Harnessing the Synergy of Urochloa brizantha and Amazonian Dark Earth Microbiomes for Enhanced Pasture Recovery

Harnessing the Synergy of Urochloa brizantha and Amazonian Dark Earth Microbiomes for Enhanced Pasture Recovery | 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 Research Article Harnessing the Synergy of Urochloa brizantha and Amazonian Dark Earth Microbiomes for Enhanced Pasture Recovery Anderson Santos de Freitas, Luís Felipe Guandalin Zagatto, Gabriel Silvestre Rocha, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5393010/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jan, 2025 Read the published version in BMC Microbiology → Version 1 posted 10 You are reading this latest preprint version Abstract Amazonian Dark Earths (ADEs) are fertile soils from the Amazon rainforest that harbor microorganisms with biotechnological potential. This study aimed to investigate the individual and potential synergistic effects of a 2% portion of ADEs and Urochloa brizantha cv. Marandu roots (Brazil's most common grass species used for pastures) on soil microbial communities and overall soil attributes in degraded soil. We conducted a comprehensive plant succession experiment, utilizing next-generation sequencing for 16S rDNA metabarcoding, enzymatic activity assays, and soil chemical properties analysis. Univariate and multivariate analyses were performed to understand better the microbial interactions within soil environments influenced by ADEs and U. brizantha roots, including differential abundance, diversity, and network analyses. Our findings reveal a complementary relationship between U. brizantha and ADEs, each contributing to distinct positive aspects of soil microbial communities and quality. The combined influence of U. brizantha roots and ADEs exhibited synergies that enhanced microbial diversity and enzyme activity. This balance supported plant growth and increased the general availability of beneficial bacteria in the soil, such as Chujaibacter and Curtobacterium , while reducing the presence of potentially pathogenic taxa. This research provided valuable insights into the intricate dynamics of plant-soil feedback, emphasizing the potential for complementary interactions between specific plant species and unique soil environments like ADEs. The findings highlight the potential for pasture ecological rehabilitation and underscore the benefits of integrating plant and soil management strategies to optimize soil characteristics. Amplicon Data Ecological Restoration Microbial Ecology Next-Generation Sequencing Soil Science Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Urochloa brizantha cv. Marandu, commonly known as signalgrass, is the most used species for pastures in the Brazilian Amazon rainforest due to its resistance to harsh conditions, such as fire and grazing, and high biomass production[ 1 ]. Once studies have highlighted its ability to increase soil organic matter content, it could be a dynamic player in soil health and ecological rehabilitation, fostering a microbial haven that improves nutrient cycling and carbon storage[ 2 , 3 ]. Furthermore, its dense root system promotes soil aggregation, enhancing water infiltration and erosion resistance[ 4 , 5 ]. Researchers also demonstrated its effectiveness in improving soil fertility and microbial diversity in previously impoverished soils, providing a most suitable environment for future plants in ecological succession[ 6 ]. Amazonian Dark Earths (ADE), by turn, are high-fertility soils formed in part by pre-Columbian Amerindian societies in the Amazon basin, thousands of years ago. These soils and their properties have also been connected with ecological restoration in recent studies due to the presence of a pathogen-suppressive and plant growth-promoting microbial community on them [ 7 – 9 ]. In addition, the nutrient content of ADE is commonly associated with a beneficial environment for plant development, such as trees and subsistence agriculture, leading to a huge potential to be sustainably explored [ 10 ]. Although both U. brizantha and ADE are promising tools for rehabilitation, many challenges arise. U. brizantha exhibits rapid growth and adaptation, but it increases the risk of invasiveness and