Growth promotion and modulation of the soybean microbiome INTACTA RR PRO TM with the application of the fungi Trichoderma harzianum and Purpureocillum lilacinum

Growth promotion and modulation of the soybean microbiome INTACTA RR PRO TM with the application of the fungi Trichoderma harzianum and Purpureocillum lilacinum | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Growth promotion and modulation of the soybean microbiome INTACTA RR PRO TM with the application of the fungi Trichoderma harzianum and Purpureocillum lilacinum Everlon Cid Rigobelo, Lucas Amoroso Lopes Carvalho, Carlos Henrique Barbosa Santos, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4301649/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Sep, 2024 Read the published version in Scientific Reports → Version 1 posted 5 You are reading this latest preprint version Abstract Soybean is a crop of great economic importance for animal and human nutrition. Currently, there is a lack of information on the effects of the fungi Trichoderma harzianum and Purpureocillum lilacinum on the INTACTA RR PRO TM transgenic soybean plants. The present study evaluated the application of the fungi T. harzianum and P. lilacinum under pot and field conditions. Under pot conditions, there were no significant differences in most of the parameters evaluated or in the abundance of the microbiota in the roots. However, under field conditions, the results showed a significant increase in soybean yield at 423. kg. ha − 1 with the application of P. lilacinum compared to the control treatment. In addition, the application of P. lilacinum promoted a significant increase in phosphorus levels in the aerial part, and there were significant correlations between the increase in taxon abundance for the genus Erwinia and productivity and the average phosphorus and nitrogen contents for the aerial part, for the taxon Bacillus and nitrogen content and productivity, and for the taxon Sphingomonas and nitrogen content. The Bradyrhizobium taxon was identified in the P. lilacinum treatment as a linking taxon linking two different networks of taxon and showing itself as an important taxon in the microbiota. The results show that the application of the fungus P. lilacinum can increase the productivity of the soybean INTACTA RR PRO TM and that this increase in productivity may be a function of the modulation of the microbiota composition of the plants leaves by P. lilacinum effect. Biological sciences/Microbiology Biological sciences/Molecular biology Earth and environmental sciences/Environmental social sciences Plant growth-promoting fungi decreased environmental impact sustainability reduction in production cost Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Figure 19 Figure 20 Introduction The soybean crop is of great importance worldwide due to the large supply of vegetable protein for animal production, such as swine and poultry production, and is also used for human consumption in addition to its derivatives, such as soybean oil 1 The largest soybean producers in the world are Brazil and the United States of America (Wang et al., 2020). Soybean is the fifth most produced food in the world and allows farmers high profitability for the maintenance of agricultural activities 3 . The soybean crop, like other agricultural crops, faces several challenges to remain productive and profitable. The problems faced in soybean production are the occurrence of several pathogens and diseases requiring the application of fungicides 4 and insecticide application due to the occurrence of several important pests that cause great economic losses 5 . In addition, there are other factors that hinder soybean production, including various environmental stresses, such as salinity, due to recurrent localized fertilization, such as fertigation in soybean production sites that do not have well-distributed rainfall (Singh, 2021). Water stress due to a lack of rainfall 7 and the presence of heavy metals and contaminants in crop soils promote significant losses in productivity 8 , high temperatures 9 and, consequently, a reduction in agricultural area and a loss of productive potential. Due to the large quantities produced and in large arable areas, soybean production requires large amounts of mineral fertilizers that, when used indiscriminately, promote salinization and contamination of soils, contamination of surface waters with the occurrence of eutrophication and contamination of groundwater with the leaching of nutrients to the ground water 10 . Fungi have diverse and wide genetic and metabolic variability, producing several secondary metabolites that can be used in biotechnological processes and anthropic activities 11 . In addition, the fungi associated with plants can promote plant growth and development, increasing the availability of nutrients in the soil 12 Moreover, plants can increase their ability to absorb water and nutrients 13 , fight pathogens and decrease the incidence of diseases 14 , 15 , fight pests by acting as biocontrol agents 16 and increase their resistance to various types of environmental stresses 17 , 18 . In this sense, the use of filamentous fungi associated with plants is an excellent alternative to face the difficulties related to soybean production, allowing the use of fewer agricultural pesticides and less mineral fertilization and promoting a lower production cost, with lower environmental impact without affecting productivity 14 , 19 – 21 . Among the fungi associated with plants, the filamentous fungus Trichoderma harzianum promotes plant growth and development, such as through mycoparasitism, where the fungus produces several enzymes that degrade the cell wall of pathogenic fungi, in addition to the production of antimicrobial substances that combat and inhibit the growth of pathogenic fungi and decrease the plant diseases by competition for nutrients and colonization niches 22 – 24 . Another fungus associated with plants used in the pest, particularly in the control of nematodes, is the filamentous fungus Purpureocillum lilacinum (Haque et al., 2018; Lan et al., 2017; Zhan et al., 2021). Although the fungus P. lilacinum has been used to control nematodes, a few studies have shown its high potential for use in promoting plant growth (Baron et al., 2019, 2020). In 2010, transgenic soybean was generated with the INTACTA RR2 PRO™ system, which confers tolerance to glyphosate herbicides to aid in the management of weeds that compete with crops. In addition, this soybean cultivar contains the genes that encode B. thuringiensis toxins for the control of the main caterpillars that attack soybeans, which are the soybean caterpillar ( Anticarsia gemmatalis) , apple borer ( Heliothis virescens ) and armpit borer ( Crocidosema aporema ), in addition to the suppression of Elasmo ( Elasmopalpus lignosellus ) and Helicoverpa ( H. zea and H. armigera ) caterpillars 30 . Thus, for the cultivars developed in this system, the cry1Ac gene of B. thuringiensis was added to the inserted genetic modification of the cp4 gene, which is responsible for conferring resistance to glyphosate and one of those responsible for the production of protein crystals with recognized insecticidal action for the cultivar, also commonly called Bt toxin 31 . Although this variety brings several benefits for soybean production, there are few studies on the growth-promoting effects of the fungi T. harzianum and P. lilacinum and on the influence of these fungi on the modulation of the microbiome of the roots and leaves of soybean plants with the INTACTA RR2 PRO™ system. Objective The objective of the present study was to evaluate the potential of the fungi T. harzianum and P. lilacinum to promote the growth of the soybean cultivar INTACT RR PRO TM and the effect of these fungi on the microbiome of the roots and leaves of soybean plants. Materials and Methods Experiment under Greenhouse Conditions The greenhouse experiment was conducted in a randomized block design with 10 treatments, six replicates and three application modes. The greenhouse was maintained at a temperature of 24 ± 2°C, humidity level of 50 ± 2% RH, and light with a cycle of 16:8 h L:D. According to the Köppen and Geiger classification, the climate is classified as Aw, and the soil of the region is a clayey eutrophic red latosol, as reported by Embrapa (1999). The pots used in the experiment were 5 dm³ in size. Description of treatments and modes of application The experiment with the fungi T. harzianum and P. lilacinum on soybean plants under greenhouse conditions was conducted in randomized blocks with 10 treatments, T1 = control (without application of fungi), T2 = P. lilacinum via furrow, T3 = P. lilacinum via foliar, T4 = P. lilacinum via furrow + foliar, T5 = T. harzianum via furrow, T6 = T. harzianum via foliar, T7 = T. harzianum via furrow + foliar, T8 = P lilacinum + T. harzianum via furrow, T9 = P. lilacinum + T. harzianum via foliar and T10 = P. lilacinum + T. harzianum via furrow and foliar. The experiment was conducted in pots for 60 days after sowing. Three application modes were performed with the aid of pipettes for application in the furrow (in the soil near the neck of the plants) and a sprayer for foliar application. Inoculation for both fungi was performed by scraping the spores grown in Petri dishes containing the culture medium maltose agar for 7 days at 28°C. The spore concentration was standardized to 1 × 10 9 spores mL − 1 , and the volume of each fungus was 10 mL. Five milliliters of fungus solution were applied via the furrow or foliar for each type of application for the treatment which received both types. In the treatments that received the mixture of fungi, 10 mL of each fungus was applied. The parameters evaluated were shoot dry mass (SDM), root dry mass (RDM), aerial part nitrogen content (N-SDM), root nitrogen content (N-RDM), phosphorus shoot dry mass content (P-SDM) and phosphorus content root dry mass (P-RDM). After 60 days of planting, the plants were dismantled, and the aerial parts and roots of each plant were carefully separated and conditioned. Five grams was removed from each root for DNA extraction and metagenomic analysis. The plant material was dried in a forced circulation oven at 65°C for three days until a constant weight was reached, after which the material was weighed on an analytical balance. Nitrogen Content in the SDM After the drying process, the SDM were ground in a Wiley mill. The nitrogen content of these materials was determined by sulfuric acid digestion and subsequent titration 32 . Phosphorus Contents in the SDM To determine the phosphorus concentration in the shoot dry matter of the crop, nitric-perchloric digestion of the material was performed, followed by 33 . Experiment under Field Conditions The experiment was conducted in the research area of the Teaching Research and Extension Farm (FEPE) of the Universidade Estadual Paulista - UNESP - Campus de Jaboticabal-SP, located in Prof. Paulo Donato Castellane Road, in the municipality of Jaboticabal – SP, at an average altitude of 575 meters above sea level. The relief is characterized as gently undulating, and its geographical location is latitude 21° 15' 22'' S and longitude 48° 18' 58'' W. The climate is defined as tropical with dry winters and classified as Aw according to the International System of Koppen Classification. The average annual rainfall is 1,425 mm, with a concentration of rainfall in the summer. The soil type is Eutrophic Red. Sowing was performed on December 5, 2023, and the plants were harvested on March 19, 2024. Soil preparation was performed using no-tillage. The soybean cultivar used was INTACTA RR2 PRO TM (Embrapa Company), which belongs to the semiearly maturation group (6.7 North American classification) and has an indeterminate growth habit. For fertilization, 350 kg ha − 1 of the formula 00-20-20 was used in the sowing furrow. Experimental Design The experiment under field conditions was conducted in a randomized block design with the following treatments: T1 = control (without the application of microorganisms); T2 = T. harzianum ; T3 = P. lilacinum; and T4 = T. harzianum + P. lilacinum . Each treatment was replicated four times, and the microorganisms were applied foliage with the aid of a costal pump. The dose of the applied fungi was 300 mL ha − 1 at a concentration of 1 × 10 9 CFU mL − 1 . The spacing between planting rows was 0.5 meters, each plot had an area of 30 m 2 , and the number of plants was approximately 250,000 plants/hectare. Sample collection In the pot experiment under greenhouse conditions, the roots were collected when the pots were poured into a sterilized container, and the soil was loosened from the roots using a sterile metal spatula. For the experiment under field conditions, the collection of leaves was performed manually with the use of surgical gloves, and the leaves were immediately deposited in sterilized plastic containers. Subsequently, for both conditions, roots and leaves were placed in a 50 ml conical tube containing 35 ml of phosphate buffer with 0.02% surfactant (Tween 20). The tubes were vortexed for 2 min to separate the root systems from the rhizosphere. Then, with the aid of sterilized forceps, the roots and leaves were placed on paper towels and transferred to centrifuge tubes (50 ml). Superficial sterilization of roots and leaves was performed according to 34 , with modifications. Plant tissues were maintained in 100% ethanol for 3 min, followed by 2% sodium hypochlorite for 2 min and 70% ethanol for 3 min. The disinfected roots and leaves were washed three times with sterile distilled water, and the last wash was inoculated onto nutrient agar plates to validate the effectiveness of the superficial sterilization procedure. DNA extraction from the roots and leaves of soybean plants The sterilized roots and leaves were macerated with a sterile mortar and pestle with the aid of liquid nitrogen. A PowerMax soil DNA extraction kit (Mo Bio Laboratories, Carlsbad, CA) was used to extract genomic DNA according to the manufacturer’s instructions. The concentration of extracted DNA was determined by fluorometry (Qubit™ 3.0, Invitrogen), and the purity was estimated by calculating the A260/A280 ratio via spectrophotometry (NanoDrop™ 1000, Thermo Fisher Scientific). The V4 hypervariable region of the 16S rRNA gene was amplified with the primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′; 35 . Three forward primers were used for amplification. These primers were modified by adding degenerate nucleotides (Ns) to the 5′ region to increase the diversity of target sequences 36 . PCR was performed in 30 cycles using the HotStarTaq Plus Master Mix kit (Qiagen) under the following conditions: 94°C for 3 min, followed by 28 cycles of 94°C for 30 s, 53°C for 40 s and 72°C for 1 min, and a final elongation step at 72°C for 5 min. PNA clamp sequences (PNA Bio) were added to block amplification of the 16S rRNA gene from ribosomes and mitochondria. The amplification products were analyzed on a 2% agarose gel to determine the success of amplification and the relative intensity of the bands. The sequencing of amplicons was performed on an Illumina MiSeq platform. Data Processing The initial evaluation of the