From lab bench to farmers' fields: Co-creating microbial inoculants with farmers input

Neuhoff D., Neumann G., Weinmann M.

In the European Union and worldwide there are a burgeoning markets for plant growth promoting microorganisms (PGPM) and other biological agents as soil improvers, bio-fertilizers, plant bio-stimulants, and biological control agents or bio-pesticides. Microbial agents have a major share in this development. The use of such products is often advertised with the promise of contributing to sustainable agricultural practices by increasing crop growth and yield and offering an alternative or substitute to decrease the dependency of agriculture on hazardeous agrochemicals. In contrast to registered microbial plant protection products, PGPM that are marketed in the EU as soil improvers or plant biostimulants, are not strictly required to have proven minimum efficacy levels under field conditions. Manufacturers only have to ensure that these products do not pose unacceptable risks to human, animal or plant health, safety or the environment. Uniform guidelines comparable to the EPPO - standards (European and Mediterranean Plant Protection Organisation) to test the efficacy in field trials are not available. This paper attempts to fill the gap. It proposes guidelines for PGPM field trial design and implementation, as well as recommendations for the type and scope of data collection and evaluation. Selected research papers from literature were evaluated to analyze, whether and to what extent the requirements are already met. The majority of the papers had a clear experimental design followed by proper data evaluation. Frequent deficiencies were the low number of tested environments and crop species, insufficient site and agronomic management description and missing data on soil humidity and temperature. Using the suggested standards is assumed to increase the expressive power of tested microbial products.

Kharbikar L., Konwarh R., Chakraborty M., Nandanwar S., Marathe A., Yele Y., Ghosh P.K., Sanan-Mishra N., Singh A.P.

The recent thrust in research has projected the type II clustered regularly interspaced short palindromic repeats and associated protein 9 (CRISPR-Cas9) system as an avant-garde plant genome editing tool. It facilitates the induction of site-specific double-stranded DNA cleavage by the RNA-guided DNA endonuclease (RGEN), Cas9. Elimination, addition, or alteration of sections in DNA sequence besides the creation of a knockout genotype (CRISPRko) is aided by the CRISPR-Cas9 system in its wild form (wtCas9). The inactivation of the nuclease domain generates a dead Cas9 (dCas9), which is capable of targeting genomic DNA without scissoring it. The dCas9 system can be engineered by fusing it with different effectors to facilitate transcriptional activation (CRISPRa) and transcriptional interference (CRISPRi). CRISPR-Cas thus holds tremendous prospects as a genome-manipulating stratagem for a wide gamut of crops. In this article, we present a brief on the fundamentals and the general workflow of the CRISPR-Cas system followed by an overview of the prospects of bioinformatics in propelling CRISPR-Cas research with a special thrust on the available databases and algorithms/web-accessible applications that have aided in increasing the usage and efficiency of editing. The article also provides an update on the current regulatory landscape in different countries on the CRISPR-Cas edited plants to emphasize the far-reaching impact of the genomic editing technology.

Ledford H.

Landmark approval of the first CRISPR therapy paves the way for treatments based on more efficient and more precise genome editors. Landmark approval of the first CRISPR therapy paves the way for treatments based on more efficient and more precise genome editors.

Kumar N., Haldarb S., Saikia R.

The release of plant metabolites from the root plays a vital role in the way plants react to and transform their surroundings, particularly when faced with stressful conditions such as salt stress. High soil salinity poses a significant challenge to the growth and viability of plants, as it has the potential to disturb the intricate equilibrium of ions and water essential for the proper functioning of plant tissues. In response, plants develop different mechanisms to cope with this stress. There is no clear evidence to suggest that plants have a specialized root exudation process explicitly aimed at defending against salt stress. However, numerous studies have shown that when a plant encounters salt stress, it releases root exudates with distinct compositions in response to this challenge. These specialized root exudates have a beneficial role in helping plants deal with soil salinity by attracting stress-reducing rhizobacteria. In this review, we compile recent evidence supporting the notion that plants exhibit a "cry for help" response when exposed to salt stress, which leads to the recruitment of stress-relieving rhizobacteria. Furthermore, we address important methodological considerations in choosing experimental approaches, such as sampling medium (soil, agar matrix, glass beads, hydroponics), and the impact of sterility on sampling accuracy in natural terrestrial environments. Additionally, we provide a summary of the main analytical techniques used to analyze components of root exudates.

Anzuay M.S., Viso N.P., Ludueña L.M., Morla F.D., Dalmasso R.Y., Angelini J.G., Taurian T.