reduces the establishment of novel species [ 11 , 12 ], whereas ADE, a non-renewable resource, is protected by genetic and archeological heritage, making it impossible to directly use this soil on a large scale for ecological rehabilitation[ 13 ]. For these reasons, it's crucial to understand the interplay between U. brizantha and ADE, to open their “black box” and comprehend how to build strategies for the management of U. brizantha , as to identify the key factors to mimic the beneficial microbiota provided by ADE in ecological rehabilitation to promote the sustainable use of its microbiome. Here, we designed an experiment with U. brizantha growing up in degraded soil from a pasture in the Amazon rainforest and later growing up with this conditioned soil (CS), with a small amount of 2% of ADE, and with the combination of CS and ADE (CS + ADE). Our aims were: (i) establish the relationship between growth and bacterial diversity in successive cultivation of U. brizantha , and (ii) study how the interplay between ADE and U. brizantha affects soil bacterial diversity and composition. Understanding these characteristics is fundamental for planning sustainable strategies to restore the soil and promote long-term health in the Central Amazon pasturelands. Material and Methods Soil source We collected 100kg of control soil from a degraded pasture in a farm located in the municipality of Presidente Figueiredo, state of Amazonas, Brazil, in the Central Amazon (2°2’4” S, 60°1’33”' W). According to the USDA classification system, the soil was classified as Oxisol[ 14 ]. Amazonian Dark Earths (approximately 20kg) were collected from the Embrapa Experimental Station, located in Iranduba, Amazonas, Brazil (03°26’00’’ S, 60°23’00’’ W). Both samplings were made in the first 20 cm of soil, representing the arable layer, at five different locations and were mixed. Part of the soil was sent to the EMBRAPA’s Laboratory of Soil Analysis, in Manaus-AM, for analysis of organic matter, pH, phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), aluminum (Al 3+ ), sulfur (S), copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), sand, clay, and silt. These analyses were carried out following the methods and standards suggested by van Raij and colleagues for Brazilian soils[ 15 ]. The other part was kept under refrigeration (4°C) for two days and then sent to Piracicaba, São Paulo, Brazil, where the experiment was conducted. This study was registered in the Brazilian National System for Management of Genetic Patrimonial and Associated Traditional Knowledge (SISGEN) under the access number AD13FB3. Experimental design The greenhouse experiment was conducted in two phases. In phase I (conditioning phase), twenty 3L pots were filled with control soil (from degraded pasture collected in the Amazon) and seeds of Urochloa brizantha cv. Marandu were sowed in 15 of them. The remaining five pots were kept without plants, as a Negative Control during the experiment. After seed germination, the number of plants in each pot was normalized to all pots having the same number of ramets. These plants were kept in the greenhouse for 60 days and were watered until reaching the field capacity once every 48 hours. After that, the aerial part of the plants was then removed and the soil with the remaining roots was used as an inoculum for treatments in phase II. In phase II, we tested the growth of new seeds of U. brizantha in four treatments: 100% of control soil (Control), 80% of Control Soil + 20% of Conditioned Soil with U. brizantha (CS), 98% of Control Soil + 2% of fresh Amazonian Dark Earths (ADE), and 78% of Control Soil + 20% of Conditioned Soil + 2% of fresh ADE (CS + ADE). The interest in these treatments lies in evaluating the feedback effects of pasture roots microbiota, ADE microbiota, and the combined effects of these two factors on plant growth. All treatments were also applied to pots without plant as a negative control. The experiment included five replicates per treatment in phase II, with 40 experimental pots, and was kept in the greenhouse for 120 days at 23.8 ºC (± 2.9 ºC) and 64% (± 11%) of air moisture, watered with deionized water until reaching the field capacity once every 48 hours. Sampling At the end