors of Crop Yield

Understanding the effectiveness and potential mechanism of action of agricultural biological products under different soil profiles and crops will allow more precise product recommendations based on local conditions and will ultimately result in increased crop yield. This study aimed to use bulk soil and rhizosphere microbial composition and structure to evaluate the potential effect of a Bacillus amyloliquefaciens inoculant (strain QST713) on potatoes and to explore its relationship with crop yield. We implemented next-generation sequencing (NGS) and bioinformatics approaches to assess the bacterial and fungal biodiversity in 185 soil samples, distributed over four different time points—from planting to harvest—from three different geographical locations in the United States. In addition to location and sampling time (which includes the difference between bulk soil and rhizosphere) as the main variables defining the microbiome composition, the microbial inoculant applied as a treatment also had a small but significant effect in fungal communities and a marginally significant effect in bacterial communities. However, treatment preserved the native communities without causing a detectable long-lasting effect on the alpha- and beta-diversity patterns after harvest. Using information about the application of the microbial inoculant and considering microbiome composition and structure data, we were able to train a Random Forest model to estimate if a bulk soil or rhizosphere sample came from a low- or high-yield block with relatively high accuracy (84.6%), concluding that the structure of fungal communities gives us more information as an estimator of potato yield than the structure of bacterial communities.

IMPORTANCE Our results reinforce the notion that each cultivar on each location recruits a unique microbial community and that these communities are modulated by the vegetative growth stage of the plant. Moreover, inoculation of a Bacillus amyloliquefaciens strain QST713-based product on potatoes also changed the abundance of specific taxonomic groups and the structure of local networks in those locations where the product caused an increase in the yield. The data obtained, from in-field assays, allowed training a predictive model to estimate the yield of a certain block, identifying microbiome variables—especially those related to microbial community structure—even with a higher predictive power than the geographical location of the block (that is, the principal determinant of microbial beta-diversity). The methods described here can be replicated to fit new models in any other crop and to evaluate the effect of any agricultural input in the composition and structure of the soil microbiome.

Irreplaceable Role of Amendment-Based Strategies to Enhance Soil Health and Disease Suppression in Potato Production

Soilborne diseases are a major constraining factor to soil health and plant health in potato production. In the toolbox of crop management, soil amendments have shown benefits to control these diseases and improve soil quality. Most amendments provide nutrients to plants and suppress multiple soilborne pathogens. Soil amendments are naturally derived materials and products and can be classified into fresh or living plants, organic or inorganic matters, and microbial supplements. Fresh plants have unique functions and continuously exude chemicals to interact with soil microbes. Organic and inorganic matter contain high levels of nutrients, including nitrogen and carbon that plants and soil microorganisms need. Soil microorganisms, whether being artificially added or indigenously existing, are a key factor in plant health. Microbial communities can be considered as a biological reactor in an ecosystem, which suppress soilborne pathogens in various mechanisms and turn soil organic matter into absorbable forms for plants, regardless of amendment types. Therefore, soil amendments serve as an energy input, nutrient source, and a driving force of microbial activities. Advanced technologies, such as microbiome analyses, make it possible to analyze soil microbial communities and soil health. As research advances on mechanisms and functions, amendment-based strategies will play an important role in enhancing soil health and disease suppression for better potato production.

Using soil bacterial communities to predict physico-chemical variables and soil quality

BACKGROUND

Soil ecosystems consist of complex interactions between biological communities and physico-chemical variables, all of which contribute to the overall quality of soils. Despite this, changes in bacterial communities are ignored by most soil monitoring programs, which are crucial to ensure the sustainability of land management practices. We applied 16S rRNA gene sequencing to determine the bacterial community composition of over 3000 soil samples from 606 sites in New Zealand. Sites were classified as indigenous forests, exotic forest plantations, horticulture, or pastoral grasslands; soil physico-chemical variables related to soil quality were also collected. The composition of soil bacterial communities was then used to predict the land use and soil physico-chemical variables of each site.

RESULTS

Soil bacterial community composition was strongly linked to land use, to the extent where it could correctly determine the type of land use with 85% accuracy. Despite the inherent variation introduced by sampling across ~ 1300 km distance gradient, the bacterial communities could also be used to differentiate sites grouped by key physico-chemical properties with up to 83% accuracy. Further, individual soil variables such as soil pH, nutrient concentrations and bulk density could be predicted; the correlations between predicted and true values ranged from weak (R2 value = 0.35) to strong (R2 value = 0.79). These predictions were accurate enough to allow bacterial communities to assign the correct soil quality scores with 50-95% accuracy.

CONCLUSIONS

The inclusion of biological information when monitoring soil quality is crucial if we wish to gain a better, more accurate understanding of how land management impacts the soil ecosystem. We have shown that soil bacterial communities can provide biologically relevant insights on the impacts of land use on soil ecosystems. Furthermore, their ability to indicate changes in individual soil parameters shows that analysing bacterial DNA data can be used to screen soil quality. Video Abstract.