Root-associated bacterial communities and root metabolite composition are linked to nitrogen use efficiency in sorghum.

The development of cereal crops with high nitrogen use efficiency (NUE) is a priority for worldwide agriculture. In addition to conventional plant breeding and genetic engineering, the use of the plant microbiome offers another approach to improving crop NUE. To gain insight into the bacterial communities associated with sorghum lines that differ in NUE, a field experiment was designed comparing 24 diverse Sorghum bicolor lines under sufficient and deficient nitrogen (N). Amplicon sequencing and untargeted gas chromatography-mass spectrometry were used to characterize the bacterial communities and the root metabolome associated with sorghum genotypes varying in sensitivity to low N. We demonstrated that N stress and sorghum type (energy, sweet, and grain sorghum) significantly impacted the root-associated bacterial communities and root metabolite composition of sorghum. We found a positive correlation between sorghum NUE and bacterial richness and diversity in the rhizosphere. The greater alpha diversity in high NUE lines was associated with the decreased abundance of a dominant bacterial taxon, Pseudomonas. Multiple strong correlations were detected between root metabolites and rhizosphere bacterial communities in response to low N stress. This indicates that the shift in the sorghum microbiome due to low N is associated with the root metabolites of the host plant. Taken together, our findings suggest that host genetic regulation of root metabolites plays a role in defining the root-associated microbiome of sorghum genotypes differing in NUE and tolerance to low N stress.IMPORTANCEThe development of crops that are more nitrogen use-efficient (NUE) is critical for the future of the enhanced sustainability of agriculture worldwide. This objective has been pursued mainly through plant breeding and plant molecular engineering, but these approaches have had only limited success. Therefore, a different strategy that leverages soil microbes needs to be fully explored because it is known that soil microbes improve plant growth through multiple mechanisms. To design approaches that use the soil microbiome to increase NUE, it will first be essential to understand the relationship among soil microbes, root metabolites, and crop productivity. Using this approach, we demonstrated that certain key metabolites and specific microbes are associated with high and low sorghum NUE in a field study. This important information provides a new path forward for developing crop genotypes that have increased NUE through the positive contribution of soil microbes.

A leaf-level spectral library to support high-throughput plant phenotyping: predictive accuracy and model transfer.

Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of plant leaf traits due to its rapid, low-cost, multi-sensing, and non-destructive nature. However, collecting samples for model calibration can still be expensive, and models show poor transferability among different datasets. This study had three specific objectives: first, to assemble a large library of leaf hyperspectral data (n=2460) from maize and sorghum; second, to evaluate two machine-learning approaches to estimate nine leaf properties (chlorophyll, thickness, water content, nitrogen, phosphorus, potassium, calcium, magnesium, and sulfur); and third, to investigate the usefulness of this spectral library for predicting external datasets (n=445) including soybean and camelina using extra-weighted spiking. Internal cross-validation showed satisfactory performance of the spectral library to estimate all nine traits (mean R2=0.688), with partial least-squares regression outperforming deep neural network models. Models calibrated solely using the spectral library showed degraded performance on external datasets (mean R2=0.159 for camelina, 0.337 for soybean). Models improved significantly when a small portion of external samples (n=20) was added to the library via extra-weighted spiking (mean R2=0.574 for camelina, 0.536 for soybean). The leaf-level spectral library greatly benefits plant physiological and biochemical phenotyping, whilst extra-weight spiking improves model transferability and extends its utility.

Soil depth and geographic distance modulate bacterial ß-diversity in deep soil profiles throughout the U.S. Corn Belt.