The use of biological inoculants in replacement of the application of chemical fertilizers is a desirable strategy taking into account it is more sustainable and economically less costly. Considering that agricultural practices can produce effects on soil microbial communities associated to the plant crops, the objective of this study was to analyze and compare the effect of these two practices on the structure of the rhizobacterial community of peanut and maize plants. For this purpose, microcosm assays were performed in which peanut and maize plants were inoculated individually with native peanut phosphate solubilizing strains or chemical fertilized with phosphorus, nitrogen, zinc and sulphur. At the beginning and at the end of the assays, samples of rhizospheric soil DNA were obtained and the structure of the rhizospheric bacterial community was analyzed by high-throughput sequencing of the 16S rRNA gene by using Illumina MiSeq platform. The results obtained indicated that the structures of the rhizospheric bacterial communities were different depending on plant type. It was possible to observe changes with respect to the initial bacterial structure in all taxonomic levels analyzed of all treatments. The more notorious structural changes of bacterial community were observed in those rhizospheres exposed to chemical fertilizers, mainly in soil samples associated to maize plants. The rhizospheric bacterial community of peanut showed to change mainly with plant growth. In conclusion, the rhizobacterial community structure is highly dynamic and influenced by different factors such as type of plant, the fertilizer input and bio-inoculant applied.

Lutz S., Bodenhausen N., Hess J., Valzano-Held A., Waelchli J., Deslandes-Hérold G., Schlaeppi K., van der Heijden M.G.

AbstractAlternative solutions to mineral fertilizers and pesticides that reduce the environmental impact of agriculture are urgently needed. Arbuscular mycorrhizal fungi (AMF) can enhance plant nutrient uptake and reduce plant stress; yet, large-scale field inoculation trials with AMF are missing, and so far, results remain unpredictable. We conducted on-farm experiments in 54 fields in Switzerland and quantified the effects on maize growth. Growth response to AMF inoculation was highly variable, ranging from −12% to +40%. With few soil parameters and mainly soil microbiome indicators, we could successfully predict 86% of the variation in plant growth response to inoculation. The abundance of pathogenic fungi, rather than nutrient availability, best predicted (33%) AMF inoculation success. Our results indicate that soil microbiome indicators offer a sustainable biotechnological perspective to predict inoculation success at the beginning of the growing season. This predictability increases the profitability of microbiome engineering as a tool for sustainable agricultural management.

Asnicar F., Thomas A.M., Passerini A., Waldron L., Segata N.

Machine learning is increasingly important in microbiology where it is used for tasks such as predicting antibiotic resistance and associating human microbiome features with complex host diseases. The applications in microbiology are quickly expanding and the machine learning tools frequently used in basic and clinical research range from classification and regression to clustering and dimensionality reduction. In this Review, we examine the main machine learning concepts, tasks and applications that are relevant for experimental and clinical microbiologists. We provide the minimal toolbox for a microbiologist to be able to understand, interpret and use machine learning in their experimental and translational activities. In this Review, Segata, Waldron and colleagues discuss important key concepts of machine learning that are relevant to microbiologists and provide them with a set of tools essential to apply machine learning in microbiology research.

Doklega S.M., Saudy H.S., El-Sherpiny M.A., El-Yazied A.A., Abd El-Gawad H.G., Ibrahim M.F., Abd El-Hady M.A., Omar M.M., Metwally A.A.

AbstractCurrently, the world is facing many troubles in crop production and the irrigation water deficit is the most harmful among them. Saving irrigation water is the main target for all countries of the world, especially in arid areas. Field trial was executed aiming to assess the influence of irrigation regimes (100, 80 and 60% of irrigation requirements, IR (IR100, IR80 and IR60, respectively), water-absorbent substances (control, hydrogel polymer and zeolite as soil addition) and foliar application of glutathione (GSH) [with GSH or without] on the performance of common bean plants. Findings clarified that plant fresh weight obtained with the combination of IR80 × zeolite × GSH had no significant differences with the superior combination of IR100 × hydrogel polymer or zeolite × GSH. Hydrogel polymer plus GSH supply showed distinctive enhancements for N, P and K accumulation in common bean leaves. Application of zeolite plus GSH reduced the accumulation of POX and CAT by 21.8 and 15.5% under IR80 and 16.1 and 7.6% under IR60, respectively. Spraying of GSH × hydrogel polymer under IR100, IR80 and IR60 significantly increased the value of pods yield by 26.5%, 25.23% and 32.80, respectively, as compared to corresponding control treatment. the interaction of IR100 and hydrogel polymer whether with or without GSH showed the highest significant values of N, P, protein, fiber, carbohydrates percentages and TDS. Briefly, it can be concluded that water holding amendments i.e., polymer and zeolite as well as low-molecular-weight antioxidants i.e., glutathione can mitigate the hazard impacts of elevated reactive oxygen species production under drought. Practically, common bean growers are advised to treat the soil with available soil amendment (hydrogel polymer, 0.24 t ha−1 or zeolite, 1.20 t ha−1) and spraying common bean plants by glutathione, 1.0 mM to sustain the crop productivity and quality under shortage water conditions

Jansson J.K., McClure R., Egbert R.G.