of the experiment, we measured plant height for each plant using a measuring tape, considering the distance between the soil and the higher plant leaf. The canopy area was measured by measuring two perpendicular pairs of points in the canopies and computing the multiplication of these two distances. All the aerial parts were collected and dried in an oven at 60 ºC for 48 hours and then weighed to measure the dry matter. Soil samples were collected from the surrounding area close to the roots for DNA extraction and enzyme activity analyses. Samples for DNA extraction were frozen at -20 ºC until the extraction time, and samples for enzymes were kept with a breather and refrigerated at 5 ºC until the measurements. Molecular Procedures Microbial DNA was extracted from 0.25g of soil using the DNeasy PowerLyzer PowerSoil Kit (Qiagen, Hilden, Germany) using the manufacturers’ instructions and the modifications suggested by Venturini and colleagues[ 16 ]. The quality was measured using a Nanodrop™ 2000c spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), considering as suitable for downstream analysis all samples with DNA concentrations higher than 10 ng uL − 1 and A260/A280 ratios between 1.70 and 2.00. Amplification and sequencing were performed by Novogene Corporation Inc. (Sacramento, CA, USA) using standard approaches as defined by the Earth Microbiome Project[ 17 ]. The V3-V4 region of the 16S rDNA was amplified to determine the abundance of prokaryotes (bacteria and archaea) in samples using the updated primers 515F[ 18 ] and 816R[ 19 ]. The paired-end sequencing with 2 x 250 bp reads was performed using the Illumina HiSeq 2500 platform. The raw reads used in this work can be found in the Sequence Read Archive (SRA) under the project number PRJNA1157008. Besides, enzyme activity analyses were performed for the soil of each pot. We tested the activity of acid phosphatases using the colorimetric method proposed by Tabatabai, at pH 5.5[ 20 ]. β-glucosidase activity was evaluated using ρ-nitrophenyl-β-D-glucopyranoside as a substrate[ 21 ]. Finally, the activity of arylsulfatase was analyzed by the hydrolysis of potassium p-nitrophenyl sulfate, incubating the soil sample for 1 h at 37 ºC[ 22 ]. All products were evaluated by colorimetric determination at 410 nm using an ELISA microplate reader LMR FLEX UV-VIS i (Loccus Biotecnologia, Cotia, SP, Brazil). Data analyses All bioinformatics and statistical analyses were performed in the R environment (version 4.3.0) using the RStudio software (version 2023.09.1 + 494)[ 23 ]. The code for the analyses performed in this study can be found publicly on GitHub at: https://github.com/FreitasAndy/PSFforAmazonianPastures . Figures were produced using the ggplot2 package[ 24 ], and some of these figures were edited only for aesthetic purposes (i.e. changing colors and fonts) using the Inkscape 1.3.2 program. Because the data did not adjust to the normal distribution, we proceeded a downstream analysis suitable for non-parametric data. We used Kruskal-Wallis followed by the post hoc Dunn test[ 25 , 26 ] to test differences in plant growth (dry matter, root length, canopy area, and plant height), chemical properties (OM, pH, P, K, Ca, Mg, H, Al 3+ ), and enzymatic activity (acid phosphatase, beta-glucosidase, and arylsulfatase). The raw reads from sequencing were analyzed using the DADA2 pipeline[ 27 ], considering acceptable sequences with a mean quality score greater than 30. Filtered reads were grouped into amplicon sequence variants (ASVs) and matched to taxonomy using the SILVA database v. 138.1[ 28 ]. The resulting ASV table was imported into both a phyloseq object[ 29 ] and a microeco’s R6 object[ 30 ] for downstream analysis. Alpha diversity was calculated by considering the number of different taxa identified in each sample (observed diversity), and dominance of taxa was calculated by the inverse Simpson index, considering a confidence level of 95% by the Kruskal-Wallis test post hoc the Dunn’s test. Beta diversity was calculated by transforming the dataset into a centered log ratio (clr), to reflect the compositional structure of the data. Data ordination was performed using Euclidean, and nonmetric multidimensional scaling was plotted on the two