Root inoculation with Herbaspirillum seropedicae RAM10 reveals structural and functional shifts in the wheat seed-borne microbiota associated with improved plant phenotype

doi:10.21203/rs.3.rs-2818060/v1

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Root inoculation with Herbaspirillum seropedicae RAM10 reveals structural and functional shifts in the wheat seed-borne microbiota associated with improved plant phenotype

https://doi.org/10.21203/rs.3.rs-2818060/v1

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Exploiting the beneficial features of the plant microbiota is a promising approach to improve cereal growth and health in a more sustainable manner. Seed-borne endophytic microbiota can intimately colonize the plant’s endosphere and influence plant responses efficiently. Understanding their structure and functions is a critical step towards the formulation of microbial inoculants that can promote plant-beneficial microbiota functions. In this study, both 16S and ITS metabarcoding analyses were employed to explore the structure of the endophytic seed-borne microbiota in wheat seeds as well as in roots either non-inoculated or inoculated with the endophytic bacterium Herbaspirillum seropedicae RAM10. Furthermore, machine learning tools were employed to predict the ecological functions associated to these structural shifts. Inoculation with H. seropedicae markedly changed the composition of the seed-borne endophytic community. This compositional shift mirrored a predicted functional diversification, which was manifested by the differential enrichment of OTUs involved in bacterial nitrogen fixation, nitrate metabolism and aerobic chemoheterotrophy as well as by changes in fungal life strategies. These results suggest that endophytic inoculants could represent suitable vehicles to effectively promote desired plant traits through the modulation of the wheat seed-borne microbiota in the root endosphere.

Biological sciences/Microbiology/Communities

Biological sciences/Microbiology/Environmental microbiology

Biological sciences/Ecology

Biological sciences/Microbiology

Wheat is one of the most important cereals cultivated worldwide, having a crucial role in human diet as a primary source of nutrients and energy. Its production, however, relies heavily on the use of fertilizers and pesticides which, despite boosting crop yields, have entailed a rapid degradation of agrosystems [1]. The unprecedented rate of these challenges calls for novel strategies to sustainably improve crop production without jeopardizing human health or the environment. In this context, harnessing crop-associated microorganisms is becoming a promising approach to create valuable and more eco-friendly products for agricultural application. Plants host a huge diversity of living microorganisms, referred to as microbiota, which can be detected outside (ectosphere) or inside (endosphere) seeds, roots and leaves [2]. Microbiota critically maintain the ecological functioning of their host, thus extending the plants´ abilities to respond to changes in the surrounding environment. For example, they can provide important growth factors and nutrients to improve plant development, or they can induce host defense mechanisms at local and/or systemic levels upon biotic or abiotic stress [3, 4].

Under changing environmental conditions, plant microbial communities undergo structural and functional shifts, which can have either beneficial or deleterious effects for the overall plant condition [5]. Thus, it is of primarily importance to push these microbiota shifts toward increased plant-beneficial services in order to generate improved seeds carrying a microbiota tailored to the needs of the host. One promising strategy to engineer the plant microbiota foresees the application of microbial inoculants. Endophytic inoculants are particularly interesting as they can reach the plant endosphere and may be more sheltered from the external environment, thus increasing their chances to both interact with the indigenous microbiota and influence plant phenotype efficiently [6]. However, although microbiota shifts have been mainly studied in the rhizosphere [3], less is known regarding the changes in the structure and functionality of seed-borne endophytic communities. Due to their early presence within seeds, seed-borne microbiota represent a starting point for community assembly in the new seedling and are considered central players in defining host phenotype [7]. These features make seed-borne endophytes ideal targets for inoculant-mediated engineering strategies aimed at developing seeds holding an improved microbial potential, which could in turn be inherited in subsequent seed generations [8]. Thus, smart delivery approaches of inoculants, particularly considering seeds and the endosphere environment, may represent promising avenues to promote target community members to support a desired plant phenotype.