quality of the sequencing data was performed using FastQC software (version 0.11.9) 37 . For a more in-depth analysis, USEARCH (version 11.0.667) was used 38 The "fastx_info" and "fastq_eestats2" functions were used to examine the quality distribution, sequence length and expected errors. The "search_oligodb" function of the same software was used to identify the presence and location of primers 341F ('5-CCTACGGGNGGCWGCAG-3') and 805R ('5-GACTACHVGGGTATCTAATCC-3'), which delimit the V3-V4 region of the 16S gene rRNA in the analyzed sequences. Next, the adjacent primers and barcodes were removed using Atropos (version 1.1.31) 39 . To ensure data quality, Fastp (version 0.23.2) 40 was used to remove sequences with an average Phred quality lower than Q25 using the parameter "average_qual 25". Considering the "paired-end" sequencing approach, the sequences were merged using PEAR (version 0.9.11) 41 , with an overlap criterion of at least 10 base pairs (min-overlap 10). The merged readings were processed through the DADA2 pipeline 42 The dada2 package (version 1.22.0) was used for integration with R statistical software (version 4.1.2) 43 . The procedure began with the filtering and truncation of the readings by the "filterAndTrim" function, adopting an expected error limit of 2 ("maxEE = 2"). Subsequently, the error probabilities were estimated on a basis using the "learnErrors" function. Based on this error model, the sequences were corrected using the "dada" function, resulting in the identification of the amplicon variant sequences (ASVs) specific to each sample. These ASVs were analyzed for the removal of possible chimeric sequences using the "removeBimeraDenovo" function. For taxonomic classification, the ASVs were compared with the SILVA database (version 138.1) 44 , allowing taxonomic identification down to the level of bacteria or archaea. ASVs not classified as such or identified as potential contaminants, including chloroplast and mitochondrial sequences, were excluded from the analysis. The counts and taxonomic annotations of the VSAs were exported in the "phyloseq" format (R package "phyloseq"; version 1.38.0) 45 . The phyloseq data were then transformed into compositional data by the function "phyloseq_standardize_otu_abundance" of the R package "metagMisc" (version 0.04) 46 for microbiome analyses. Descriptive and Statistical Analysis of the Microbiome The efficiency of the sampling was evaluated by means of rarefaction curves using "amp_rarecurve" analysis of the R package "ampvis2" (version 2.7.17) 47 . After that, the samples were subjected to rarefaction based on the lowest number of sequences found in a library (n = 346,844), and the analyses were conducted using the tables resulting from this rarefaction. Alpha diversity was quantified by examining both species richness (observed and estimated by the Chao1 index) and diversity (Shannon and Gini Simpson indices) using the "alpha" function of the R package "microbiome" (version 1.16.0) 48 . For the comparative analysis of the means, ANOVA was applied, establishing a confidence interval of 95% (p value < 0.05). Complementary statistical analyses, including post hoc multiple comparisons between treatments, were performed with the "emmeans" function (R package "emmeans"; version 1.8.9) 49 , adjusting the p values using the false discovery rate (FDR) method. Beta diversity analysis was performed by calculating the Bray‒Curtis dissimilarity between the samples using the "distance" function of the "phyloseq" R package. To determine whether there were significant differences between treatments, PERMANOVA was used, using the "adonis" function of the "vegan" R package (version 2.6.2) 50 The significance level was established at a p value < 0.05. For the interpretation of the multidimensional distances, a principal coordinate analysis (PCoA) was performed, and the results were visualized in subsequent graphs. The identification of differentially abundant taxa among the treatments was performed using the DESeq2 methodology (package R version 1.34.0) 51 A negative binomial model was used to compare the means via the Wald test (adjusted p value < 0.05). The visualizations of the aforementioned analyses were prepared in R using the "ggplot2" package (version 3.3.6) 52 . Structural Analysis of the Microbiome To evaluate the structural characteristics of microbial communities in response to different treatments, an analysis of co-occurrence networks was performed at the genus level. Pearson's correlation coefficients were calculated using the "corr.test" function of the "psych" R package (version 2.2.5) 53 . Only significant correlations (p value < 0.05) with a minimum Pearson coefficient of ± 0.75 were considered, with a focus on strongly positive or negative relationships. Additionally, to reduce noise and focus on relevant genera, only those with a mean relative abundance of at least 0.001% in at least one treatment were included. The construction of the networks and the analysis of their topological properties were performed using the R package "igraph" (version 1.3.4) 54 . The topological properties included the total number of correlated genera (number of nodes), total number of links (edges), average and maximum degrees, modularity, number of modules, clustering coefficient, and measures of average and centrality between maxima. The main "hubs" were identified by calculating the "Kleinberg's hubbiness score" 55 , highlighting the genres with the greatest influence on the Results Greenhouse experiment In the experiment conducted under greenhouse conditions with 10 treatments and six replicates, the results showed that the shoot dry mass varied between 5.02 and 15.03 grams and that the treatments did not differ from each other (p > 0.05) according to the 5% Duncan test (Fig. 1 A). The root dry mass ranged between 0.46 and 2.00 grams, and the values also did not differ from each other (p > 0.05) ( Fig. 1 B). The highest mean values (p < 0.05) of nitrogen levels in the SDM were found in treatments T5 ( T. harzianum furrow application) and T6 ( T. harzianum foliar application), followed by treatments T1 (control), T3 (P. lilacinum via foliar) and T7 ( T. harzianum via furrow + foliar). The lowest nitrogen contents were found in treatments T2 ( P. lilacinum via furrow), T8 ( P. lilacinum + T. harzianum via furrow), T9 ( P. lilacinum + T. harzianum via foliar) and T10 ( P. lilacinum + T. harzianum furrow + foliar) (Fig. 2 A). Regarding the average of phosphorus content in the SDM, the highest values were found in treatment T10 ( P. lilacinum + T. harzianum via furrow and foliar), followed by treatments T1 (control) and T5 ( T. harzianum via furrow), T6 ( T. harzianum via foliar) and T7 ( T. harzianum via furrow and foliar). Treatments T4 ( P. lilacinum via foliar) and T8 ( P. lilacinum + T. harzianum via furrow) had lower average phosphorus contents (Fig. 2 B). The highest mean values of nitrogen from the root were found in the T8 treatment ( P. lilacinum + T. harzianum via furrow) compared to the T2 treatment. ( P. lilacinum via furrow). The other treatments did not differ (p > 0.05) from each other (Fig. 3 A). There was no significant difference (p > 0.05) between the treatments and the control treatment (Fig. 3 B). Regarding the diversity of endophytic bacteria from the roots of soybean plants, inoculations of the fungi P. lilacinum and T. harzianum performed in the experiment under greenhouse conditions showed no difference between the treatments. The bacterial genera found most frequently in the treatments were Pseudomonas sp., Salmonella sp., Rhizobium , Rhizobiaceae , Agrobacterium and Stenotrophomonas . The bacterial genera and species least abundant in the treatments were Achromobacter , Pantoa dispersa and bentonitic Stenotrophomonas (Fig. 4 ). There was no significant difference (p > 0.05) in the diversity of endophytic fungi isolated from the roots in the pot experiment under greenhouse conditions. The fungal genera and species present in greatest quantities were Fusarium , F. oxysporum , Plectosphaerella and Curvularia . The genera and species that were found in smaller numbers were Mythecium inundatum , Chaetomium globosum , Fusarium suflorianum and Saccharomyces (Fig. 5 ). The mean values found in the split analysis with two factors, factor 1 (fungal species, T. harzianum ; P. lilacinum and T. harzianum + P. lilacinum ) and factor 2 (application methods, furrow, foliar and furrow + foliar), under potted conditions showed no difference (p > 0.05) for the parameters of SDM (Fig. 6 ), nitrogen content from SDM (Fig. 7 ) or phosphorus content from SDM (Fig. 8 ). Experiment under field conditions The highest values for SDM under field conditions were found in treatments T2 ( T. harzianum ), T3 ( P. lilacinum ) and T4 ( T. harzianum + P. lilacinum ) compared with the control treatment T1, which had the lowest value (p < 0.05) (Fig. 9 ). There was no significant difference (p < 0.05) in nitrogen content between the treatments based on SDM (Fig. 10 A). Nevertheless, the phosphorus content was the highest in the T3 treatment, which utilized P. lilacinum (Fig. 10 B). The most abundant phylum was Pseudomonas , and the percentages in the T1 (control), T2 ( T. harzianum ), T3 ( P. lilacinum ) and T4 ( T. harzianum + P. lilacinum ) treatments were 44.93%, 29.18%, 20.01% and 53.88%, respectively. The second most abundant genus was Bradyrhizobium at 31.24%, 33.482%, 44.72%, and 17.43%, and the third most abundant genus was Enterobacter at 16.77%, 24.50%, 25.552%, and 24.377%, respectively (Fig. 11 ). Interestingly, there was a significant difference in the number of species between treatments T1 (control), T2 ( T. harzianum ), T3 ( P. lilacinum ) and T4 ( T. harzianum + P. lilacinum ), with 70, 50, 13 and 29 species, respectively. Comparative analysis between treated samples (T2 to T4 treatments) and control samples (T1 treatment) revealed a total of 77 differentially abundant taxa (DA), categorized into 2 phyla, 4 classes, 5 orders, 19 families, and 26 genera. Among these, 58 taxa were predominantly more abundant in the T1 treatment (control), while 6, 4 and 9 taxa were more abundant in the T2 ( T. harzianum ), T3 ( P. lilacinum ) and T4 ( T. harzianum ) treatments. + P. lilacinum ), respectively. The DA taxa at the genus level are visualized in Fig. 13 . Notably, with the exception of Kosakonia , all other affected genera exhibited a relative abundance lower than 1%. Genera such as Oligoflexus , Achromobacter , Shinella and Sphingobacterium were differentially abundant in the T1 treatment (control) in multiple comparisons. Notably, the genus Luteibacter was also differentially abundant in treatments T2 ( T. harzianum ) and T4 ( T. harzianum + P. lilacinum ). The greatest differences (log2-fold changes) were observed in the absence of genus in the opposite treatment. However, the greatest variations in terms of relative abundance were recorded for Kosakonia , which was significantly more abundant in T3 ( P. lilacinum ) (3.6%) than in T1 (control) (0.08%), and Siccibacter , which was more abundant in T1 (control) (0.81%) than in T2 ( T. harzianum ) (0.003%). Principal coordinate analysis (PCoA) based on Bray‒Curtis distances was applied to investigate the microbial composition of the samples under different treatments. The results indicate a trend toward a significant separation of the samples as a function of the treatments, although the p value is marginally above the significance threshold ( p value = 0.051). The dimensionality reduction performed by PCoA was able to explain 76.07% of the total variability observed in the samples based on the first three main axes (Fig. 14 ). Although considerable variability was observed within the groups and some overlap between them, post hoc analyses indicated trends of significant compositional differences between treatments, particularly between T3 ( P. lilacinum ) and T4 ( T. harzianum + P. lilacinum ) (p value = 0.028), as well as between T1 (control) and T3 ( P. lilacinum ) (p value = 0.058). These results suggest the existence of distinct patterns in the microbial composition associated with each treatment, reflecting the specific influence of each intervention on the microbial community from the leaves of soybean plants. Venn diagram analysis (Fig. 15 ) revealed significant sharing of taxa at the higher taxonomic levels, with 12 phyla and 98 genera identified as common among all treatments. However, the comparison at the level of ASVs showed a distinct pattern, with only 59 ASVs out of a total of 2,207 being shared by all treatments. This result suggested conservation of the main taxonomic groups among the treatments, while the differences in the ASV indicated significant variations in the population composition. Regarding the presence of exclusive taxa, there was a trend in which the control treatment (T1) had the greatest number of unique taxa, followed by treatments T3 ( P. lilacinum ), T2 ( T. harzianum ) and, finally, T4 ( T. harzianum + P. lilacinum ), which were consistent at all the taxonomic levels analyzed. The structuring of the microbiomes of the samples was inferred from the co-occurrence networks of the different treatments. There were changes in the relationships between the identified genera (Fig. 16 ). In this sense, treatment T1 (control) had a greater number of correlated genera ("N. of nodes") and correlations ("N. of edges"). Although this treatment had more than twice the amount of bonding compared to the other treatments, treatments T2 ( T. harzianum ) and T3 ( P. lilacinum ) presented a greater number of negative bonds ("negative edges"), with 57 and 71, respectively, against only 25 in T1 (control). The characteristics of T1 (control) are mainly due to the presence of a cluster with a large number of correlations, reflecting higher means of connections ("Mean degree") and average and maximum potential of betweenness/Max. betweenness"). This is further reinforced by the high number of key taxa ("main hubs") found for this treatment. In general, treatments with fungal inoculants showed reduced binding, increased negative binding (except for T4 ( T. harzianum + P. lilacinum ) and a reduction in the number of key taxa, which in turn differed between the treatments. These observations suggest that treatments differentially influence the structure and dynamics of microbial communities, altering the patterns of co-occurrence and the relative importance of certain taxa within the networks. The highest mean yield value (p 0.05) from each other (Fig. 17 ). The correlation between the taxonomic groups showed that some genera had a positive and significant correlation with some plant growth parameters. Specifically, for productivity, the genera Erwinia and Bacillus followed the genus Blautia (Fig. 18 ). Treatment T3 ( P. lilacinum ) was the only treatment that promoted increased productivity compared to the other treatments (Figs. 17 and 19 ). The parameters that were significantly influenced by the T3 treatment ( P. lilacinum ) were the phosphorus concentration in SDM, productivity and nitrogen content (Fig. 20 ). Discussion Experiment under Greenhouse Conditions The results showed that soybean growth did not increase when the plants were inoculated