Understanding how microbial communities are shaped across spatial dimensions is of fundamental importance in microbial ecology. However, most studies on soil biogeography have focused on the topsoil microbiome, while the factors driving the subsoil microbiome distribution are largely unknown. Here we used 16S rRNA amplicon sequencing to analyse the factors underlying the bacterial ß-diversity along vertical (0-240 cm of soil depth) and horizontal spatial dimensions (~500,000 km2 ) in the U.S. Corn Belt. With these data we tested whether the horizontal or vertical spatial variation had stronger impacts on the taxonomic (Bray-Curtis) and phylogenetic (weighted Unifrac) ß-diversity. Additionally, we assessed whether the distance-decay (horizontal dimension) was greater in the topsoil (0-30 cm) or subsoil (in each 30 cm layer from 30-240 cm) using Mantel tests. The influence of geographic distance versus edaphic variables on the bacterial communities from the different soil layers was also compared. Results indicated that the phylogenetic ß-diversity was impacted more by soil depth, while the taxonomic ß-diversity changed more between geographic locations. The distance-decay was lower in the topsoil than in all subsoil layers analysed. Moreover, some subsoil layers were influenced more by geographic distance than any edaphic variable, including pH. Although different factors affected the topsoil and subsoil biogeography, niche-based models explained the community assembly of all soil layers. This comprehensive study contributed to elucidating important aspects of soil bacterial biogeography including the major impact of soil depth on the phylogenetic ß-diversity, and the greater influence of geographic distance on subsoil than on topsoil bacterial communities in agroecosystems.

Corrigendum: Microbiome variation across populations of desert halophyte Zygophyllum qatarensis.

[This corrects the article DOI: 10.3389/fpls.2022.841217.].

Root exudate concentrations of indole-3-acetic acid (IAA) and abscisic acid (ABA) affect maize rhizobacterial communities at specific developmental stages.

Root exudates shape the rhizosphere microbiome, but little is known about the specific compounds in root exudates that are important. Here, we investigated the impacts of the plant-synthesized phytohormones indole-3-acetic acid (IAA) and abscisic acid (ABA) exuded by roots on the maize rhizobacterial communities. To identify maize genotypes that differed in the root exudate concentrations of IAA and ABA, we screened hundreds of inbred lines using a semi-hydroponic system. Twelve genotypes with variable exudate concentrations of IAA and ABA were selected for a replicated field experiment. Bulk soil, rhizosphere, and root endosphere samples were collected at two vegetative and one reproductive maize developmental stage. IAA and ABA concentrations in rhizosphere samples were quantified by liquid chromatography-mass spectrometry. The bacterial communities were analyzed by V4 16S rRNA amplicon sequencing. Results indicated that IAA and ABA concentrations in root exudates significantly affected the rhizobacterial communities at specific developmental stages. ABA impacted the rhizosphere bacterial communities at later developmental stages, whereas IAA affected the rhizobacterial communities at the vegetative stages. This study contributed to our knowledge about the influence that specific root exudate compounds have on the rhizobiome composition, showing that the phytohormones IAA and ABA exuded by roots have a role in the plant-microbiome interactions.

A role for heritable transcriptomic variation in maize adaptation to temperate environments.

BACKGROUND: Transcription bridges genetic information and phenotypes. Here, we evaluated how changes in transcriptional regulation enable maize (Zea mays), a crop originally domesticated in the tropics, to adapt to temperate environments. RESULT: We generated 572 unique RNA-seq datasets from the roots of 340 maize genotypes. Genes involved in core processes such as cell division, chromosome organization and cytoskeleton organization showed lower heritability of gene expression, while genes involved in anti-oxidation activity exhibited higher expression heritability. An expression genome-wide association study (eGWAS) identified 19,602 expression quantitative trait loci (eQTLs) associated with the expression of 11,444 genes. A GWAS for alternative splicing identified 49,897 splicing QTLs (sQTLs) for 7614 genes. Genes harboring both cis-eQTLs and cis-sQTLs in linkage disequilibrium were disproportionately likely to encode transcription factors or were annotated as responding to one or more stresses. Independent component analysis of gene expression data identified loci regulating co-expression modules involved in oxidation reduction, response to water deprivation, plastid biogenesis, protein biogenesis, and plant-pathogen interaction. Several genes involved in cell proliferation, flower development, DNA replication, and gene silencing showed lower gene expression variation explained by genetic factors between temperate and tropical maize lines. A GWAS of 27 previously published phenotypes identified several candidate genes overlapping with genomic intervals showing signatures of selection during adaptation to temperate environments. CONCLUSION: Our results illustrate how maize transcriptional regulatory networks enable changes in transcriptional regulation to adapt to temperate regions.

Phosphate deficiency modifies lipid composition and seed oil production in camelina.