first axes. Significance was calculated by permutational multivariate analysis of variance (PERMANOVA), at the level of significance of 5% and 999 permutations, using the adonis function from the package vegan[ 31 ]. Differential abundance analysis of each treatment per plant against the control was accessed by the ALDEx2 algorithm[ 32 ], considering significant differences between those with p-value < 0.01 calculated by Welch’s test, and also with effect size bigger than 1. The functional estimation for each sample was carried out using the FAPROTAX tool, which presumes the function of microorganisms from an ASV table based on previously published studies with those taxa[ 33 ]. The results were plotted as a heatmap representing key potential functions in soil health and management. Finally, correlation network analyses were performed at the genus level using the SpiecEasi algorithm[ 34 ], considering significant correlations higher than 70% with p-values lower than 0.001, thereby capturing only strong and most trustable correlations. Results Initial soil came from a very degraded environment To perform this experiment, we collected soil from a degraded pasture in the Central Amazon that has been covered with U. brizantha for over 20 years. Besides the expected conditions of increased compaction and low grass abundance, this soil presented lower organic matter content and nutrient balance (Table 1 ), especially phosphorus (P), potassium (K), and sodium (Na), in comparison with ADE. In contrast, ADE samples collected from a secondary forest had lower calcium (Ca) and magnesium (Mg) levels. Although the pH did not differ between the soils, the aluminium levels were higher in degraded oxisol (Table 1 ). Table 1 Description of chemical variables for each collected soil. Variable Amazonian Dark Earth Pasture Oxisol p-value pH (CaCl 2 ) 5.2 ± 0.1 5.1 ± 0.2 ns Organic Matter (%) 46.5 ± 6.5 26.5 ± 8.3 0.02 P (mg.dm − 3 ) 160.3 ± 38.4 7.5 ± 1.7 0.02 K (mmolc.dm − 3 ) 45.8 ± 20.1 0.4 ± 0.1 0.02 Na (mmolc.dm − 3 ) 6.3 ± 2.1 1.1 ± 0.9 0.02 Ca (mmolc.dm − 3 ) 6.8 ± 0.6 29.5 ± 1.7 0.02 Mg (mmolc.dm − 3 ) 1.2 ± 0.3 15.3 ± 1.0 0.02 H + Al 3 (mmolc.dm − 3 ) 4.3 ± 0.6 32.5 ± 10.8 0.02 Base Saturation (%) 82.0 ± 0.8 45.3 ± 3.0 0.02 p-values were calculated for the Kruskal Wallis chi-squared test, considered as significant values with p < 0.05. ns = not significantly different. ADE mitigated the negative legacy of U. brizantha The growth aspects in the degraded soil showed that the worst environment for U. brizantha to establish and grow was in the conditioned soil by itself. Plants in conspecific soil (CS) presented lower mass, height, and a smaller stem than the Control. However, the inclusion of 2% ADE drove all these factors to the same level as the control with or without the presence of U. brizantha , suggesting that ADE inhibits its conspecific negative effects. No difference was observed in root size, once the roots were spread all over the pots in all treatments. ADE highly influences the soil microbial structure ADE was this study's key driver for diversity (Fig. 02 ). All groups were separated by two-dimensional ordination, but the ADE treatment presented the most varied samples, all of them with a high distance from all other groups but heterogeneous among themselves (Fig. 02 -A). The ADE + CS treatment was the most diverse in taxa, with all other treatments presenting diversity similar to the control (Fig. 02 -B). However, there was no difference in the dominance indexes, even though it was highly variable in each treatment, especially in the CS and ADE groups (Fig. 03 -C). The phyla distribution in all treatments was also similar, with Proteobacteria, Acidobacteriota, Actinobacteria, Chloroflexi, Verrucomicrobia, and Firmicutes being the most common ones, with small variance either among samples or groups (Fig. 03 -D), with supposed differences in deeper taxonomic levels. ADE induces major microbial differences In the CS treatment, when U. brizantha showed less growth than the control, there was a depletion in several genera, such as Anaerolinea , Brevundinomas , Curtobacterium , Leptothrix , RB41 , and Sphingopyxis . On the other hand, Sphingorhabdus and Tychonema CCAP 1459-11B were increased in