with the fungi T. harzianum and P. lilacinum alone or in combination under greenhouse conditions. There was no difference in SDM or RDM (Fig. 1 A and B ). In general, there were no significant increases in nitrogen levels with the application of the fungi P. lilacinum or T. harzianum . Studies under controlled conditions, such as those conducted in pots in greenhouses, have several advantages, such as the attribution of results to the microorganisms evaluated and the ease of replicability of the results. The reasons why the fungi did not promote growth were not identified; however, under controlled conditions, with little variation in temperature and without water or nutritional stress, there is strong evidence that the optimal growth conditions of soybean provided by greenhouse condition may have decreased the interaction between plants and fungal microorganisms since this interaction is usually strengthened by adverse environmental conditions and not by appropriate environmental conditions 56 . Since the emergence of plants, microorganisms interact with them, increasing the availability and absorption capacity of water and nutrients and increasing resistance to adverse biotic and abiotic factors. Interestingly, the same fungus, P. lilacinum , promoted an increase in soybean yield under field conditions but did not promote increases in any other biometric parameters of the plant under pot conditions. This inconsistency of results usually occurs with the application of microorganisms, often due to environmental conditions and not due to the microorganism. Interestingly, there was a tendency for the mixture of the two fungi P. lilacinum + T. harzianum to decrease the nitrogen levels in the SDM compared to the application of T. harzianum alone. Most likely, the mixture of fungi caused losses in nitrogen absorption (Fig. 2 A). This was due to the lower values found in treatments T8 ( P. lilacinum + T. harzianum via furrow), T9 ( P. lilacinum + T. harzianum via foliar) and T10 ( P. lilacinum + T. harzianum via furrow and foliar), which received inoculation of the two fungi P. lilacinum and T. harzianum , compared with treatments T5 ( T. harzianum via furrow), T6 ( T. harzianum via foliar) and T7 ( T. harzianum via furrow + foliar), which received only the inoculation of T. harzianum . Probably the fungus P. lilacinum could decrease the action of another fungus when applied as a mixture. A study revealed that the application of the fungus P. lilacinum , despite reducing the incidence and severity of rust in tomato plants caused by the fungus Phytophthora capsici , in combination with the fungus Funneliformis caledonium promoted a reduction in its efficiency in the inhibition of the disease compared with the application of the fungus F. caledonium alone(Hu et al., 2020). Other studies used mixtures of different fungi, such as Beauveria bassiana , T. harzianum , Pochonia chlamydosporia and P. lilacinum , and although the fungus P. lilacinum did not increase the effect of the application of the other fungi, there was no evidence of antagonistic effects. On the other hand, the results showed that the application of P. lilacinum alone increased few parameters, such as root dry matter, in common bean plants 58 .The application of P. lilacinum to pineapple plants also promoted root growth compared to that in the control treatment 59 . In these studies, there was no antagonistic effect when the fungus P. lilacinum was applied together with other fungi to the plants. However, the results of the present study suggest that caution should be taken when mixing the fungus P. lilacinum with other fungi to promote plant growth. Regarding the influence of the application of the two fungi T. harzianum and P. lilacinum on the microbiota of soybean roots, the results showed that although there was a high number of taxa for Pseudomonas , Salmonella and Rhizobium , there was no significant difference in relation to the diversity of these bacteria under the treatments (Fig. 4 ). The genus Pseudomonas is commonly found in soybean roots, and several studies have shown that certain Pseudomonas species in soybean have growth-promoting effects, induction of systemic resistance and modulation of the root microbiome with growth-promoting effects on plants 60 – 62 . The genus Salmonella has several species of bacteria that are pathogenic to animals and humans. Although there are no reports of Salmonella promoting the growth of soybean plants, colonization of this bacterium in roots is relatively common and occurs due to the ability of the bacterium to suppress the defense mechanisms of the soybean plant 63 . The presence of this genus indicates that it is likely an opportunistic bacterium originating from bird feces. Among the endophytic fungi identified, Fusarium, F. oxysporum, Plectosphaerella and Curvularia were the most prevalent. However, there was no significant difference between treatments (Fig. 5 ). Interestingly, although T. harzianum and P. lilacinum were inoculated into soybean plants, these fungi were not identified as endophytic in the roots. Although some studies have shown the ability of T. harzianum to colonize soybean roots in an endophytic way, the fungi T. harzianum and P. lilacinum were isolated from the soil environment and probably do not have an affinity for endophyticism 29 The values of the splitting showed that for the parameters of the SDM, RDM and the contents of nitrogen and phosphorus were not altered in relation to the application of the two fungal species or the mixture of both fungi. There was also no difference in the parameters evaluated in relation to the three modes of application (fungi, furrows, foliar and a mixture of furrows and foliar) (Figs. 6 – 8 ). These results reinforce that although a microorganism has several abilities related to the promotion of plant growth, depending on the environmental conditions, this effect does not occur. Generally, when there is no stress environment, plant‒microbe interactions decrease in intensity, and thus, the effect of microorganisms on plants also decreases 64 Field Experiment All treatments promoted an increase in SDM and RDM compared to the control treatment, which did not receive fungal inoculation. With the exception of the control treatment, the other treatments did not differ from each other (Fig. 9 ). Interestingly, these fungi did not promote an increase in SDM, and there was no increase in RDM under potted conditions, as previously mentioned. In contrast, the experiment was performed under field conditions. The evaluated fungi produce phytohormones that promote the development of roots and shoots, increasing soil exploitation efficiency and photosynthetic efficiency and contributing to increased resistance to abiotic stresses and plant growth 65 , 66 There was no difference in the nitrogen content of the SDM between treatments (Fig. 10 A); however, treatment T3 ( P. lilacinum ) increased the phosphorus content of the SDM. The other treatments did not differ from each other (Fig. 10 B) in the selection of these same fungal isolates, showed the potential use of these fungi to promote growth in maize, common beans, and soybean plants with increases in the average levels of nitrogen and phosphorus in the plants 29 . Interestingly, the evaluations performed for the selection of these fungi were also performed under pot conditions, and unlike the present study, the results were significant for the parameters analyzed. It is crucial to emphasize that the environmental parameters of the greenhouse in which these fungi were isolated varied from those employed in the present investigation. A few studies have shown that the fungus P. lilacinum promotes increased nutrient levels in plants. Although the fungus P. lilacinum increased the levels of nitrogen, phosphorus, manganese, copper, zinc and boron in the SDM of bean plants, the fungus did not significantly affect the activity of the enzyme arylsulfatase or the solubilization of phosphorus in the soil. These results suggest that the fungus has the ability to increase the ability of plants to absorb these nutrients rather than increasing the availability of these nutrients in the soil 58 , 67 , 68 . According to the taxonomic profile, the T3 treatment ( P. lilacinum ) increased the prevalence of Bradyrhizobium and the bacterium Kosakonia cowanii (Fig. 13 ). However, there was no significant difference compared to the other treatments. Interestingly, Bradyrhizobium behaved as a common taxon for treatments T2 ( T. harzianum ) and T4 ( T. harzianum + P. lilacinum ), but for treatment T3 ( P. lilacinum ), Bradyrhizobium was a binding taxon linking two distinct networks (Fig. 16 ) . Treatment T3 ( P. lilacinum ) was the only treatment that promoted increased soybean productivity under field conditions compared to the control treatment (Figs. 11 and 17 ). Further research is necessary to confirm whether the application of the fungus P. lilacinum is able to increase the abundance of Bradyrhizobium in soybean plants. In addition, there were positive and significant correlations for yield, SDM, averages of nitrogen and phosphorus contents with increasing abundance of Erwinia bacterium, and average of nitrogen contents and yield with increased abundance of Bacillus and for mean nitrogen contents to increase the abundance of Sphingomonas . The genus Sphingomonas includes bacteria that can produce phytohormones and volatile organic compounds, and some studies have shown that Sphingomonas can promote plant growth 69 , 70 . The genus Erwinia has several bacterial species classified as plant pathogens. However, this genus also harbors species reported to promote plant growth. A study revealed a new strain of bacteria, called A4, from almond tree leaves that may promote plant growth by increasing access to nutrients and producing a stress-reducing compound called spermidine. This bacterium has been reported to have potential for use in various crops to improve productivity and sustainability in agriculture. The bacterium Erwinia A4 was also shown to successfully colonize the Arabidopsis thaliana model plant, spreading from the roots to aerial parts such as leaves and flowers, indicating its ability to live inside the plants and potentially benefit them by promoting plant growth. Genome analysis of the bacterium Erwinia A4 revealed unique genes that may contribute to its ability to promote plant growth, including those involved in the synthesis of spermidine, a compound known to help plants cope with stress. Experiments showed that plants treated with A4 had a 30% greater fresh mass than untreated plants, suggesting that A4 significantly increases plant growth 71 . In general, the treatments with the fungi T. harzianum and P. lilacinum showed a reduction in the number of links, an increase in the number of negative links (except for T4) and a reduction in the number of key taxa, which in turn differed between treatments. These observations suggest that treatments differentially influence the structure and dynamics of microbial communities, altering the patterns of co-occurrence and the relative importance of certain taxa within the networks. These results suggest the existence of distinct patterns in the microbial composition associated with each treatment, reflecting the specific influence of each intervention on the microbial community of the leaves of soybean plants. Plant growth is influenced by numerous factors, and it is intriguing to consider how these factors interact with each other. One of the key factors affecting plant growth is the plant microbiome. Thus, the plant microbiome can be used as an effective strategy to enhance plant growth. However, altering the microbiome to promote plant growth is challenging. These results suggest that microbial inoculations that increase the negative co-occurrence of certain taxa can promote plant growth. Further research is required to elucidate the impact of the increased negative co-occurrence resulting from microbial inoculation on the overall plant microbiome. Additionally, it remains to be determined whether the decrease in the entire microbiome is a justifiable reason for promoting plant growth. In other words, it needs to be better elucidated if to enhance plant growth, the influence of certain taxa on the microbiome must be decreased. As previously mentioned, compared with the control treatment, the T3 treatment ( P. lilacinum ) promoted an increase in soybean yield. Yield is influenced by several factors, and in a complex way, this increase may have been due to the various changes promoted by the application of the fungus P. lilacinum to soybean plants, such as all the aforementioned changes in the composition of the leaf microbiome and the increase in phosphorus levels in leaves. Conclusion The results of the present study show that it was possible to significantly increase the productivity of the transgenic soybean INTACTA RR PRO TM with the application of the fungus P. lilacinum and that this increase in productivity may have occurred due to a set of several factors that were influenced by the application of the fungus P. lilacinum , such as the increase in the phosphorus content in the SDM; the Erwinia, Bacillus and Sphingomonas taxon increase in the leaves; their positive and significant correlations with the productivity and the average phosphorus and nitrogen contents in the SDM; and the promotion of the genus Bradyrhizobium as a linking taxon of other taxon networks. Furthermore, it is important to note that the same fungus, P. lilacinum , applied under pot conditions did not increase the growth of soybean plants. These results help to explain several inconsistencies in the results found in the application of these fungi and reinforce the importance of the environment in the expression of the abilities of the microorganisms and in the effective action of these microorganisms as promoters of plant growth and in the aid of more sustainable agricultural production. Declarations Experimental research and field studies on plants (either cultivated or wild), including the collection of plant material, must comply with relevant institutional, national, and international guidelines and legislation. The soybean cultivar is a business cultivar sold across the country and this cultivar is registered with the Ministry of Agriculture, Livestock and Supply. Author Contribution All the authors have contributted in this study in the same way. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4301649","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":296942089,"identity":"8d8f7cf8-0a92-442d-95a5-8e63d2df92d5","order_by":0,"name":"Everlon Cid 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Ath, Belgium.","correspondingAuthor":false,"prefix":"","firstName":"Nicolas","middleName":"","lastName":"Desoignies","suffix":""}],"badges":[],"createdAt":"2024-04-21 17:09:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4301649/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4301649/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-71565-2","type":"published","date":"2024-09-09T15:57:13+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":55571490,"identity":"69ece52c-e4e0-4641-8b96-16787f9a659f","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25074,"visible":true,"origin":"","legend":"\u003cp\u003eMean shoot dry mass \u003cstrong\u003e(A)\u003c/strong\u003e and root dry mass \u003cstrong\u003e(B)\u003c/strong\u003e of soybean plants of the\u003cstrong\u003e \u003c/strong\u003eINTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e variety in the different treatments.