Endophytes from several cereal varieties have been proposed as potential alternatives for plant-growth promotion [9]. The b-proteobacterium Herbaspirillum seropedicae strain RAM10 [10] is prominently associated to graminaceous plants and has the potential for an intimate root association and growth promotion in different cereals [11, 12]. Different H. seropedicae strains display a wide repertoire of protein secretion systems, type IV pili, as well as genes involved in plant surface adhesion, indicating its potential to actively colonize the endosphere environment [13, 14]. However, its microbiota modulatory capacity has been previously explored through culture-based methods and only considering the bacterial community [15]. In this work, both 16S and ITS metabarcoding analyses were employed to test the hypothesis that H. seropedicae inoculation will lead to structural shifts in the wheat seed-borne endophytic microbiota. Furthermore, machine learning and differential abundance tests were employed in order to identify keystone microbiota members and predict the functional relationship between structural microbiota shifts and host functioning. These results will contribute to the implementation of feasible designs to support plant growth and health through an overlooked mode of action of inoculants: the engineering of the plant microbiota.

2.1 Herbaspirillum seropedicae growth conditions

Herbaspirillum seropedicae strain RAM10, isolated from Graminaceae plants [10], was grown in LB medium (tryptone, 10 g/L; yeast extract, 5 g/L; sodium chloride (NaCl), 10 g/L; pH 7.0] and incubated for 24 h in a rotary shaker (28ºC, 120 rpm), centrifuged (2,374 x g, 10 min, 15 min), and resuspended in 25 ml of 1/4 diluted Hoagland solution [16] to an optical density at a wavelength of 600 nm (OD₆₀₀) = 1 (10⁹ CFU/ml).

2.2 Plant growth conditions and treatments

The plant study complies with relevant institutional, national, and international guidelines and legislation. Wheat (T. aestivum, variety Jordão) seeds, purchased from Estação de Melhoramento de plantas (INIAV, Elvas, Portugal), were surface-sterilized (1.5 min in 70% ethanol; 1 wash in sterile deionized water (s.d.w.), 3 min in sodium hypochlorite; 10 washes in s.d.w.), soaked for 12 h in s.d.w. and heat-treated (10 min, 50ºC). Seeds were then transferred aseptically to Petri dishes containing 1.5% water agar (10 seeds per dish) and kept in a growing chamber with a 16-h light/8-h dark photoperiod and temperature of 25/20ºC (RH = 70/50%), for 96 h. Four-day-old seedlings were transferred to tip boxes containing 250 ml of 1/4 diluted Hoagland solution, with the leaves emerging from the holes of the rack and the solution bathing the roots. Six boxes (21 seedlings/box) were prepared, half of which were kept as control (non-inoculated, NI) roots, and the other half were inoculated

with H. seropedicae (inoculated roots, I) to a final density of 10⁸ CFU/ml. Each box was sealed in sterilized gas exchange bags and maintained in the growth chamber for two weeks. Roots were then collected from each biological replicate, weighted, added to 30 ml s.d.w. and macerated with mortar and pestle. In parallel, three groups consisting of twenty-one surface-sterilized seeds (S) each were added to 30 ml s.d.w. and macerated with mortar and pestle. Both root and seed suspensions were used for the extraction of microbial DNA.

2.3 DNA isolation from plant tissues and 16S rRNA and ITS sequencing

Extraction of DNA from seeds, NI roots and I roots macerates was carried out with the PowerSoil Pro DNA Isolation Kit (Mo Bio Laboratories, Carlsbad, CA, USA). The manufacturer’s instructions were followed and the yield and quality of the DNA was determined using a Qubit 2.0 fluorometer and Qubit dsDNA BR kit (ThermoFisher Scientific, Waltham, MA, USA). Once purified, DNA products were amplified and sequenced by STAB Vida (Lisbon, Portugal). Bacterial DNA was amplified targeting the variable V3-V4 regions of the 16S rRNA gene using the forward primer 341F (5′-CCTACGGGNGGCWGCAG-3′) and the reverse Primer 785R (5′-GACTACHVGGGTATCTAATCC-3′). Fungal DNA was amplified by targeting the fungal ITS1 region between the 18S − 5.8S rRNA using the forward primer ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3´and the revers primer ITS2 (5′-GCTGCGTTCTTCATCGATGC-3′). Genomic libraries were prepared using an in-house protocol based on Illumina 16S Metagenomic Sequencing Library preparation protocol (15044223 Rev. B). DNA products obtained following PCR-mediated amplification of the 16S rRNA gene sequences were purified with the purification kit Agencourt Sera-Mag Select (Cytiva). DNA concentration of the amplified sequence library was determined using a Qubit 2.0 fluorometer and Qubit dsDNA BR kit. Sequencing was carried out throguh Illumina MiSeq platform, using MiSeq eagent Kit v3 and 300bp paired end. The analysis of the generated raw sequence data was carried out using QIIME2 v2022.2. The reads were denoised using the DADA2 plugin. The reads were organized in features, which are essentially units of observation, in this particular case operational taxonomic units (OTUs) and then classified by taxon using a fitted classifier. The scikit-learn classifier was used to train the classifier using the SILVA (release 138 QIIME) database, with a dynamic clustering threshold. For classification purposes, only OTUs containing at least 10 sequence reads were considered as significant.

