Competitiveness of Bradyrhizobium japonicum inoculation strain for soybean nodule occupancy

The competitiveness of Bradyrhizobium japonicum inoculation strain against indigenous rhizobia was examined in a soil pot experiment. The effect of inoculation strain was evaluated under different soil conditions: with or without previously grown soybean and applied commercial inoculant. Molecular identification of inoculation strain and investigated rhizobial isolates, obtained from nodules representing inoculated treatments, was performed based on 16S rDNA and enterobacterial repetitive intergenic consensus (ERIC) sequencing. Inoculation strain showed a significant effect on the investigated parameters in both soils. Higher nodule occupancy (45% vs. 18%), nodule number (111% vs. 5%), nodule dry weight (49% vs. 9%), shoot length (15% vs. 7%), root length (31% vs. 13%), shoot dry weight (34% vs. 11%), shoot nitrogen content (27% vs. 2%), and nodule nitrogen content (9% vs. 5%) was detected in soil without previously grown soybean and applied commercial inoculant. Soil had a significant effect on the shoot, root and nodule nitrogen content, while interaction of experimental factors significantly altered dry weight and nitrogen content of shoots, roots and nodules, as well as number of nodules. Nodulation parameters were significantly related with shoot dry weight, shoot and nodule nitrogen content. Symbiotic performance of inoculation strains in the field could be improved through co-selection for their competitiveness and effectiveness.

Using Machine Learning to Develop a Fully Automated Soybean Nodule Acquisition Pipeline (SNAP)

Nodules form on plant roots through the symbiotic relationship between soybean (Glycine max L. Merr.) roots and bacteria (Bradyrhizobium japonicum) and are an important structure where atmospheric nitrogen (N2) is fixed into bioavailable ammonia (NH3) for plant growth and development. Nodule quantification on soybean roots is a laborious and tedious task; therefore, assessment is frequently done on a numerical scale that allows for rapid phenotyping, but is less informative and suffers from subjectivity. We report the Soybean Nodule Acquisition Pipeline (SNAP) for nodule quantification that combines RetinaNet and UNet deep learning architectures for object (i.e., nodule) detection and segmentation. SNAP was built using data from 691 unique roots from diverse soybean genotypes, vegetative growth stages, and field locations and has a good model fit (R2=0.99). SNAP reduces the human labor and inconsistencies of counting nodules, while acquiring quantifiable traits related to nodule growth, location, and distribution on roots. The ability of SNAP to phenotype nodules on soybean roots at a higher throughput enables researchers to assess the genetic and environmental factors, and their interactions on nodulation from an early development stage. The application of SNAP in research and breeding pipelines may lead to more nitrogen use efficiency for soybean and other legume species cultivars, as well as enhanced insight into the plant-Bradyrhizobium relationship.

DIAZOTROPH ACTIVITY REGULATING STRATEGY UNDER THEIR INTRODUCTION IN AGROCENOSES

Objective. Investigate approaches to managing the activity of soil diazotrophs and propose a strategy for its regulation. Methods. Theoretical, vegetation and field experiments, microbiological, gas chromatographic, mathematical and statistical. Results. The activity of beneficial soil microorganisms can change under the action of temperature, humidity, chemical compounds of various origin, and other microorganisms. It was established that, taking into account a significant variety of factors, it is necessary to develop a set of specific ways to increase the growth and functional activity of nitrogen-fixing bacteria, as well as their viability. It has been proved that the combination of diazotrophs forms an effective symbiotic leguminous-rhizobial system, which provides additional biological nitrogen in agrocenoses. At the same time, there was an increase in plant mass, chlorophyll content in the leaves, protein and oil content in the products. The combined use of diazotrophs increases the yield, in particular, soybeans by 9–16 % compared with inoculation by pure bacterial culture. Conclusion. Based on the analysis and generalization of the obtained research results, a strategy for regulating the activity of diazotrophs for their effective introduction into agrocenoses is proposed, which consists in combining bacteria of different species, selecting conditions for their co-cultivation and application upon stabilisation of the number of viable bacterial cells. The proposed strategy involves solving the problem by obtaining an inoculant, which is characterized by a high titre and a stable number of viable cells, which allows to obtain an effective nitrogen-fixing system. The strategy is tried-and-tested on the example of regulating the growth and functional activity of soybean nodule bacteria by combining diazotrophs of different species, substantiating the conditions of their co-cultivation and application to ensure positive interaction in the form of commensalism, as well as by regulating viability of diazotrophs by adding stabilisers to the medium.