Camelina (Camelina sativa) is an emerging industrial oilseed crop because of its potential for double cropping, fallow year production, growth on marginal lands, and multiple uses of seed oils and meals. To realize the potential for sustainable production of camelina, a better understanding of how camelina seed oil production and composition respond to low input environments is desired. Phosphorus (P) is one of the least available essential macronutrients to plants with finite worldwide supply. This study investigated seed oil production and lipid composition of camelina in field settings and under greenhouse conditions in response to P deficiency. Lipidomic profiling reveals that P deficiency in field settings triggered extensive leaf lipid remodeling that decreased the ratio of phospholipids to non-P-containing galactolipids from 30% to 5% under P sufficient to deficient conditions. P deficiency increased seed oil content per seed weight by approximately 25% and 20% in field and greenhouse settings, respectively. In addition, P deficiency altered seed fatty acid composition, with increases in monounsaturated 18:1 and 20:1 and decreases in polyunsaturated 18:3. Total seed production was decreased by 10- to 15-fold under P deficiency and the decrease resulted from reduced seed numbers without affecting seed weight. The results from field and greenhouse conditions indicate that P deficiency increases seed oil content, alters fatty acid composition, and decreases greatly seed production, suggesting that achieving a high yield and quality of camelina seed oil is positively linked to P status of soil.

Poisson hurdle model-based method for clustering microbiome features.

MOTIVATION: High-throughput sequencing technologies have greatly facilitated microbiome research and have generated a large volume of microbiome data with the potential to answer key questions regarding microbiome assembly, structure and function. Cluster analysis aims to group features that behave similarly across treatments, and such grouping helps to highlight the functional relationships among features and may provide biological insights into microbiome networks. However, clustering microbiome data are challenging due to the sparsity and high dimensionality. RESULTS: We propose a model-based clustering method based on Poisson hurdle models for sparse microbiome count data. We describe an expectation-maximization algorithm and a modified version using simulated annealing to conduct the cluster analysis. Moreover, we provide algorithms for initialization and choosing the number of clusters. Simulation results demonstrate that our proposed methods provide better clustering results than alternative methods under a variety of settings. We also apply the proposed method to a sorghum rhizosphere microbiome dataset that results in interesting biological findings. AVAILABILITY AND IMPLEMENTATION: R package is freely available for download at https://cran.r-project.org/package=PHclust. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sugars and Jasmonic Acid Concentration in Root Exudates Affect Maize Rhizosphere Bacterial Communities.

Root exudates contribute to shaping the root-associated microbiomes, but it is unclear which of the many exudate compounds are important in this process. Here, we focused on understanding the influence of sugars and jasmonic acid (JA) concentrations in maize root exudates on the rhizobacterial communities. Twelve maize genotypes were identified with variable concentrations of sugars and JA based on a screening of 240 maize genotypes grown in a semihydroponic system. These twelve maize genotypes were grown in a replicated field experiment in which samples were collected at three maize developmental stages. The 16S rRNA gene (V4 region) was amplified and sequenced. Sugars and JA concentrations from rhizosphere soils were also quantified. The results indicated that the maize genotypic variability in sugars and JA concentration in root exudates, measured in the semihydroponic system, significantly affected the rhizosphere bacterial community composition at multiple stages plant development. In contrast, the root endosphere and bulk soil bacterial communities were only affected at specific growth stages. Sugars and JA concentration as quantified in rhizosphere soil samples confirmed that these two compounds affected the rhizobacterial communities at all developmental stages analyzed. The effects of specific sugars on the composition of the rhizobacterial communities were also measured, with larger effects of sucrose at earlier developmental stages and trehalose at later developmental stages. Our results indicate that JA and sugars are important root exudate compounds that influence the composition of the maize rhizobacterial communities. IMPORTANCE Roots secrete exudates that are important in interactions with soil microbes that promote plant growth and health. However, the exact chemical compounds in root exudates that participate in these interactions are not fully known. Here, we investigated whether sugars and the phytohormone jasmonic acid influence the composition of the rhizobacterial communities of maize, which is an important crop for food, feed, and energy. Our results revealed that both compounds contribute to the assemblage of rhizobacterial communities at different maize developmental stages. Knowledge about the specific compounds in root exudates that contribute to shape the rhizobiome will be important for future strategies to develop sustainable agricultural practices that are less dependent on agrochemicals.