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eT1\u003c/strong\u003e = control (no fungal application), \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via furrow, \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via foliar, \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via furrow + foliar, \u003cstrong\u003eT5\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via furrow, \u003cstrong\u003eT6\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via foliar, \u003cstrong\u003eT7\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via furrow + foliar, \u003cstrong\u003eT8\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow, \u003cstrong\u003eT9\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via foliar and furrow \u003cstrong\u003eT10\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow and foliar.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/acdb1f19fa73b2df24e4e471.png"},{"id":55571945,"identity":"633744ea-4002-4a48-ab19-b51fa9b932a1","added_by":"auto","created_at":"2024-04-30 05:42:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":127818,"visible":true,"origin":"","legend":"\u003cp\u003eMean values of nitrogen \u003cstrong\u003e(A)\u003c/strong\u003e and phosphorus \u003cstrong\u003e(B)\u003c/strong\u003e in the aerial parts of INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e soybean plants in the different treatments.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eT1\u003c/strong\u003e = control (no fungal application), \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via furrow, \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via foliar, \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via furrow + foliar, \u003cstrong\u003eT5\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via furrow, \u003cstrong\u003eT6\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via foliar, \u003cstrong\u003eT7\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via furrow + foliar, \u003cstrong\u003eT8\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow, \u003cstrong\u003eT9\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via foliar and furrow \u003cstrong\u003eT10\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow and foliar.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/a34a2ce57e77db0d57902291.png"},{"id":55571491,"identity":"9ea098c3-a4f1-4906-b521-6e39bf803138","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38053,"visible":true,"origin":"","legend":"\u003cp\u003eMean values of nitrogen \u003cstrong\u003e(A)\u003c/strong\u003e and phosphorus \u003cstrong\u003e(B)\u003c/strong\u003e in roots of INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e soybean plants in the different treatments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e = control (no fungal application), \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via furrow, \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via foliar, \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via furrow + foliar, \u003cstrong\u003eT5\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via furrow, \u003cstrong\u003eT6\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via foliar, \u003cstrong\u003eT7\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via furrow + foliar, \u003cstrong\u003eT8\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow, \u003cstrong\u003eT9\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via foliar and furrow \u003cstrong\u003eT10\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow and foliar.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/07187eef319b263bfa7a123a.png"},{"id":55571499,"identity":"ba0d51b0-f83d-412e-a1c2-427bd7b117f2","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":154321,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic affiliation at the species level of endophytic bacteria from the roots of INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e soybean plants under different treatments inoculated with the fungi \u003cem\u003ePurpureocillum\u003c/em\u003e and \u003cem\u003eTrichoderma\u003c/em\u003e under greenhouse conditions.\u003c/p\u003e\n\u003cp\u003ePu = \u003cem\u003eP. lilacinum\u003c/em\u003e; FRW = furrow; FLR = foliar; Tr= \u003cem\u003eT. harzianum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/a8e9a726d3cd10b66dc6172d.png"},{"id":55571946,"identity":"254c5945-c272-408d-889d-b5ab2e3c1228","added_by":"auto","created_at":"2024-04-30 05:42:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":106057,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic affiliation at the species level of endophytic fungi isolated from the roots of INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e soybean plants under different treatments inoculated with the fungi \u003cem\u003ePurpureocillum\u003c/em\u003e and \u003cem\u003eTrichoderma\u003c/em\u003e under greenhouse conditions.\u003c/p\u003e\n\u003cp\u003ePu = \u003cem\u003eP. lilacinum\u003c/em\u003e; FRW = furrow; FLR = foliar; Tr= \u003cem\u003eT. harzianum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/5afa99c65e36d612302a45c1.png"},{"id":55571497,"identity":"d4786750-43e1-4cf9-ad25-415cba1fd027","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":24410,"visible":true,"origin":"","legend":"\u003cp\u003eUnfolding of the average shoot dry matter (SDM) values of INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e soybean plants in the different treatments \u003cstrong\u003e(A)\u003c/strong\u003e of the treatments with inoculation of the fungi \u003cem\u003eT. harzianum\u003c/em\u003e, \u003cem\u003eP. lilacinum\u003c/em\u003e and the mixture \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e and the forms of application \u003cstrong\u003e(B)\u003c/strong\u003e of sulcus, foliar and the mixture of sulcus + foliar.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eT1\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eF1\u003c/strong\u003e = furrow application; \u003cstrong\u003eF2\u003c/strong\u003e = foliar application; and \u003cstrong\u003eF3\u003c/strong\u003e = furrow and foliar application.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/6986c0fca6c24d636fd4efda.png"},{"id":55571510,"identity":"7029dede-766a-4598-bc98-0f332a108e9b","added_by":"auto","created_at":"2024-04-30 05:34:58","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":33709,"visible":true,"origin":"","legend":"\u003cp\u003eUnfolding of the\u003cstrong\u003e \u003c/strong\u003eaverage nitrogen contents of the shoot dry matter of the INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e soybean plants in the different treatments \u003cstrong\u003e(A)\u003c/strong\u003e of the treatments with the inoculation of the fungi \u003cem\u003eT. harzianum\u003c/em\u003e, \u003cem\u003eP. lilacinum\u003c/em\u003e and the mixture \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e and of the forms of \u003cstrong\u003e(B)\u003c/strong\u003e sulcus, foliar application and of the sulcus + foliar mixture.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eT1\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eF1\u003c/strong\u003e = furrow application; \u003cstrong\u003eF2\u003c/strong\u003e = foliar application; and \u003cstrong\u003eF3\u003c/strong\u003e = furrow and foliar application.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/4a152188831943dc1c4ada72.png"},{"id":55571506,"identity":"40bc1f69-40d1-4b02-aa1f-038c12315478","added_by":"auto","created_at":"2024-04-30 05:34:57","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":29516,"visible":true,"origin":"","legend":"\u003cp\u003eUnfolding of the average phosphorus contents of the shoot dry matter of the aerial part of the soybean plant INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e in the different treatments \u003cstrong\u003e(A)\u003c/strong\u003e of the treatments with the inoculation of the fungi \u003cem\u003eT. harzianum\u003c/em\u003e, \u003cem\u003eP. lilacinum\u003c/em\u003e and the mixture of \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e and the forms of application \u003cstrong\u003e(B)\u003c/strong\u003e of sulcus, foliar and the mixture of sulcus + foliar.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eF1\u003c/strong\u003e = furrow application; \u003cstrong\u003eF2\u003c/strong\u003e = foliar application; and \u003cstrong\u003eF3\u003c/strong\u003e = furrow and foliar application.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/5bf01ae762f117bd87b4b520.png"},{"id":55571495,"identity":"8aaf64aa-1ab4-4afe-87ac-a8c04fc55e02","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":20289,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e = Control; \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMean values of the SDM of the soybean plant INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e in the different treatments with the application of the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/0260c7afdce2965fc2b06f09.png"},{"id":55571492,"identity":"2d4206e5-ad50-4c72-a689-47a7940a25cb","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":53352,"visible":true,"origin":"","legend":"\u003cp\u003eMean nitrogen content of the shoot part dry mass \u003cstrong\u003e(A\u003c/strong\u003e) and mean phosphorus content \u003cstrong\u003e(B)\u003c/strong\u003e of the soybean plant INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e in the different treatments with the application of the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e = Control; \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/f8a7e3ae6981845e08c7a7bc.png"},{"id":55571509,"identity":"2d145e43-0aa9-4318-9ae2-52f4ced680f1","added_by":"auto","created_at":"2024-04-30 05:34:57","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":111428,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic profile of the relative abundance of species-level endophytic bacteria on the leaves of INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e soybean plants in the different treatments inoculated with the fungi \u003cem\u003eP. lilacinum\u003c/em\u003e and \u003cem\u003eT. harzianum.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1 = Control; T2\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/c5a008d25f4b616f106f019b.png"},{"id":55571505,"identity":"db0a1ba6-89fe-4200-818b-7331202bef05","added_by":"auto","created_at":"2024-04-30 05:34:57","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":91611,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic affiliation at the species level of endophytic fungi of the leaves of INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e soybean plants in the different treatments inoculated with the fungi \u003cem\u003eP. lilacinum\u003c/em\u003e and \u003cem\u003eT. harzianum.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1 = Control; T2\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage12.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/0be1739dc672a959fac780de.png"},{"id":55571504,"identity":"eadbc783-0edc-4c85-8fd7-e3055b3c9ca8","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":65549,"visible":true,"origin":"","legend":"\u003cp\u003eDifferentially abundant (AD) genera among treatments. The graphs show, on the left, the relative abundance and, on the right, the mean intensity of difference (log2-fold change) of the genera that showed statistically significant differences between treatments (adjusted p value \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage13.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/65086cf838af4f2d46d94eb9.png"},{"id":55571496,"identity":"b9fec255-a239-410b-b6b1-9c19d6d354be","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":61305,"visible":true,"origin":"","legend":"\u003cp\u003eBeta diversity analysis via PCoA. The dispersion of the samples based on the Bray‒Curtis distances through the combinations of the axes PCoA 1 and 2 (left) and PCoA 1 and 3 (right). The figure highlights the differences in the microbial composition of soybean leaves between treatments.\u003c/p\u003e","description":"","filename":"floatimage14.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/32a6afcb22c9a8b1bf2ea2a3.png"},{"id":55571493,"identity":"64da4298-ce37-4a06-b7fb-5cf85746f549","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":37342,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram of taxonomic sharing between treatments. Sharing of phyla (A), genera (B) and ASVs (C) among the different treatments. Each set represents the unique and shared diversity of taxonomic categories, providing information on overlaps and exclusivity among treatments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e= Control; \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage15.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/d8f8d76a75aa7a8e3ca47e2b.png"},{"id":55571502,"identity":"2b112b48-3d5d-4a36-a943-18823f1b0a98","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":262534,"visible":true,"origin":"","legend":"\u003cp\u003eGenera co-occurrence networks by treatment. Co-occurrence networks of the identified genera, based on Pearson's correlation coefficients (r = ±0.75) and a 95% confidence level (p value \u0026lt; 0.05). Positive connections are highlighted in blue, and negative connections are highlighted in red, while the filled color of the nodes indicates the phylum to which the genus belongs. Critical nodes for the structure of the network (articulation points) are emphasized with an external contour, emphasizing their importance in the connectivity between submodules of the network.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e= Control; \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage16.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/d059cfdfc34a25e0216e22c1.png"},{"id":55571498,"identity":"1b9ede6e-7ba0-498d-aa5b-35b3981e995f","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":17,"title":"Figure 17","display":"","copyAsset":false,"role":"figure","size":26461,"visible":true,"origin":"","legend":"\u003cp\u003eSoybean yield in tons per hectare of the soybean variety INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e under field conditions among the different treatments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1\u003c/strong\u003e = Control; \u003cstrong\u003eT2\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cstrong\u003eT3\u003c/strong\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e; \u003cstrong\u003eT4\u003c/strong\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage17.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/bdfc3d7114594d5f4b0119b9.png"},{"id":55571503,"identity":"569bb48a-89de-4b85-8c12-203c8fac76d6","added_by":"auto","created_at":"2024-04-30 05:34:56","extension":"png","order_by":18,"title":"Figure 18","display":"","copyAsset":false,"role":"figure","size":143189,"visible":true,"origin":"","legend":"\u003cp\u003ePearson correlation between the analyzed parameters and the abundance of taxa.