Recent advances in microbial ecology and synthetic biology have the potential to mitigate damage caused by anthropogenic activities that are deleteriously impacting Earth’s soil ecosystems. Here, we discuss challenges and opportunities for harnessing natural and synthetic soil microbial communities, focusing on plant growth promotion under different scenarios. We explore current needs for microbial solutions in soil ecosystems, how these solutions are being developed and applied, and the potential for new biotechnology breakthroughs to tailor and target microbial products for specific applications. We highlight several scientific and technological advances in soil microbiome engineering, including characterization of microbes that impact soil ecosystems, directing how microbes assemble to interact in soil environments, and the developing suite of gene-engineering approaches. This Review underscores the need for an interdisciplinary approach to understand the composition, dynamics and deployment of beneficial soil microbiomes to drive efforts to mitigate or reverse environmental damage by restoring and protecting healthy soil ecosystems. Challenges and opportunities for engineering and studying the soil microbiome are discussed.

Philippot L., Chenu C., Kappler A., Rillig M.C., Fierer N.

In recent years, there has been considerable progress in determining the soil properties that influence the structure of the soil microbiome. By contrast, the effects of microorganisms on their soil habitat have received less attention with most previous studies focusing on microbial contributions to soil carbon and nitrogen dynamics. However, soil microorganisms are not only involved in nutrient cycling and organic matter transformations but also alter the soil habitat through various biochemical and biophysical mechanisms. Such microbially mediated modifications of soil properties can have local impacts on microbiome assembly with pronounced ecological ramifications. In this Review, we describe the processes by which microorganisms modify the soil environment, considering soil physics, hydrology and chemistry. We explore how microorganism–soil interactions can generate feedback loops and discuss how microbially mediated modifications of soil properties can serve as an alternative avenue for the management and manipulation of microbiomes to combat soil threats and global change. In this Review, Philippot et al. explore how soil microorganisms can affect the physical and chemical properties of soil and discuss the ecological and evolutionary consequences of these microbially driven shifts in soil properties. They also explore how microbially mediated changes in soil properties can be used to combat threats to soil health and other environmental challenges.

Benmrid B., Ghoulam C., Zeroual Y., Kouisni L., Bargaz A.

AbstractEnsuring plant resilience to drought and phosphorus (P) stresses is crucial to support global food security. The phytobiome, shaped by selective pressures, harbors stress-adapted microorganisms that confer host benefits like enhanced growth and stress tolerance. Intercropping systems also offer benefits through facilitative interactions, improving plant growth in water- and P-deficient soils. Application of microbial consortia can boost the benefits of intercropping, although questions remain about the establishment, persistence, and legacy effects within resident soil microbiomes. Understanding microbe- and plant-microbe dynamics in drought-prone soils is key. This review highlights the beneficial effects of rhizobacterial consortia-based inoculants in legume-cereal intercropping systems, discusses challenges, proposes a roadmap for development of P-solubilizing drought-adapted consortia, and identifies research gaps in crop-microbe interactions.

Ubal C., Di-Giorgi G., Contreras-Reyes J.E., Salas R.

Long-term dependence is an essential feature for the predictability of time series. Estimating the parameter that describes long memory is essential to describing the behavior of time series models. However, most long memory estimation methods assume that this parameter has a constant value throughout the time series, and do not consider that the parameter may change over time. In this work, we propose an automated methodology that combines the estimation methodologies of the fractional differentiation parameter (and/or Hurst parameter) with its application to Recurrent Neural Networks (RNNs) in order for said networks to learn and predict long memory dependencies from information obtained in nonlinear time series. The proposal combines three methods that allow for better approximation in the prediction of the values of the parameters for each one of the windows obtained, using Recurrent Neural Networks as an adaptive method to learn and predict the dependencies of long memory in Time Series. For the RNNs, we have evaluated four different architectures: the Simple RNN, LSTM, the BiLSTM, and the GRU. These models are built from blocks with gates controlling the cell state and memory. We have evaluated the proposed approach using both synthetic and real-world data sets. We have simulated ARFIMA models for the synthetic data to generate several time series by varying the fractional differentiation parameter. We have evaluated the proposed approach using synthetic and real datasets using Whittle’s estimates of the Hurst parameter classically obtained in each window. We have simulated ARFIMA models in such a way that the synthetic data generate several time series by varying the fractional differentiation parameter. The real-world IPSA stock option index and Tree Ringtime series datasets were evaluated. All of the results show that the proposed approach can predict the Hurst exponent with good performance by selecting the optimal window size and overlap change.