Genome structure and evolutionary history of frankincense producing Boswellia sacra.

Boswellia sacra Flueck (family Burseraceae) tree is wounded to produce frankincense. We report its de novo assembled genome (667.8 Mb) comprising 18,564 high-confidence protein-encoding genes. Comparing conserved single-copy genes across eudicots suggest >97% gene space assembly of B. sacra genome. Evolutionary history shows B. sacra gene-duplications derived from recent paralogous events and retained from ancient hexaploidy shared with other eudicots. The genome indicated a major expansion of Gypsy retroelements in last 2 million years. The B. sacra genetic diversity showed four clades intermixed with a primary genotype-dominating most resin-productive trees. Further, the stem transcriptome revealed that wounding concurrently activates phytohormones signaling, cell wall fortification, and resin terpenoid biosynthesis pathways leading to the synthesis of boswellic acid-a key chemotaxonomic marker of Boswellia. The sequence datasets reported here will serve as a foundation to investigate the genetic determinants of frankincense and other resin-producing species in Burseraceae.

Increased signal-to-noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components.

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create microtreatments throughout the field. In addition, the variation within different soil properties is often nonrandomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome, and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a method with which sources of environmental variation in field data can be identified and adjusted, improving our ability to resolve effects of interest and to quantify subtle phenotypes.

Natural variation in root exudation of GABA and DIMBOA impacts the maize root endosphere and rhizosphere microbiomes.

Root exudates are important for shaping root-associated microbiomes. However, studies on a wider range of metabolites in exudates are required for a comprehensive understanding about their influence on microbial communities. We identified maize inbred lines that differ in exudate concentrations of 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) and γ-aminobutyric acid (GABA) using a semi-hydroponic system. These lines were grown in the field to determine the changes in microbial diversity and gene expression due to varying concentrations of DIMBOA and GABA in exudates using 16S rRNA amplicon sequencing and metatranscriptomics. Results showed individual and interaction effects of DIMBOA and GABA on the rhizosphere and root endosphere ß-diversity, most strongly at the V10 growth stage. The main bacterial families affected by both compounds were Ktedonobacteraceae and Xanthomonadaceae. Higher concentrations of DIMBOA in exudates affected the rhizosphere metatranscriptome, enriching for metabolic pathways associated with plant disease. This study validated the use of natural variation within plant species as a powerful approach for understanding the role of root exudates on microbiome selection. We also showed that a semi-hydroponic system can be used to identify maize genotypes that differ in GABA and DIMBOA exudate concentrations under field conditions. The impact of GABA exudation on root-associated microbiomes is shown for the first time.

Identification of beneficial and detrimental bacteria impacting sorghum responses to drought using multi-scale and multi-system microbiome comparisons.

Drought is a major abiotic stress limiting agricultural productivity. Previous field-level experiments have demonstrated that drought decreases microbiome diversity in the root and rhizosphere. How these changes ultimately affect plant health remains elusive. Toward this end, we combined reductionist, transitional and ecological approaches, applied to the staple cereal crop sorghum to identify key root-associated microbes that robustly affect drought-stressed plant phenotypes. Fifty-three Arabidopsis-associated bacteria were applied to sorghum seeds and their effect on root growth was monitored. Two Arthrobacter strains caused root growth inhibition (RGI) in Arabidopsis and sorghum. In the context of synthetic communities, Variovorax strains were able to protect plants from Arthrobacter-caused RGI. As a transitional system, high-throughput phenotyping was used to test the synthetic communities. During drought stress, plants colonized by Arthrobacter had reduced growth and leaf water content. Plants colonized by both Arthrobacter and Variovorax performed as well or better than control plants. In parallel, we performed a field trial wherein sorghum was evaluated across drought conditions. By incorporating data on soil properties into the microbiome analysis, we accounted for experimental noise with a novel method and were able to observe the negative correlation between the abundance of Arthrobacter and plant growth. Having validated this approach, we cross-referenced datasets from the high-throughput phenotyping and field experiments and report a list of bacteria with high confidence that positively associated with plant growth under drought stress. In conclusion, a three-tiered experimental system successfully spanned the lab-to-field gap and identified beneficial and deleterious bacterial strains for sorghum under drought.