Species diversity of natural rhizobia populations of the Russian Far East

The specificity of the soils of the Far East is the presence of aboriginal soybean nodule bacteria in them. A detailed study of the morphological and cultural, physiological and economically useful properties of these microorganisms made it possible to identify the most valuable strains of B. japonicum, S. fredii, B. elkanii from the Far Eastern natural populations for their preservation in the collection.

Soybean Nodule-Associated Non-Rhizobial Bacteria Inhibit Plant Pathogens and Induce Growth Promotion in Tomato

The root nodules are a unique environment formed on legume roots through a highly specific symbiotic relationship between leguminous plants and nodule-inducing bacteria. Previously, Rhizobia were presumed to be the only group of bacteria residing within nodules. However, recent studies discovered diverse groups of bacteria within the legume nodules. In this report soybean nodule-associated bacteria were studied in an effort to identify beneficial bacteria for plant disease control and growth promotion. Analysis of surface-sterilized single nodules showed bacterial diversity of the nodule microbiome. Five hundred non-rhizobial colonies from 10 nodules, 50 colonies per nodule, were tested individually against the tomato wilt causing bacterial pathogen Clavibacter michiganensis subsp. michiganensis (Cmm) for inhibition of pathogen growth. From the initial screening, 54 isolates were selected based on significant growth inhibition of Cmm. These isolates were further tested in vitro on another bacterial pathogen Pseudomonas syringae pv. tomato (Pst) and two fungal pathogens Rhizoctonia solani and Sclerotinia sclerotiorum. Bacterial metabolites were extracted from 15 selected isolates with ethanol and tested against pathogen Cmm and Pst. These isolates were identified by using MALDI-TOF mass spectrometry and 16S rRNA gene sequencing. Pseudomonas spp. were the dominant soybean nodule-associated non-rhizobial bacterial group. Several isolates imparted significant protection against pathogens and/or plant growth promotion on tomato seedlings. The most promising nodule-associated bacterial isolate that suppressed both Cmm and Pst in vitro and Pst in tomato seedlings was identified as a Proteus species. Isolation and identification of beneficial nodule-associated bacteria established the foundation for further exploration of potential nodule-associated bacteria for plant protection and growth promotion.

Using Machine Learning To Develop A Fully Automated Soybean Nodule Acquisition Pipeline (SNAP)

Nodules form on plant roots through the symbiotic relationship between soybean (Glycine max L. Merr.) roots and bacteria (Bradyrhizobium japonicum), and are an important structure where atmospheric nitrogen (N2) is fixed into bio-available ammonia (NH3) for plant growth and developmental. Nodule quantification on soybean roots is a laborious and tedious task; therefore, assessment is done on a less informative qualitative scale. We report the Soybean Nodule Acquisition Pipeline (SNAP) for nodule quantification that combines RetinaNet and UNet deep learning architectures for object (i.e., nodule) detection and segmentation. SNAP was built using data from 691 unique roots from diverse soybean genotypes, vegetative growth stages, and field locations; and has a prediction accuracy of 99%. SNAP reduces the human labor and inconsistencies of counting nodules, while acquiring quantifiable traits related to nodule growth, location and distribution on roots. The ability of SNAP to phenotype nodules on soybean roots at a higher throughput enables researchers to assess the genetic and environmental factors, and their interactions on nodulation from an early development stage. The application of SNAP in research and breeding pipelines may lead to more nitrogen use efficient soybean and other legume species cultivars, as well as enhanced insight into the plant-Bradyrhizobium relationship.

Biological and Cellular Functions of the Microdomain-Associated FWL/CNR Protein Family in Plants

Membrane microdomains/nanodomains are sub-compartments of the plasma membrane enriched in sphingolipids and characterized by their unique protein composition. They play important roles in regulating plant development and plant-microbe interactions including mutualistic symbiotic interactions. Several protein families are associated with the microdomain fraction of biological membranes such as flotillins, prohibitins, and remorins. More recently, GmFWL1, a FWL/CNR protein exclusively expressed in the soybean nodule, was functionally characterized as a new microdomain-associated protein. Interestingly, GmFWL1 is homologous to the tomato FW2-2 protein, a major regulator of tomato fruit development. In this review, we summarize the knowledge gained about the biological, cellular, and physiological functions of members of the FWL/CNR family across various plant species. The role of the FWL/CNR proteins is also discussed within the scope of their evolution and transcriptional regulation.