\u003c/p\u003e","description":"","filename":"floatimage18.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/16e890756bb7c58f844848d7.png"},{"id":55571508,"identity":"022365ed-f7a9-466d-8057-aef7ee75c13c","added_by":"auto","created_at":"2024-04-30 05:34:57","extension":"png","order_by":19,"title":"Figure 19","display":"","copyAsset":false,"role":"figure","size":68775,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the treatments with the plant growth parameters analyzed.\u003c/p\u003e","description":"","filename":"floatimage19.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/2cdbbbd6472eb86df02d72bf.png"},{"id":55571947,"identity":"67beb97b-486d-4f0a-ba3a-c6bdad0e12ff","added_by":"auto","created_at":"2024-04-30 05:42:57","extension":"png","order_by":20,"title":"Figure 20","display":"","copyAsset":false,"role":"figure","size":55471,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component and variable analyses obtained in the field experiment with the control treatments, \u003cem\u003eT\u003c/em\u003e. harzianum, \u003cem\u003eP. lilacinum\u003c/em\u003e and a mixture of both.\u003c/p\u003e","description":"","filename":"floatimage20.png","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/3e3756e93f1b7a136e7de7d5.png"},{"id":64620086,"identity":"4d36f4a9-6671-402c-9390-c9bbb80bf22c","added_by":"auto","created_at":"2024-09-16 16:17:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2256044,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4301649/v1/bdc96a56-ab1a-44c1-a0c6-31bf4d292681.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Growth promotion and modulation of the soybean microbiome INTACTA RR PRO TM with the application of the fungi Trichoderma harzianum and Purpureocillum lilacinum","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe soybean crop is of great importance worldwide due to the large supply of vegetable protein for animal production, such as swine and poultry production, and is also used for human consumption in addition to its derivatives, such as soybean oil\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The largest soybean producers in the world are Brazil and the United States of America (Wang et al., 2020). Soybean is the fifth most produced food in the world and allows farmers high profitability for the maintenance of agricultural activities\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe soybean crop, like other agricultural crops, faces several challenges to remain productive and profitable. The problems faced in soybean production are the occurrence of several pathogens and diseases requiring the application of fungicides \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and insecticide application due to the occurrence of several important pests that cause great economic losses\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. In addition, there are other factors that hinder soybean production, including various environmental stresses, such as salinity, due to recurrent localized fertilization, such as fertigation in soybean production sites that do not have well-distributed rainfall (Singh, 2021). Water stress due to a lack of rainfall\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e and the presence of heavy metals and contaminants in crop soils promote significant losses in productivity\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, high temperatures\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and, consequently, a reduction in agricultural area and a loss of productive potential.\u003c/p\u003e \u003cp\u003eDue to the large quantities produced and in large arable areas, soybean production requires large amounts of mineral fertilizers that, when used indiscriminately, promote salinization and contamination of soils, contamination of surface waters with the occurrence of eutrophication and contamination of groundwater with the leaching of nutrients to the ground water\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFungi have diverse and wide genetic and metabolic variability, producing several secondary metabolites that can be used in biotechnological processes and anthropic activities \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In addition, the fungi associated with plants can promote plant growth and development, increasing the availability of nutrients in the soil \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Moreover, plants can increase their ability to absorb water and nutrients\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, fight pathogens and decrease the incidence of diseases\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, fight pests by acting as biocontrol agents\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and increase their resistance to various types of environmental stresses\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In this sense, the use of filamentous fungi associated with plants is an excellent alternative to face the difficulties related to soybean production, allowing the use of fewer agricultural pesticides and less mineral fertilization and promoting a lower production cost, with lower environmental impact without affecting productivity\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e–\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong the fungi associated with plants, the filamentous fungus \u003cem\u003eTrichoderma harzianum\u003c/em\u003e promotes plant growth and development, such as through mycoparasitism, where the fungus produces several enzymes that degrade the cell wall of pathogenic fungi, in addition to the production of antimicrobial substances that combat and inhibit the growth of pathogenic fungi and decrease the plant diseases by competition for nutrients and colonization niches \u003csup\u003e\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e–\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAnother fungus associated with plants used in the pest, particularly in the control of nematodes, is the filamentous fungus \u003cem\u003ePurpureocillum lilacinum\u003c/em\u003e(Haque et al., 2018; Lan et al., 2017; Zhan et al., 2021). Although the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e has been used to control nematodes, a few studies have shown its high potential for use in promoting plant growth (Baron et al., 2019, 2020).\u003c/p\u003e \u003cp\u003eIn 2010, transgenic soybean was generated with the INTACTA RR2 PRO™ system, which confers tolerance to glyphosate herbicides to aid in the management of weeds that compete with crops. In addition, this soybean cultivar contains the genes that encode \u003cem\u003eB. thuringiensis\u003c/em\u003e toxins for the control of the main caterpillars that attack soybeans, which are the soybean caterpillar (\u003cem\u003eAnticarsia gemmatalis)\u003c/em\u003e, apple borer (\u003cem\u003eHeliothis virescens\u003c/em\u003e) and armpit borer (\u003cem\u003eCrocidosema aporema\u003c/em\u003e), in addition to the suppression of Elasmo (\u003cem\u003eElasmopalpus lignosellus\u003c/em\u003e) and \u003cem\u003eHelicoverpa\u003c/em\u003e (\u003cem\u003eH. zea\u003c/em\u003e and \u003cem\u003eH. armigera\u003c/em\u003e) caterpillars \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Thus, for the cultivars developed in this system, the \u003cem\u003ecry1Ac\u003c/em\u003e gene of \u003cem\u003eB. thuringiensis\u003c/em\u003e was added to the inserted genetic modification of the \u003cem\u003ecp4\u003c/em\u003e gene, which is responsible for conferring resistance to glyphosate and one of those responsible for the production of protein crystals with recognized insecticidal action for the cultivar, also commonly called Bt toxin\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Although this variety brings several benefits for soybean production, there are few studies on the growth-promoting effects of the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e and on the influence of these fungi on the modulation of the microbiome of the roots and leaves of soybean plants with the INTACTA RR2 PRO™ system.\u003c/p\u003e \u003cp\u003e \u003cb\u003eObjective\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe objective of the present study was to evaluate the potential of the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e to promote the growth of the soybean cultivar INTACT RR PRO \u003csup\u003eTM\u003c/sup\u003e and the effect of these fungi on the microbiome of the roots and leaves of soybean plants.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e \u003cb\u003eExperiment under Greenhouse Conditions\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe greenhouse experiment was conducted in a randomized block design with 10 treatments, six replicates and three application modes. The greenhouse was maintained at a temperature of 24 ± 2°C, humidity level of 50 ± 2% RH, and light with a cycle of 16:8 h L:D. According to the Köppen and Geiger classification, the climate is classified as Aw, and the soil of the region is a clayey eutrophic red latosol, as reported by Embrapa (1999). The pots used in the experiment were 5 dm³ in size.\u003c/p\u003e\u003cp\u003e \u003cb\u003eDescription of treatments and modes of application\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe experiment with the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e on soybean plants under greenhouse conditions was conducted in randomized blocks with 10 treatments, \u003cb\u003eT1\u003c/b\u003e = control (without application of fungi), \u003cb\u003eT2\u003c/b\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via furrow, \u003cb\u003eT3\u003c/b\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via foliar, \u003cb\u003eT4\u003c/b\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e via furrow + foliar, \u003cb\u003eT5\u003c/b\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via furrow, \u003cb\u003eT6\u003c/b\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via foliar, \u003cb\u003eT7\u003c/b\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e via furrow + foliar, \u003cb\u003eT8\u003c/b\u003e = \u003cem\u003eP lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow, \u003cb\u003eT9\u003c/b\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via foliar and \u003cb\u003eT10\u003c/b\u003e = \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow and foliar.\u003c/p\u003e\u003cp\u003eThe experiment was conducted in pots for 60 days after sowing. Three application modes were performed with the aid of pipettes for application in the furrow (in the soil near the neck of the plants) and a sprayer for foliar application. Inoculation for both fungi was performed by scraping the spores grown in Petri dishes containing the culture medium maltose agar for 7 days at 28°C. The spore concentration was standardized to 1 × 10\u003csup\u003e9\u003c/sup\u003e spores mL\u003csup\u003e− 1\u003c/sup\u003e, and the volume of each fungus was 10 mL. Five milliliters of fungus solution were applied via the furrow or foliar for each type of application for the treatment which received both types. In the treatments that received the mixture of fungi, 10 mL of each fungus was applied. The parameters evaluated were shoot dry mass (SDM), root dry mass (RDM), aerial part nitrogen content (N-SDM), root nitrogen content (N-RDM), phosphorus shoot dry mass content (P-SDM) and phosphorus content root dry mass (P-RDM). After 60 days of planting, the plants were dismantled, and the aerial parts and roots of each plant were carefully separated and conditioned. Five grams was removed from each root for DNA extraction and metagenomic analysis. The plant material was dried in a forced circulation oven at 65°C for three days until a constant weight was reached, after which the material was weighed on an analytical balance.\u003c/p\u003e\u003cp\u003e \u003cb\u003eNitrogen Content in the SDM\u003c/b\u003e \u003c/p\u003e\u003cp\u003eAfter the drying process, the SDM were ground in a Wiley mill. The nitrogen content of these materials was determined by sulfuric acid digestion and subsequent titration\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e\u003cp\u003e \u003cb\u003ePhosphorus Contents in the SDM\u003c/b\u003e \u003c/p\u003e\u003cp\u003eTo determine the phosphorus concentration in the shoot dry matter of the crop, nitric-perchloric digestion of the material was performed, followed by\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e \u003cb\u003eExperiment under Field Conditions\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe experiment was conducted in the research area of the Teaching Research and Extension Farm (FEPE) of the Universidade Estadual Paulista - UNESP - Campus de Jaboticabal-SP, located in Prof. Paulo Donato Castellane Road, in the municipality of Jaboticabal – SP, at an average altitude of 575 meters above sea level. The relief is characterized as gently undulating, and its geographical location is latitude 21° 15' 22'' S and longitude 48° 18' 58'' W. The climate is defined as tropical with dry winters and classified as Aw according to the International System of Koppen Classification. The average annual rainfall is 1,425 mm, with a concentration of rainfall in the summer. The soil type is Eutrophic Red.\u003c/p\u003e\u003cp\u003eSowing was performed on December 5, 2023, and the plants were harvested on March 19, 2024. Soil preparation was performed using no-tillage. The soybean cultivar used was INTACTA RR2 PRO \u003csup\u003eTM\u003c/sup\u003e (Embrapa Company), which belongs to the semiearly maturation group (6.7 North American classification) and has an indeterminate growth habit. For fertilization, 350 kg ha \u003csup\u003e− 1\u003c/sup\u003e of the formula 00-20-20 was used in the sowing furrow.\u003c/p\u003e\u003cp\u003e \u003cb\u003eExperimental Design\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe experiment under field conditions was conducted in a randomized block design with the following treatments: \u003cb\u003eT1\u003c/b\u003e = control (without the application of microorganisms); \u003cb\u003eT2\u003c/b\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cb\u003eT3\u003c/b\u003e = \u003cem\u003eP. lilacinum;\u003c/em\u003e and \u003cb\u003eT4\u003c/b\u003e = \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e. Each treatment was replicated four times, and the microorganisms were applied foliage with the aid of a costal pump. The dose of the applied fungi was 300 mL ha \u003csup\u003e− 1\u003c/sup\u003e at a concentration of 1 × 10\u003csup\u003e9\u003c/sup\u003e CFU mL \u003csup\u003e− 1\u003c/sup\u003e. The spacing between planting rows was 0.5 meters, each plot had an area of 30 m\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, and the number of plants was approximately 250,000 plants/hectare.