Zhang F., Hou Y., Zed R., Mauchline T.H., Shen J., Zhang F., Jin K.

Soil compaction restricts root growth and plant nutrient uptake, but the effects on the abundance and diversity of soil microbiome are poorly understood. A field study with maize (Zea mays L.) was conducted with two soil-compaction treatments (NC: non-compacted; C: compacted) to investigate the interactions of root exudates and microorganisms and the effect on P uptake at two growth stages (seedling and flowering). At the seedling stage, shoot P concentration was decreased by 13.7% in the C treatment compared with the NC. Root growth and arbuscular mycorrhizal fungi colonization were reduced probably due to the decreased soil porosity after compaction. However, root organic acid anions (OAAs) levels were increased by 170%. Several genera of actinobacteria were specifically enriched in the rhizosphere and their abundance was significantly correlated with the concentration of OAAs. However, the positive correlations of concentration of OAAs and abundance of microorganisms or plant P uptake were not observed at flowering stage. Our results indicated that besides the well-known function of exuded organic acid anions on soil P mobilization, maize might also select for microorganisms associated with the facilitation of P acquisition, and mitigating P deficiency at the early growth stage of the plant in compacted soil.

Miller T., Mikiciuk G., Kisiel A., Mikiciuk M., Paliwoda D., Sas-Paszt L., Cembrowska-Lech D., Krzemińska A., Kozioł A., Brysiewicz A.

Drought conditions pose significant challenges to sustainable agriculture and food security. Identifying microbial strains that can mitigate drought effects is crucial to enhance crop resilience and productivity. This study presents a comprehensive comparison of several machine learning models, including Random Forest, Decision Tree, XGBoost, Support Vector Machine (SVM), and Artificial Neural Network (ANN), to predict optimal microbial strains for this purpose. Models were assessed on multiple metrics, such as accuracy, standard deviation of results, gains, total computation time, and training time per 1000 rows of data. Notably, the Gradient Boosted Trees model outperformed others in accuracy but required extensive computational resources. This underscores the balance between accuracy and computational efficiency in machine learning applications. Leveraging machine learning for selecting microbial strains signifies a leap beyond traditional methods, offering improved efficiency and efficacy. These insights hold profound implications for agriculture, especially concerning drought mitigation, thus furthering the cause of sustainable agriculture and ensuring food security.

Notario E., Visci G., Fosso B., Gissi C., Tanaskovic N., Rescigno M., Marzano M., Pesole G.

The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary.

Ríos-Ruiz W.F., Jave-Concepción H.G., Torres-Chávez E.E., Rios-Reategui F., Padilla-Santa-Cruz E., Guevara-Pinedo N.E.

This article presents a systematic review of the ecophysiological mechanisms underpinning the essential role of plant-growth-promoting microorganisms (PGPMs) in improving rice yield and quality. The scientific literature is thoroughly reviewed, highlighting how PGPMs positively influence the growth, development, and health of rice plants. Key aspects, such as nitrogen fixation, nutrient solubilization, hormone production, and disease resistance induction, are emphasized. Additionally, technological advancements related to PGPM use are analyzed, including the identification of effective strains, the formulation of enhanced biofertilizers, and genetic engineering. The article concludes that PGPMs represent a promising tool with which to boost the sustainability and productivity of rice cultivation, providing a robust foundation for future research and practical applications in a field crucial to global food security.

Adeniji A., Huang J., Li S., Lu X., Guo R.

This review explores how soil texture and nutrient availability influence root exudate composition and their effects on rhizosphere microbial dynamics and disease suppression, ultimately affecting plant health and resilience. The findings reveal that clay soil has a dense structure and limited aeration. As a stress response, clay soil restricts root growth, prompts plants to release more exudates to enhance nutrient uptake and attracts beneficial microbes. In contrast, sandy soil, due to its loose texture, is easier for roots to penetrate, often resulting in less exudation. Nutrient availability plays a pivotal role in shaping exudate profiles, such as coumarins and organic acids, which recruit beneficial microbes like Pseudomonas and Trichoderma harzianum, aiding in nutrient acquisition and disease suppression. The interaction between soil texture and nutrient levels creates a dynamic environment that shapes microbial community structure and promotes disease suppression. This review highlights the current understanding of how variations in soil texture and nutrient levels impact root exudates and microbial communities in the rhizosphere. It also identifies key gaps, particularly the need for long-term field studies to explore these interactions under diverse environmental conditions. These insights are critical for developing targeted rhizosphere management strategies, paving the way for more resilient and productive agricultural systems.