2.4. Data processing and statistical analyses:

De-noised and filtered sequencing data from each treatment were analyzed using QIIME software, using the barplot command to generate relative abundance profiles at the genus level. Relative abundance profiles generated with the number of reads were used to estimate alpha diversity, both Simpson and Shannon diversity indices were computed (diversity function of the vegan package in R; [17]). Given that microbial communities did not meet the normality assumptions (Shapiro Wilk test; p < 0.05), index values obtained from different treatments were compared by Kruskal-Wallis rank sum test followed by Dunn´s post hoc test, and cases with p < 0.05 were considered statistically significant. To estimate dissimilarity between communities, Bray–Curtis distances were calculated per site using the trans_beta class of the microeco package [18]. Significant differences between groups were calculated using multivariate permutation test (number of permutations = 1000) using the Adonis2 function of the microeco package, and cases with p < 0.05 were considered statistically significant. Principal coordinate analysis (PCoA) plots based on Bray–Curtis and Jaccard distances were plotted using microeco package. To illustrate the distribution of shared and unique species between seeds, NI roots and I roots, the abundance of each fungal and bacterial genus was calculated to build a Venn Diagram, using the trans_venn class of the microeco package. Key taxa in determining the community differences across groups were determined through linear discriminant analysis (LDA) effect size (LEfSe) analyses, using the trans_diff class of the microeco package. The model combined non-parametric test (pairwise Wilcoxon test, p < 0.05) and linear LDA to determine taxa with differential abundance among NI and I roots and to rank these features by their efect size [19]. Taxonomic biomarkers at the genus level were detected using LEfSe with an LDA score threshold > 2.0 and p < 0.05. Functional Annotation of Prokaryotic Taxa (FAPROTAX) was applied to predict the microbial ecological function profiles using trans_func class of the microeco R package, [20], where the percentage of OTUs within each community was associated to specific ecological functions.

3.1. Structural shifts in bacterial microbiota

Both Shannon and Simpson indexes indicated significant differences in bacterial alpha diversity between all groups, with I roots showing higher values compared to both seeds and NI roots (Fig. 1A and B). Furthermore, PCoA based on Bray–Curtis and Jaccard dissimilarity followed by PERMANOVA test highlighted a significant difference between the composition of the communities (p = 0.01, Supplemetaty Table S1a, Fig. 1C). Distribution of taxa based on their patterns of appearance across treatments (Fig. 1D) revealed only one core genus shared between seeds, NI roots and I roots, which showed an overall relative abundance of 75% across treatments. Four and seven genera were exclusive in NI and I roots, respectively. In line with these observations, relative abundance profiles at the genus level revealed clear shifts in bacterial microbiota between seeds, NI roots and I roots (Fig. 1E). Seeds were dominated by the genus Pantoea which accounted for 70% of the bacterial population followed, in decreasing order, by the genus Anaerobacillus, Staphylococcus and Cutibacterium. In the transition from seeds to seedlings, Pantoea abundance increased up to 95% in NI roots, with the remaining 5% including, in decreasing order, members from the genus Curtobacterium, Paenibacillus, Luteibacter, Massilia and Staphylococcus. Compared to NI roots, an increase in the relative abundance of Massilia was observed in I ones, accounting for almost 10% of the bacterial microbiota. Furthermore, I roots showed a 40% reduction in the relative abundance of Pantoea compared to NI ones, concomitant with the emergence of 5 genera from the Pseudomonadota phylum, including, Brevundimonas, Brucella, Luteibacter, and Advenella. Importantly, the inoculant H. seropedicae accounted for nearly 13% of the bacterial microbiota, suggesting the ability of this inoculant to penetrate the roots and multiply within wheat root tissues. Finally, two additional genera from the Actinomycetota phylum, Brevibacterium sp. and Microbacterium sp., were also exclusively detected in I roots.