\u003c/p\u003e\u003cp\u003e \u003cb\u003eSample collection\u003c/b\u003e \u003c/p\u003e\u003cp\u003eIn the pot experiment under greenhouse conditions, the roots were collected when the pots were poured into a sterilized container, and the soil was loosened from the roots using a sterile metal spatula. For the experiment under field conditions, the collection of leaves was performed manually with the use of surgical gloves, and the leaves were immediately deposited in sterilized plastic containers. Subsequently, for both conditions, roots and leaves were placed in a 50 ml conical tube containing 35 ml of phosphate buffer with 0.02% surfactant (Tween 20). The tubes were vortexed for 2 min to separate the root systems from the rhizosphere. Then, with the aid of sterilized forceps, the roots and leaves were placed on paper towels and transferred to centrifuge tubes (50 ml). Superficial sterilization of roots and leaves was performed according to \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, with modifications. Plant tissues were maintained in 100% ethanol for 3 min, followed by 2% sodium hypochlorite for 2 min and 70% ethanol for 3 min. The disinfected roots and leaves were washed three times with sterile distilled water, and the last wash was inoculated onto nutrient agar plates to validate the effectiveness of the superficial sterilization procedure.\u003c/p\u003e\u003cp\u003e \u003cb\u003eDNA extraction from the roots and leaves of soybean plants\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe sterilized roots and leaves were macerated with a sterile mortar and pestle with the aid of liquid nitrogen. A PowerMax soil DNA extraction kit (Mo Bio Laboratories, Carlsbad, CA) was used to extract genomic DNA according to the manufacturer’s instructions. The concentration of extracted DNA was determined by fluorometry (Qubit™ 3.0, Invitrogen), and the purity was estimated by calculating the A260/A280 ratio via spectrophotometry (NanoDrop™ 1000, Thermo Fisher Scientific). The V4 hypervariable region of the 16S rRNA gene was amplified with the primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′;\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Three forward primers were used for amplification. These primers were modified by adding degenerate nucleotides (Ns) to the 5′ region to increase the diversity of target sequences\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. PCR was performed in 30 cycles using the HotStarTaq Plus Master Mix kit (Qiagen) under the following conditions: 94°C for 3 min, followed by 28 cycles of 94°C for 30 s, 53°C for 40 s and 72°C for 1 min, and a final elongation step at 72°C for 5 min. PNA clamp sequences (PNA Bio) were added to block amplification of the 16S rRNA gene from ribosomes and mitochondria. The amplification products were analyzed on a 2% agarose gel to determine the success of amplification and the relative intensity of the bands. The sequencing of amplicons was performed on an Illumina MiSeq platform.\u003c/p\u003e\u003cp\u003e \u003cb\u003eData Processing\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe initial evaluation of the quality of the sequencing data was performed using FastQC software (version 0.11.9)\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. For a more in-depth analysis, USEARCH (version 11.0.667) was used\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e The \"fastx_info\" and \"fastq_eestats2\" functions were used to examine the quality distribution, sequence length and expected errors. The \"search_oligodb\" function of the same software was used to identify the presence and location of primers 341F ('5-CCTACGGGNGGCWGCAG-3') and 805R ('5-GACTACHVGGGTATCTAATCC-3'), which delimit the V3-V4 region of the 16S gene rRNA in the analyzed sequences. Next, the adjacent primers and barcodes were removed using Atropos (version 1.1.31)\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. To ensure data quality, Fastp (version 0.23.2)\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e was used to remove sequences with an average Phred quality lower than Q25 using the parameter \"average_qual 25\". Considering the \"paired-end\" sequencing approach, the sequences were merged using PEAR (version 0.9.11)\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, with an overlap criterion of at least 10 base pairs (min-overlap 10). The merged readings were processed through the DADA2 pipeline\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e The dada2 package (version 1.22.0) was used for integration with R statistical software (version 4.1.2)\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. The procedure began with the filtering and truncation of the readings by the \"filterAndTrim\" function, adopting an expected error limit of 2 (\"maxEE = 2\"). Subsequently, the error probabilities were estimated on a basis using the \"learnErrors\" function. Based on this error model, the sequences were corrected using the \"dada\" function, resulting in the identification of the amplicon variant sequences (ASVs) specific to each sample. These ASVs were analyzed for the removal of possible chimeric sequences using the \"removeBimeraDenovo\" function. For taxonomic classification, the ASVs were compared with the SILVA database (version 138.1)\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, allowing taxonomic identification down to the level of bacteria or archaea. ASVs not classified as such or identified as potential contaminants, including chloroplast and mitochondrial sequences, were excluded from the analysis. The counts and taxonomic annotations of the VSAs were exported in the \"phyloseq\" format (R package \"phyloseq\"; version 1.38.0)\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. The phyloseq data were then transformed into compositional data by the function \"phyloseq_standardize_otu_abundance\" of the R package \"metagMisc\" (version 0.04)\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e for microbiome analyses.\u003c/p\u003e\u003cp\u003e \u003cb\u003eDescriptive and Statistical Analysis of the Microbiome\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe efficiency of the sampling was evaluated by means of rarefaction curves using \"amp_rarecurve\" analysis of the R package \"ampvis2\" (version 2.7.17)\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. After that, the samples were subjected to rarefaction based on the lowest number of sequences found in a library (n = 346,844), and the analyses were conducted using the tables resulting from this rarefaction. Alpha diversity was quantified by examining both species richness (observed and estimated by the Chao1 index) and diversity (Shannon and Gini Simpson indices) using the \"alpha\" function of the R package \"microbiome\" (version 1.16.0)\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. For the comparative analysis of the means, ANOVA was applied, establishing a confidence interval of 95% (p value \u0026lt; 0.05). Complementary statistical analyses, including post hoc multiple comparisons between treatments, were performed with the \"emmeans\" function (R package \"emmeans\"; version 1.8.9)\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, adjusting the p values using the false discovery rate (FDR) method. Beta diversity analysis was performed by calculating the Bray‒Curtis dissimilarity between the samples using the \"distance\" function of the \"phyloseq\" R package. To determine whether there were significant differences between treatments, PERMANOVA was used, using the \"adonis\" function of the \"vegan\" R package (version 2.6.2)\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e The significance level was established at a p value \u0026lt; 0.05. For the interpretation of the multidimensional distances, a principal coordinate analysis (PCoA) was performed, and the results were visualized in subsequent graphs. The identification of differentially abundant taxa among the treatments was performed using the DESeq2 methodology (package R version 1.34.0)\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e A negative binomial model was used to compare the means via the Wald test (adjusted p value \u0026lt; 0.05). The visualizations of the aforementioned analyses were prepared in R using the \"ggplot2\" package (version 3.3.6)\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e \u003cb\u003eStructural Analysis of the Microbiome\u003c/b\u003e \u003c/p\u003e\u003cp\u003eTo evaluate the structural characteristics of microbial communities in response to different treatments, an analysis of co-occurrence networks was performed at the genus level. Pearson's correlation coefficients were calculated using the \"corr.test\" function of the \"psych\" R package (version 2.2.5)\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Only significant correlations (p value \u0026lt; 0.05) with a minimum Pearson coefficient of ± 0.75 were considered, with a focus on strongly positive or negative relationships. Additionally, to reduce noise and focus on relevant genera, only those with a mean relative abundance of at least 0.001% in at least one treatment were included. The construction of the networks and the analysis of their topological properties were performed using the R package \"igraph\" (version 1.3.4)\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. The topological properties included the total number of correlated genera (number of nodes), total number of links (edges), average and maximum degrees, modularity, number of modules, clustering coefficient, and measures of average and centrality between maxima. The main \"hubs\" were identified by calculating the \"Kleinberg's hubbiness score\"\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, highlighting the genres with the greatest influence on the\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eGreenhouse experiment\u003c/b\u003e \u003c/p\u003e\u003cp\u003eIn the experiment conducted under greenhouse conditions with 10 treatments and six replicates, the results showed that the shoot dry mass varied between 5.02 and 15.03 grams and that the treatments did not differ from each other (p \u0026gt; 0.05) according to the 5% Duncan test (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The root dry mass ranged between 0.46 and 2.00 grams, and the values also did not differ from each other (p \u0026gt; 0.05) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The highest mean values (p \u0026lt; 0.05) of nitrogen levels in the SDM were found in treatments T5 (\u003cem\u003eT. harzianum\u003c/em\u003e furrow application) and T6 (\u003cem\u003eT. harzianum\u003c/em\u003e foliar application), followed by treatments T1 (control), T3 \u003cem\u003e(P. lilacinum\u003c/em\u003e via foliar) and T7 (\u003cem\u003eT. harzianum\u003c/em\u003e via furrow + foliar). The lowest nitrogen contents were found in treatments T2 (\u003cem\u003eP. lilacinum\u003c/em\u003e via furrow), T8 (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow), T9 (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via foliar) and T10 (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e furrow + foliar) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003eRegarding the average of phosphorus content in the SDM, the highest values were found in treatment T10 (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow and foliar), followed by treatments T1 (control) and T5 (\u003cem\u003eT. harzianum\u003c/em\u003e via furrow), T6 (\u003cem\u003eT. harzianum\u003c/em\u003e via foliar) and T7 (\u003cem\u003eT. harzianum\u003c/em\u003e via furrow and foliar). Treatments T4 (\u003cem\u003eP. lilacinum\u003c/em\u003e via foliar) and T8 (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow) had lower average phosphorus contents (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eThe highest mean values of nitrogen from the root were found in the T8 treatment (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow) compared to the T2 treatment. (\u003cem\u003eP. lilacinum\u003c/em\u003e via furrow). The other treatments did not differ (p \u0026gt; 0.05) from each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). There was no significant difference (p \u0026gt; 0.05) between the treatments and the control treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eRegarding the diversity of endophytic bacteria from the roots of soybean plants, inoculations of the fungi \u003cem\u003eP. lilacinum\u003c/em\u003e and \u003cem\u003eT. harzianum\u003c/em\u003e performed in the experiment under greenhouse conditions showed no difference between the treatments. The bacterial genera found most frequently in the treatments were \u003cem\u003ePseudomonas\u003c/em\u003e sp., \u003cem\u003eSalmonella\u003c/em\u003e sp., \u003cem\u003eRhizobium\u003c/em\u003e, \u003cem\u003eRhizobiaceae\u003c/em\u003e, \u003cem\u003eAgrobacterium\u003c/em\u003e and \u003cem\u003eStenotrophomonas\u003c/em\u003e. The bacterial genera and species least abundant in the treatments were \u003cem\u003eAchromobacter\u003c/em\u003e, \u003cem\u003ePantoa dispersa\u003c/em\u003e and \u003cem\u003ebentonitic Stenotrophomonas\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThere was no significant difference (p \u0026gt; 0.05) in the diversity of endophytic fungi isolated from the roots in the pot experiment under greenhouse conditions. The fungal genera and species present in greatest quantities were \u003cem\u003eFusarium\u003c/em\u003e, \u003cem\u003eF. oxysporum\u003c/em\u003e, \u003cem\u003ePlectosphaerella\u003c/em\u003e and \u003cem\u003eCurvularia\u003c/em\u003e. The genera and species that were found in smaller numbers were \u003cem\u003eMythecium inundatum\u003c/em\u003e, \u003cem\u003eChaetomium globosum\u003c/em\u003e, \u003cem\u003eFusarium suflorianum\u003c/em\u003e and \u003cem\u003eSaccharomyces\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe mean values found in the split analysis with two factors, factor 1 (fungal species, \u003cem\u003eT. harzianum\u003c/em\u003e; \u003cem\u003eP. lilacinum\u003c/em\u003e and \u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e) and factor 2 (application methods, furrow, foliar and furrow + foliar), under potted conditions showed no difference (p \u0026gt; 0.05) for the parameters of SDM (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), nitrogen content from SDM (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) or phosphorus content from SDM (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e \u003cb\u003eExperiment under field conditions\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe highest values for SDM under field conditions were found in treatments T2 (\u003cem\u003eT. harzianum\u003c/em\u003e), T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) and T4 (\u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e) compared with the control treatment T1, which had the lowest value (p \u0026lt; 0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThere was no significant difference (p \u0026lt; 0.05) in nitrogen content between the treatments based on SDM (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA). Nevertheless, the phosphorus content was the highest in the T3 treatment, which utilized \u003cem\u003eP. lilacinum\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eThe most abundant phylum was \u003cem\u003ePseudomonas\u003c/em\u003e, and the percentages in the T1 (control), T2 (\u003cem\u003eT. harzianum\u003c/em\u003e), T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) and T4 (\u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e) treatments were 44.93%, 29.18%, 20.01% and 53.88%, respectively. The second most abundant genus was \u003cem\u003eBradyrhizobium\u003c/em\u003e at 31.24%, 33.482%, 44.72%, and 17.43%, and the third most abundant genus was \u003cem\u003eEnterobacter\u003c/em\u003e at 16.77%, 24.50%, 25.552%, and 24.377%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). Interestingly, there was a significant difference in the number of species between treatments T1 (control), T2 (\u003cem\u003eT. harzianum\u003c/em\u003e), T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) and T4 (\u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e), with 70, 50, 13 and 29 species, respectively.