Microbiome Variation Across Populations of Desert Halophyte Zygophyllum qatarensis.

Microbial symbionts play a significant role in plant health and stress tolerance. However, few studies exist that address rare species of core-microbiome function during abiotic stress. In the current study, we compared the microbiome composition of succulent dwarf shrub halophyte Zygophyllum qatarensis Hadidi across desert populations. The results showed that rhizospheric and endosphere microbiome greatly varied due to soil texture (sandy and gravel). No specific bacterial amplicon sequence variants were observed in the core-microbiome of bulk soil and rhizosphere, however, bacterial genus Alcaligenes and fungal genus Acidea were abundantly distributed across root and shoot endospheres. We also analyzed major nutrients such as silicon (Si), magnesium, and calcium across different soil textures and Z. qatarensis populations. The results showed that the rhizosphere and root parts had significantly higher Si content than the bulk soil and shoot parts. The microbiome variation can be attributed to markedly higher Si - suggesting that selective microbes are contributing to the translocation of soluble Si to root. In conclusion, low core-microbiome species abundance might be due to the harsh growing conditions in the desert - making Z. qatarensis highly selective to associate with microbial communities. Utilizing rare microbial players from plant microbiomes may be vital for increasing crop stress tolerance and productivity during stresses.

A glass bead semi-hydroponic system for intact maize root exudate analysis and phenotyping.

BACKGROUND: Although there have been numerous studies describing plant growth systems for root exudate collection, a common limitation is that these systems require disruption of the plant root system to facilitate exudate collection. Here, we present a newly designed semi-hydroponic system that uses glass beads as solid support to simulate soil impedance, which combined with drip irrigation, facilitates growth of healthy maize plants, collection and analysis of root exudates, and phenotyping of the roots with minimal growth disturbance or root damage. RESULTS: This system was used to collect root exudates from seven maize genotypes using water or 1 mM CaCl2, and to measure root phenotype data using standard methods and the Digital imaging of root traits (DIRT) software. LC-MS/MS (Liquid Chromatography-Tandem Mass Spectrometry) and GC-MS (Gas Chromatography-Mass Spectrometry) targeted metabolomics platforms were used to detect and quantify metabolites in the root exudates. Phytohormones, some of which are reported in maize root exudates for the first time, the benzoxazinoid DIMBOA (2,4-Dihydroxy-7-methoxy-1,4-benzoxazin-3-one), amino acids, and sugars were detected and quantified. After validating the methodology using known concentrations of standards for the targeted compounds, we found that the choice of the exudate collection solution affected the exudation and analysis of a subset of analyzed metabolites. No differences between collection in water or CaCl2 were found for phytohormones and sugars. In contrast, the amino acids were more concentrated when water was used as the exudate collection solution. The collection in CaCl2 required a clean-up step before MS analysis which was found to interfere with the detection of a subset of the amino acids. Finally, using the phenotypic measurements and the metabolite data, significant differences between genotypes were found and correlations between metabolites and phenotypic traits were identified. CONCLUSIONS: A new plant growth system combining glass beads supported hydroponics with semi-automated drip irrigation of sterile solutions was implemented to grow maize plants and collect root exudates without disturbing or damaging the roots. The validated targeted exudate metabolomics platform combined with root phenotyping provides a powerful tool to link plant root and exudate phenotypes to genotype and study the natural variation of plant populations.

Assessment of Bacterial Inoculant Delivery Methods for Cereal Crops.