3.2. Structural shifts in fungal microbiota

Regarding the fungal microbiota, I roots showed significantly higher alpha diversity indexes compared with both seeds and NI roots, which did not differ significantly (Fig. 2A and B). Furthermore, PCoA based on Bray–Curtis and Jaccard dissimilarity showed a significant difference in the composition of the fungal microbiota (p = 0.01, Table S1, Supplementary Table S1b, Fig. 2C). Three genera were shared between seeds, NI roots and I roots, which showed an overall relative abundance of 50% across treatments. In the transition from seeds to seedlings, NI and I roots hosted three common fungal genera, while exclusive fungal genera were found only in I roots (Fig. 2D). Relative abundance profiles at the genus level (Fig. 2E) showed that seeds were dominated by the genus Alternaria which accounted for 82% of the seed microbiota, followed, in decreasing order of abundance, by Fusarium sp., Epicoccum sp. and Meyerozyma sp. Minor taxa (relative abundance < 1%) were also identified in the seed, including Stemphylium, Wallemia, Pleurotus, and Malassezia. In comparison with seeds, both NI and I roots showed a decrease in the population of Alternaria of 27 and 46%, respectively. In NI roots, this decrease in Alternaria populations was accompanied by the emergence of the unicellular yeast Rhodotorula, which accounted for almost 50% of the fungal microbiota, followed members from the genera Meyerozyma, Malassezia and Wallemia. Compared to NI roots, Rhodotorula population decreased drastically and accounted for less than 5% of the population in I roots. In turn, I roots exclusively hosted the yeast from the genus Filobasidium, which accounted for over 40% of the total fungal community.

3.3. Impact of H. seropedicae on biomarker taxa and microbiota functionality

The relative abundance profiles generated with the number of reads were used to detect genera with potential biological relevance related to H. seropedicae inoculation. The LDA scores resulting from LEfSe analysis highlighted that 12 out of 28 genera significantly explained the greatest differences between communities (LDA > 2.0 and p-value < 0.05; Fig. 3A). Most of these genera belonged to the Pseudomonadota and Ascomycota phyla, followed by Actinomycetota. While most of the biomarker taxa included those exclusively found either in NI or in I roots, LDA scores also indicated that the relative abundance of Rhodotorula was significantly higher in NI roots, while Massilia was significantly higher in I roots.

Furthermore, the functional profiles of each microbiota were predicted by comparing the sequencing data with FAPROTAX database. A total of 8 functional sub-categories within four major categories, “Energy source”, “N-cycle”, “Trophic mode” and “Guild”, were identified and linked to the microbial communities across seeds, NI roots and I roots (Fig. 3B). Compared to seeds and NI roots, I roots harbored higher relative abundance of bacterial OTUs involved in N-cycle functions, specifically in NO₃ respiration/reduction and N fixation, and in Energy source functions, specifically in aerobic chemoheterotrophy. Regarding the fungal microbiota, higher relative abundance of potential pathotrophs was found in the seeds, while their abundance in NI and I roots was generally lower and more variable between replicates. The Guild category was exclusively affected in seeds and I roots, where soil and litter saprotrophs were exclusively linked with the seed or with I roots, respectively, while the abundance of fungal parasites was similar in both environments.

The objectives of this study were to analyze the structure of the endophytic seed-borne microbiota across seeds, NI roots and I roots and to predict whether H. seropedicae inoculation could shift microbial functions towards potential beneficial outcomes for the host plant. Shifts in the structure of the wheat microbiota were stimulated both by the transition of seeds to seedlings and by H. seropedicae inoculation. The bacterial genus Pantoea together with the fungal genera Alternaria, Meyerozyma and Malassezia were found as persistent taxa, suggesting a possible long association and coevolution between these seed-borne endophytes and wheat plants. Different strains from the genus Pantoea and Alternaria have been previously found as a core members across different wheat species and are known to display high metabolic versatility [21, 22]. This feature may allow them to rapidly multiply in the germinating seeds, increasing their legacy in posterior plant developmental stages.

Inoculation with H. seropedicae led to a remarkable shift in the composition of the root wheat microbiota, where it promoted a more diverse microbiota in I roots. The endophytic lifestyle of H. seropedicae likely allows this bacterium to increase its abundance in the endosphere environment and to physically compete for space with indigenous microbiota, including core members such as Pantoea. Active endosphere colonization by endophytic inoculants may contribute to promote microbiota shifts more efficiently compared with non-endophytic ones, which often fail to be effective due to the difficulty of manipulating the highly complex rhizosphere environment [23].