\u003c/p\u003e\u003cp\u003eComparative analysis between treated samples (T2 to T4 treatments) and control samples (T1 treatment) revealed a total of 77 differentially abundant taxa (DA), categorized into 2 phyla, 4 classes, 5 orders, 19 families, and 26 genera. Among these, 58 taxa were predominantly more abundant in the T1 treatment (control), while 6, 4 and 9 taxa were more abundant in the T2 (\u003cem\u003eT. harzianum\u003c/em\u003e), T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) and T4 (\u003cem\u003eT. harzianum\u003c/em\u003e) treatments. + \u003cem\u003eP. lilacinum\u003c/em\u003e), respectively. The DA taxa at the genus level are visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e. Notably, with the exception of \u003cem\u003eKosakonia\u003c/em\u003e, all other affected genera exhibited a relative abundance lower than 1%. Genera such as \u003cem\u003eOligoflexus\u003c/em\u003e, \u003cem\u003eAchromobacter\u003c/em\u003e, \u003cem\u003eShinella\u003c/em\u003e and \u003cem\u003eSphingobacterium\u003c/em\u003e were differentially abundant in the T1 treatment (control) in multiple comparisons. Notably, the genus \u003cem\u003eLuteibacter\u003c/em\u003e was also differentially abundant in treatments T2 (\u003cem\u003eT. harzianum\u003c/em\u003e) and T4 (\u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e). The greatest differences (log2-fold changes) were observed in the absence of genus in the opposite treatment. However, the greatest variations in terms of relative abundance were recorded for \u003cem\u003eKosakonia\u003c/em\u003e, which was significantly more abundant in T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) (3.6%) than in T1 (control) (0.08%), and \u003cem\u003eSiccibacter\u003c/em\u003e, which was more abundant in T1 (control) (0.81%) than in T2 (\u003cem\u003eT. harzianum\u003c/em\u003e) (0.003%).\u003c/p\u003e\u003cp\u003ePrincipal coordinate analysis (PCoA) based on Bray‒Curtis distances was applied to investigate the microbial composition of the samples under different treatments. The results indicate a trend toward a significant separation of the samples as a function of the treatments, although the \u003cem\u003ep\u003c/em\u003e value is marginally above the significance threshold (\u003cem\u003ep\u003c/em\u003e value = 0.051). The dimensionality reduction performed by PCoA was able to explain 76.07% of the total variability observed in the samples based on the first three main axes (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e). Although considerable variability was observed within the groups and some overlap between them, post hoc analyses indicated trends of significant compositional differences between treatments, particularly between T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) and T4 (\u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e) (p value = 0.028), as well as between T1 (control) and T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) (p value = 0.058). These results suggest the existence of distinct patterns in the microbial composition associated with each treatment, reflecting the specific influence of each intervention on the microbial community from the leaves of soybean plants.\u003c/p\u003e\u003cp\u003eVenn diagram analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003e) revealed significant sharing of taxa at the higher taxonomic levels, with 12 phyla and 98 genera identified as common among all treatments. However, the comparison at the level of ASVs showed a distinct pattern, with only 59 ASVs out of a total of 2,207 being shared by all treatments. This result suggested conservation of the main taxonomic groups among the treatments, while the differences in the ASV indicated significant variations in the population composition. Regarding the presence of exclusive taxa, there was a trend in which the control treatment (T1) had the greatest number of unique taxa, followed by treatments T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e), T2 (\u003cem\u003eT. harzianum\u003c/em\u003e) and, finally, T4 (\u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e), which were consistent at all the taxonomic levels analyzed.\u003c/p\u003e\u003cp\u003eThe structuring of the microbiomes of the samples was inferred from the co-occurrence networks of the different treatments. There were changes in the relationships between the identified genera (Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e). In this sense, treatment T1 (control) had a greater number of correlated genera (\"N. of nodes\") and correlations (\"N. of edges\"). Although this treatment had more than twice the amount of bonding compared to the other treatments, treatments T2 (\u003cem\u003eT. harzianum\u003c/em\u003e) and T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) presented a greater number of negative bonds (\"negative edges\"), with 57 and 71, respectively, against only 25 in T1 (control). The characteristics of T1 (control) are mainly due to the presence of a cluster with a large number of correlations, reflecting higher means of connections (\"Mean degree\") and average and maximum potential of betweenness/Max. betweenness\"). This is further reinforced by the high number of key taxa (\"main hubs\") found for this treatment. In general, treatments with fungal inoculants showed reduced binding, increased negative binding (except for T4 (\u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e) and a reduction in the number of key taxa, which in turn differed between the treatments. These observations suggest that treatments differentially influence the structure and dynamics of microbial communities, altering the patterns of co-occurrence and the relative importance of certain taxa within the networks.\u003c/p\u003e\u003cp\u003eThe highest mean yield value (p \u0026lt; 0.05) was found for treatment \u003cb\u003eT3\u003c/b\u003e (\u003cem\u003eP. lilacinum\u003c/em\u003e) compared to treatment T1 (control). The T2 (\u003cem\u003eT. harzianum\u003c/em\u003e), T3 (P. lilacinum) and T4 \u003cb\u003e(\u003c/b\u003e\u003cem\u003eT. harzianum\u003c/em\u003e \u003cb\u003e+\u003c/b\u003e \u003cem\u003eP. lilacinum\u003c/em\u003e\u003cb\u003e)\u003c/b\u003e treatments did not differ (p \u0026gt; 0.05) from each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig17\" class=\"InternalRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe correlation between the taxonomic groups showed that some genera had a positive and significant correlation with some plant growth parameters. Specifically, for productivity, the genera \u003cem\u003eErwinia\u003c/em\u003e and \u003cem\u003eBacillus\u003c/em\u003e followed the genus \u003cem\u003eBlautia\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig18\" class=\"InternalRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTreatment T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) was the only treatment that promoted increased productivity compared to the other treatments (Figs.\u0026nbsp;\u003cspan refid=\"Fig17\" class=\"InternalRef\"\u003e17\u003c/span\u003e and \u003cspan refid=\"Fig19\" class=\"InternalRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe parameters that were significantly influenced by the T3 treatment (\u003cem\u003eP. lilacinum\u003c/em\u003e) were the phosphorus concentration in SDM, productivity and nitrogen content (Fig.\u0026nbsp;\u003cspan refid=\"Fig20\" class=\"InternalRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cb\u003eExperiment under Greenhouse Conditions\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe results showed that soybean growth did not increase when the plants were inoculated with the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e alone or in combination under greenhouse conditions. There was no difference in SDM or RDM (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA \u003cb\u003eand B\u003c/b\u003e). In general, there were no significant increases in nitrogen levels with the application of the fungi \u003cem\u003eP. lilacinum\u003c/em\u003e or \u003cem\u003eT. harzianum\u003c/em\u003e. Studies under controlled conditions, such as those conducted in pots in greenhouses, have several advantages, such as the attribution of results to the microorganisms evaluated and the ease of replicability of the results. The reasons why the fungi did not promote growth were not identified; however, under controlled conditions, with little variation in temperature and without water or nutritional stress, there is strong evidence that the optimal growth conditions of soybean provided by greenhouse condition may have decreased the interaction between plants and fungal microorganisms since this interaction is usually strengthened by adverse environmental conditions and not by appropriate environmental conditions\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Since the emergence of plants, microorganisms interact with them, increasing the availability and absorption capacity of water and nutrients and increasing resistance to adverse biotic and abiotic factors. Interestingly, the same fungus, \u003cem\u003eP. lilacinum\u003c/em\u003e, promoted an increase in soybean yield under field conditions but did not promote increases in any other biometric parameters of the plant under pot conditions. This inconsistency of results usually occurs with the application of microorganisms, often due to environmental conditions and not due to the microorganism.\u003c/p\u003e\u003cp\u003eInterestingly, there was a tendency for the mixture of the two fungi \u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e to decrease the nitrogen levels in the SDM compared to the application of \u003cem\u003eT. harzianum\u003c/em\u003e alone. Most likely, the mixture of fungi caused losses in nitrogen absorption (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). This was due to the lower values found in treatments T8 (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow), T9 (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via foliar) and T10 (\u003cem\u003eP. lilacinum\u003c/em\u003e + \u003cem\u003eT. harzianum\u003c/em\u003e via furrow and foliar), which received inoculation of the two fungi \u003cem\u003eP. lilacinum\u003c/em\u003e and \u003cem\u003eT. harzianum\u003c/em\u003e, compared with treatments T5 (\u003cem\u003eT. harzianum\u003c/em\u003e via furrow), T6 (\u003cem\u003eT. harzianum\u003c/em\u003e via foliar) and T7 (\u003cem\u003eT. harzianum\u003c/em\u003e via furrow + foliar), which received only the inoculation of \u003cem\u003eT. harzianum\u003c/em\u003e. Probably the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e could decrease the action of another fungus when applied as a mixture. A study revealed that the application of the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e, despite reducing the incidence and severity of rust in tomato plants caused by the fungus \u003cem\u003ePhytophthora capsici\u003c/em\u003e, in combination with the fungus \u003cem\u003eFunneliformis caledonium\u003c/em\u003e promoted a reduction in its efficiency in the inhibition of the disease compared with the application of the fungus \u003cem\u003eF. caledonium\u003c/em\u003e alone(Hu et al., 2020). Other studies used mixtures of different fungi, such as \u003cem\u003eBeauveria bassiana\u003c/em\u003e, \u003cem\u003eT. harzianum\u003c/em\u003e, \u003cem\u003ePochonia chlamydosporia\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e, and although the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e did not increase the effect of the application of the other fungi, there was no evidence of antagonistic effects. On the other hand, the results showed that the application of \u003cem\u003eP. lilacinum\u003c/em\u003e alone increased few parameters, such as root dry matter, in common bean plants \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.The application of \u003cem\u003eP. lilacinum\u003c/em\u003e to pineapple plants also promoted root growth compared to that in the control treatment\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. In these studies, there was no antagonistic effect when the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e was applied together with other fungi to the plants. However, the results of the present study suggest that caution should be taken when mixing the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e with other fungi to promote plant growth.\u003c/p\u003e\u003cp\u003eRegarding the influence of the application of the two fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e on the microbiota of soybean roots, the results showed that although there was a high number of taxa for \u003cem\u003ePseudomonas\u003c/em\u003e, \u003cem\u003eSalmonella\u003c/em\u003e and \u003cem\u003eRhizobium\u003c/em\u003e, there was no significant difference in relation to the diversity of these bacteria under the treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The genus \u003cem\u003ePseudomonas\u003c/em\u003e is commonly found in soybean roots, and several studies have shown that certain \u003cem\u003ePseudomonas\u003c/em\u003e species in soybean have growth-promoting effects, induction of systemic resistance and modulation of the root microbiome with growth-promoting effects on plants\u003csup\u003e\u003cspan additionalcitationids=\"CR61\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e–\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. The genus \u003cem\u003eSalmonella\u003c/em\u003e has several species of bacteria that are pathogenic to animals and humans. Although there are no reports of \u003cem\u003eSalmonella\u003c/em\u003e promoting the growth of soybean plants, colonization of this bacterium in roots is relatively common and occurs due to the ability of the bacterium to suppress the defense mechanisms of the soybean plant\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. The presence of this genus indicates that it is likely an opportunistic bacterium originating from bird feces.\u003c/p\u003e\u003cp\u003eAmong the endophytic fungi identified, \u003cem\u003eFusarium, F.