Despite growing evidence that plant growth-promoting bacteria can be used to improve crop vigor, a comparison of the different methods of delivery to determine which is optimal has not been published. An optimal inoculation method ensures that the inoculant colonizes the host plant so that its potential for plant growth-promotion is fully evaluated. The objective of this study was to compare the efficacy of three seed coating methods, seedling priming, and soil drench for delivering three bacterial inoculants to the sorghum rhizosphere and root endosphere. The methods were compared across multiple time points under axenic conditions and colonization efficiency was determined by quantitative polymerase chain reaction (qPCR). Two seed coating methods were also assessed in the field to test the reproducibility of the greenhouse results under non-sterile conditions. In the greenhouse seed coating methods were more successful in delivering the Gram-positive inoculant (Terrabacter sp.) while better colonization from the Gram-negative bacteria (Chitinophaga pinensis and Caulobacter rhizosphaerae) was observed with seedling priming and soil drench. This suggested that Gram-positive bacteria may be more suitable for the seed coating methods possibly because of their thick peptidoglycan cell wall. We also demonstrated that prolonged seed coating for 12 h could effectively enhance the colonization of C. pinensis, an endophytic bacterium, but not the rhizosphere colonizing C. rhizosphaerae. In the field only a small amount of inoculant was detected in the rhizosphere. This comparison demonstrates the importance of using the appropriate inoculation method for testing different types of bacteria for their plant growth-promotion potential.

Root exudates impact plant performance under abiotic stress.

Plant root exudates serve pivotal roles in supporting plant development and interactions with the physicochemical and biological factors in the rhizosphere. Under stress conditions, root exudation is involved in enhancing plant resource-use efficiency and facilitating the crosstalk between plant and soil microbes to ameliorate stress. Although there are a large number of root exudates that remain to be characterized, recent technological advancements have allowed for the function of many exudate compounds to be elucidated. In this review, we discuss current knowledge about the key root exudates that modulate plant resource-use efficiency under various abiotic stresses including drought, aluminum toxicity, phosphorus, nitrogen, and iron deficiency. The role that key root exudates play in shaping microbial communities in the rhizosphere under stress conditions is also an important consideration addressed in this review.

Transcriptomics of tapping and healing process in frankincense tree during resin production.

Frankincense tree (Boswellia sacra Fluek) has been poorly known on how it responds to tapping and wound-recovery process at molecular levels. Here, we used RNA-sequencing analysis to profile transcriptome of B. sacra after 30 min, 3 h and 6 h of post-tapping. Results showed 5525 differentially expressed genes (DEGs) that were related to terpenoid biosynthesis, phytohormonal regulation, cellular transport, and cell-wall synthesis. Plant-growth-regulators were applied exogenously which showed regulation of endogenous jasmonates and resulted in rapid recovery of cell-wall integrity by significantly up-regulated gene expression of terpenoid biosynthesis (germacrene-D synthase, B-amyrin synthase, and squalene epioxidase-1) and cell-wall synthesis (xyloglucan endotransglucosylase, cellulose synthase-A, and cell-wall hydrolase) compared to control. These findings suggest that tapping immediately activated several cell-developmental and regeneration processes, alongwith defense-induced terpenoid metabolism, to improve the healing process in epidermis. Exogenous growth regulators, especially jasmonic acid, can drastically help tree recovery from tissue degeneration and might help in tree conservation purposes.

Sweet Sorghum Genotypes Tolerant and Sensitive to Nitrogen Stress Select Distinct Root Endosphere and Rhizosphere Bacterial Communities.

The belowground microbiomes have many beneficial functions that assist plant growth, including nutrient cycling, acquisition and transport, as well as alleviation of stresses caused by nutrient limitations such as nitrogen (N). Here we analyzed the root endosphere, rhizosphere and soil bacterial communities of seven sweet sorghum genotypes differing in sensitivity to N-stress. Sorghum genotypes were grown in fields with no (low-N) or sufficient (high-N) N. The dry shoot weight ratio (low-N/high-N) was used to determine N-stress sensitivity. Our hypothesis was that genotypes tolerant and sensitive to N-stress select distinct bacterial communities. The endosphere and rhizosphere bacterial community structure were significantly different between the N-stress sensitive and tolerant genotypes in the high-N field, but not in the low-N field. However, significant changes in the relative abundance of specific bacterial taxa were observed in both fields. Streptomyces, a bacterial genus known to alleviate plant abiotic stresses, was enriched in the endosphere and rhizosphere of the tolerant genotypes in the low-N field. Our study indicates that sweet sorghum genotypes tolerant to N-stress select taxa that can potentially mitigate the N-stress, suggesting that the interactions between N-stress tolerant lines and the root-associated microbiome might be vital for coping with N-stress.