Changes in different genera from the Pseudomonadota phylum have been previously reported for Massilia, Advenella and Brucella, which include different strains that can produce siderophores, solubilize phosphate or increase lateral root number [24, 25]. Shifts in actinobacterial populations have been also reported in response to both inoculants and pathogens, were the abundances of Microbacterium, Curtobacterium or Brevibacterium populations were also differentially impacted [26, 27]. Furthermore, H. seropedicae inoculation led to a marked reduction in the relative abundance of the unicellular yeast Rhodotorula and promoted an increase in the abundance of the genus Filobasidium, suggesting that inoculation may favor fungal populations with diverse reproductive strategies. Some species from the genus Filobasidium can form pseudohyphae which may have mycoparasitic functions and could thus significantly impact microbe-microbe interrelationships within the root microbiota [28].

The prediction of microbial functions associated in NI and I roots pointed to an early imprinting of H. seropedicae on microbiota functionality. Higher biological N fixation capacity in I roots may be attributable to the diazotrophic nature of H. seropedicae, which is known to contain the nifH gene and has been shown to fix N in different cereal species, including rice, sorghum, maize and wheat [29, 30, 31]. However, Pseudomonadota members promoted by H. seropedicae inoculation also contain numerous important intracellular mutualists that may equally contribute to boost N metabolism in planta. For example, members from the genus Massilia or Brevundimonas are known to contain N fixers which can metabolize a variety of nitrogenous compounds [32, 33]. In addition, genera belonging to the Actinmomyetota phylum present in I roots such as Microbacterium or Brevibacterium are also able to fix nitrogen [34, 35]. Furthermore, increased nitrate respiration in the endosphere of I roots may be linked to higher dissimilatory nitrate reduction to ammonium levels, suggesting a potential ecological filtering for more efficient N cycling microorganisms. Considering that microbial N processing is a major determinant of plant productivity and yield, inoculant application could be an effective strategy to push microbial functions towards improved N metabolism, ultimately improving plant growth. For example, promoting an endophytic bacteriome with higher nitrate processing potential within the plant body may help reduce the exogenous application of nitrogen fertilizers, which is often costly and detrimental for the environment due to its accumulation in the ground water [36]. In addition to promote N cycling, H. seropedicae inoculation in I roots treatment promoted a higher proportion of putative chemoheterotrophic bacteria, which may be explained by a higher circulation of organic matter and flow of energy within the I root system [37]. Although this function has been shown to be enriched in rhizosphere environment [38], this is the first report of its potential increased activity in the endosphere, where a higher proportion of bacteria may need to acquire carbon sources and energy by the oxidation of organic compounds, possibly promoting their degradation and increase the nutrient content in the endosphere.

The present study shows that root inoculation with the endophytic bacterium H. seropedicae can be used as a tool to engineer the endosphere microbiota towards potential desirable plant traits in agriculturally relevant crops, such as wheat. Microbiome engineering of major crops through inoculative strategies could help promote new seed generations hosting improved microbiomes, holding a great potential for sustainable crop improvement. In addition, smart delivery strategies in the endosphere using endophytic inoculants may ensure microbiota shifts in a more protected environment, where inoculants as well as the modified microbiota may be sheltered to some extent from the biotic and abiotic stresses of the surrounding environment. This may in turn maximize their chances to be inherited in subsequent seed generations carrying a tailored microbial bank with improved functional repertoire and likely reducing the need to perform further inoculation events in the future.

Author contributions:

PC designed and performed the experiments and wrote the manuscript. EN carried out analyses of microeco package, CC and RT were central parts for the design and supervision of all the sections of this manuscript. PC, CC and RT contributed to the research and approved the final version of the manuscript.

Data availability statement:

Both 16S and ITS sequencing data are in the SRA database through the Bioproject accession ID PRJNA947916.

Competing Interests Statement:

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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No competing interests reported.

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Root inoculation with Herbaspirillum seropedicae RAM10 reveals structural and functional shifts in the wheat seed-borne microbiota associated with improved plant phenotype

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Abstract

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1. Introduction

2. Materials and methods

2.2 Plant growth conditions and treatments

2.3 DNA isolation from plant tissues and 16S rRNA and ITS sequencing

2.4. Data processing and statistical analyses:

3. Results

4. Discussion

5. Concluding remarks and future perspectives

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