\u003c/em\u003e oxysporum, \u003cem\u003ePlectosphaerella\u003c/em\u003e and \u003cem\u003eCurvularia\u003c/em\u003e were the most prevalent. However, there was no significant difference between treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Interestingly, although \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e were inoculated into soybean plants, these fungi were not identified as endophytic in the roots. Although some studies have shown the ability of \u003cem\u003eT. harzianum\u003c/em\u003e to colonize soybean roots in an endophytic way, the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e were isolated from the soil environment and probably do not have an affinity for endophyticism \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe values of the splitting showed that for the parameters of the SDM, RDM and the contents of nitrogen and phosphorus were not altered in relation to the application of the two fungal species or the mixture of both fungi. There was also no difference in the parameters evaluated in relation to the three modes of application (fungi, furrows, foliar and a mixture of furrows and foliar) (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e–\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). These results reinforce that although a microorganism has several abilities related to the promotion of plant growth, depending on the environmental conditions, this effect does not occur. Generally, when there is no stress environment, plant‒microbe interactions decrease in intensity, and thus, the effect of microorganisms on plants also decreases\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e \u003cb\u003eField Experiment\u003c/b\u003e \u003c/p\u003e\u003cp\u003eAll treatments promoted an increase in SDM and RDM compared to the control treatment, which did not receive fungal inoculation. With the exception of the control treatment, the other treatments did not differ from each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Interestingly, these fungi did not promote an increase in SDM, and there was no increase in RDM under potted conditions, as previously mentioned. In contrast, the experiment was performed under field conditions. The evaluated fungi produce phytohormones that promote the development of roots and shoots, increasing soil exploitation efficiency and photosynthetic efficiency and contributing to increased resistance to abiotic stresses and plant growth \u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThere was no difference in the nitrogen content of the SDM between treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA); however, treatment T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) increased the phosphorus content of the SDM. The other treatments did not differ from each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eB) in the selection of these same fungal isolates, showed the potential use of these fungi to promote growth in maize, common beans, and soybean plants with increases in the average levels of nitrogen and phosphorus in the plants \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Interestingly, the evaluations performed for the selection of these fungi were also performed under pot conditions, and unlike the present study, the results were significant for the parameters analyzed. It is crucial to emphasize that the environmental parameters of the greenhouse in which these fungi were isolated varied from those employed in the present investigation. A few studies have shown that the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e promotes increased nutrient levels in plants. Although the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e increased the levels of nitrogen, phosphorus, manganese, copper, zinc and boron in the SDM of bean plants, the fungus did not significantly affect the activity of the enzyme arylsulfatase or the solubilization of phosphorus in the soil. These results suggest that the fungus has the ability to increase the ability of plants to absorb these nutrients rather than increasing the availability of these nutrients in the soil \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAccording to the taxonomic profile, the T3 treatment (\u003cem\u003eP. lilacinum\u003c/em\u003e) increased the prevalence of \u003cem\u003eBradyrhizobium\u003c/em\u003e and the bacterium \u003cem\u003eKosakonia cowanii\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e). However, there was no significant difference compared to the other treatments. Interestingly, \u003cem\u003eBradyrhizobium\u003c/em\u003e behaved as a common taxon for treatments T2 (\u003cem\u003eT. harzianum\u003c/em\u003e) and T4 (\u003cem\u003eT. harzianum\u003c/em\u003e + \u003cem\u003eP. lilacinum\u003c/em\u003e), but for treatment T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e), \u003cem\u003eBradyrhizobium\u003c/em\u003e was a binding taxon linking two distinct networks (Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Treatment T3 (\u003cem\u003eP. lilacinum\u003c/em\u003e) was the only treatment that promoted increased soybean productivity under field conditions compared to the control treatment (Figs.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e and \u003cspan refid=\"Fig17\" class=\"InternalRef\"\u003e17\u003c/span\u003e). Further research is necessary to confirm whether the application of the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e is able to increase the abundance of \u003cem\u003eBradyrhizobium\u003c/em\u003e in soybean plants. In addition, there were positive and significant correlations for yield, SDM, averages of nitrogen and phosphorus contents with increasing abundance of \u003cem\u003eErwinia\u003c/em\u003e bacterium, and average of nitrogen contents and yield with increased abundance of \u003cem\u003eBacillus\u003c/em\u003e and for mean nitrogen contents to increase the abundance of \u003cem\u003eSphingomonas\u003c/em\u003e. The genus \u003cem\u003eSphingomonas\u003c/em\u003e includes bacteria that can produce phytohormones and volatile organic compounds, and some studies have shown that Sphingomonas can promote plant growth\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe genus \u003cem\u003eErwinia\u003c/em\u003e has several bacterial species classified as plant pathogens. However, this genus also harbors species reported to promote plant growth. A study revealed a new strain of bacteria, called A4, from almond tree leaves that may promote plant growth by increasing access to nutrients and producing a stress-reducing compound called spermidine. This bacterium has been reported to have potential for use in various crops to improve productivity and sustainability in agriculture. The bacterium \u003cem\u003eErwinia\u003c/em\u003e A4 was also shown to successfully colonize the \u003cem\u003eArabidopsis thaliana\u003c/em\u003e model plant, spreading from the roots to aerial parts such as leaves and flowers, indicating its ability to live inside the plants and potentially benefit them by promoting plant growth. Genome analysis of the bacterium \u003cem\u003eErwinia\u003c/em\u003e A4 revealed unique genes that may contribute to its ability to promote plant growth, including those involved in the synthesis of spermidine, a compound known to help plants cope with stress. Experiments showed that plants treated with A4 had a 30% greater fresh mass than untreated plants, suggesting that A4 significantly increases plant growth\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn general, the treatments with the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e showed a reduction in the number of links, an increase in the number of negative links (except for T4) and a reduction in the number of key taxa, which in turn differed between treatments. These observations suggest that treatments differentially influence the structure and dynamics of microbial communities, altering the patterns of co-occurrence and the relative importance of certain taxa within the networks. These results suggest the existence of distinct patterns in the microbial composition associated with each treatment, reflecting the specific influence of each intervention on the microbial community of the leaves of soybean plants.\u003c/p\u003e\u003cp\u003ePlant growth is influenced by numerous factors, and it is intriguing to consider how these factors interact with each other. One of the key factors affecting plant growth is the plant microbiome. Thus, the plant microbiome can be used as an effective strategy to enhance plant growth. However, altering the microbiome to promote plant growth is challenging. These results suggest that microbial inoculations that increase the negative co-occurrence of certain taxa can promote plant growth. Further research is required to elucidate the impact of the increased negative co-occurrence resulting from microbial inoculation on the overall plant microbiome. Additionally, it remains to be determined whether the decrease in the entire microbiome is a justifiable reason for promoting plant growth. In other words, it needs to be better elucidated if to enhance plant growth, the influence of certain taxa on the microbiome must be decreased.\u003c/p\u003e\u003cp\u003eAs previously mentioned, compared with the control treatment, the T3 treatment (\u003cem\u003eP. lilacinum\u003c/em\u003e) promoted an increase in soybean yield. Yield is influenced by several factors, and in a complex way, this increase may have been due to the various changes promoted by the application of the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e to soybean plants, such as all the aforementioned changes in the composition of the leaf microbiome and the increase in phosphorus levels in leaves.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results of the present study show that it was possible to significantly increase the productivity of the transgenic soybean INTACTA RR PRO \u003csup\u003eTM\u003c/sup\u003e with the application of the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e and that this increase in productivity may have occurred due to a set of several factors that were influenced by the application of the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e, such as the increase in the phosphorus content in the SDM; the \u003cem\u003eErwinia, Bacillus\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e taxon increase in the leaves; their positive and significant correlations with the productivity and the average phosphorus and nitrogen contents in the SDM; and the promotion of the genus \u003cem\u003eBradyrhizobium\u003c/em\u003e as a linking taxon of other taxon networks. Furthermore, it is important to note that the same fungus, \u003cem\u003eP. lilacinum\u003c/em\u003e, applied under pot conditions did not increase the growth of soybean plants. These results help to explain several inconsistencies in the results found in the application of these fungi and reinforce the importance of the environment in the expression of the abilities of the microorganisms and in the effective action of these microorganisms as promoters of plant growth and in the aid of more sustainable agricultural production.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eExperimental research and field studies on plants (either cultivated or wild), including the collection of plant material, must comply with relevant institutional, national, and international guidelines and legislation.\u003c/p\u003e \u003cp\u003eThe soybean cultivar is a business cultivar sold across the country and this cultivar is registered with the Ministry of Agriculture, Livestock and Supply.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll the authors have contributted in this study in the same way.\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e \u003cp\u003eWe thanks Fapesp for financial support\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and analyzed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLiu, S., Zhang, M., Feng, F. \u0026amp; Tian, Z. 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Currently, there is a lack of information on the effects of the fungi \u003cem\u003eTrichoderma harzianum\u003c/em\u003e and \u003cem\u003ePurpureocillum lilacinum\u003c/em\u003e on the INTACTA RR PRO \u003csup\u003eTM\u003c/sup\u003e transgenic soybean plants. The present study evaluated the application of the fungi \u003cem\u003eT. harzianum\u003c/em\u003e and \u003cem\u003eP. lilacinum\u003c/em\u003e under pot and field conditions. Under pot conditions, there were no significant differences in most of the parameters evaluated or in the abundance of the microbiota in the roots. However, under field conditions, the results showed a significant increase in soybean yield at 423. kg. ha \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e with the application of \u003cem\u003eP. lilacinum\u003c/em\u003e compared to the control treatment. In addition, the application of \u003cem\u003eP. lilacinum\u003c/em\u003e promoted a significant increase in phosphorus levels in the aerial part, and there were significant correlations between the increase in taxon abundance for the genus \u003cem\u003eErwinia\u003c/em\u003e and productivity and the average phosphorus and nitrogen contents for the aerial part, for the taxon \u003cem\u003eBacillus\u003c/em\u003e and nitrogen content and productivity, and for the taxon \u003cem\u003eSphingomonas\u003c/em\u003e and nitrogen content. The \u003cem\u003eBradyrhizobium\u003c/em\u003e taxon was identified in the \u003cem\u003eP. lilacinum\u003c/em\u003e treatment as a linking taxon linking two different networks of taxon and showing itself as an important taxon in the microbiota. The results show that the application of the fungus \u003cem\u003eP. lilacinum\u003c/em\u003e can increase the productivity of the soybean INTACTA RR PRO \u003csup\u003eTM\u003c/sup\u003e and that this increase in productivity may be a function of the modulation of the microbiota composition of the plants leaves by \u003cem\u003eP. lilacinum\u003c/em\u003e effect.\u003c/p\u003e","manuscriptTitle":"Growth promotion and modulation of the soybean microbiome INTACTA RR PRO TM with the application of the fungi Trichoderma harzianum and Purpureocillum lilacinum","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-30 05:34:51","doi":"10.21203/rs.3.rs-4301649/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-27T08:20:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-22T11:45:43+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-25T09:17:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-25T05:55:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-04-21T16:55:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc564d42-b412-4820-9b33-76741bb6d528","owner":[],"postedDate":"April 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":31321673,"name":"Biological sciences/Microbiology"},{"id":31321674,"name":"Biological sciences/Molecular biology"},{"id":31321675,"name":"Earth and environmental sciences/Environmental social sciences"}],"tags":[],"updatedAt":"2024-09-16T16:15:01+00:00","versionOfRecord":{"articleIdentity":"rs-4301649","link":"https://doi.org/10.1038/s41598-024-71565-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-09-09 15:57:13","publishedOnDateReadable":"September 9th, 2024"},"versionCreatedAt":"2024-04-30 05:34:51","video":"","vorDoi":"10.1038/s41598-024-71565-2","vorDoiUrl":"https://doi.org/10.1038/s41598-024-71565-2","workflowStages":[]},"version":"v1","identity":"rs-4301649","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4301649","identity":"rs-4301649","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}