CS (Table 2 ). Table 2 List of microbial taxa with significant differences between treatments and control group after 120 days of growth of U. brizantha . CS (20%) x Control Genera rab.Control rab.CS effect overlap we.ep Anaerolinea 1.32 3.96 3.79 < 0.01 < 0.01 Brevundimonas 2.30 -0.31 -2.03 < 0.01 0.01 Curtobacterium 1.87 -5.23 -3.08 < 0.01 0.01 Leptothrix 2.35 -5.11 -3.01 < 0.01 < 0.01 RB41 4.96 7.21 2.96 < 0.01 0.01 Sphingopyxis 2.31 -5.42 -3.32 < 0.01 < 0.01 Sphingorhabdus 1.44 -5.42 -2.72 < 0.01 0.01 Tychonema CCAP 1459-11B 2.62 -5.18 -3.04 < 0.01 < 0.01 ADE (2%) x Control Genera rab.Control rab.ADE effect overlap we.ep Streptomyces 4.24 5.78 4.16 < 0.01 < 0.01 Paenibacillus 2.45 5.44 4.13 < 0.01 < 0.01 Lysinibacillus 2.59 5.04 4.10 < 0.01 < 0.01 Actinoallomurus 2.76 4.23 4.10 < 0.01 < 0.01 Solirubrobacter 2.88 4.61 3.89 < 0.01 < 0.01 Cohnella 0.55 4.05 3.88 < 0.01 < 0.01 Pseudonocardia 2.76 4.40 3.67 < 0.01 < 0.01 Kitasatospora 1.63 3.08 3.53 < 0.01 < 0.01 Luedemannella 4.93 6.77 3.49 < 0.01 < 0.01 Phaselicystis 3.75 5.10 3.36 < 0.01 < 0.01 Actinoplanes 1.57 3.62 3.35 < 0.01 < 0.01 Clostridium sensu stricto 12 2.18 3.60 3.31 < 0.01 < 0.01 Gaiella 5.37 6.77 3.25 < 0.01 0.01 Acidothermus 6.44 8.38 3.16 < 0.01 < 0.01 Conexibacter 5.75 8.28 2.77 < 0.01 0.01 Pedomicrobium 6.27 7.29 2.75 < 0.01 < 0.01 Ruminiclostridium 2.42 4.02 2.66 0.01 < 0.01 Mycobacterium 5.17 7.29 2.58 < 0.01 < 0.01 Micromonospora 2.57 4.31 2.52 < 0.01 0.01 Rugosimonospora 4.01 5.41 2.47 < 0.01 0.01 Clostridium sensu stricto 1 0.10 1.90 2.39 < 0.01 0.01 Dactylosporangium 2.36 4.56 2.34 < 0.01 < 0.01 Plantactinospora 0.03 1.90 2.19 < 0.01 0.01 Actinomadura 1.26 3.02 2.13 < 0.01 0.01 Paenarthrobacter 0.36 -5.52 -2.37 < 0.01 0.01 Sphingopyxis 0.97 -5.61 -2.57 < 0.01 0.01 CS + ADE x Control Genera rab.Control rab.CS + ADE effect overlap we.ep Chujaibacter 1.51 3.28 2.91 < 0.01 < 0.01 Curtobacterium 1.81 -5.55 -3.18 < 0.01 < 0.01 Sphingopyxis 2.23 -5.64 -3.24 < 0.01 0.01 Tychonema CCAP 1459-11B 2.55 -5.78 -3.56 < 0.01 < 0.01 rab.: relative abundance, median centered log-ratio value for the group mentioned; effect: effect size of the difference, a median of difference between groups on a log base 2 scale/largest median variation within groups, positive values indicate a higher abundance in the treatment group whereas negative values indicate higher abundance control group; overlap: confusion in assigning an observation Control or treatment; we.ep: the expected value of the Welch test p-value. The table includes all OTUs with effect > 1 and p-value ≤ 0.01. The addition of ADE without conditioned soil, which did not alter the plant growth but hardly altered the microbiota, increased the abundance of different genera, such as Streptomyces , Paenibacillus , Conella , and Lysinibacillus . Besides, ADE depleted the abundance of Paenarthobacter and Sphingopyxis . Finally, the addition of both CS and ADE, although the increase in observed diversity, was the closest treatment to control differential abundance. CS + ADE presented an increase in Chujaibacter and a decrease in Curtobacterium , Sphingopyxis (also decreased in only ADE treatment), and Tychonema CCAP 1459-11B (also decreased in only CS treatment). Putative functions were driven by both CS and ADE In addition to increasing the abundance of beneficial bacteria, both CS and ADE (alone or together) altered the genetic and functional profile of degraded soil. Treatments with the addition of U. brizantha roots (CS and CS + ADE) presented a higher number of phototrophic microorganisms (Fig. 4 ), as well as other carbon-fixing organisms, such as photosynthetic cyanobacteria. ADE treatment, in turn, increased the potential for nitrogen fixation and cellulolysis. When combined, these treatments presented both characteristics higher than the control, highlighting the cumulative effect of then. Enzymatic activity is increased by treatments Regarding enzymes, treatment with just conditioned soil (CS) decreased beta-glucosidase activity with no differences in acid phosphatase and arylsulfatase activities. ADE treatment, on the other hand, increased the activity of beta-glucosidase but did not affect any other enzymes. In the combined effect of both treatments (CS + ADE), the activity of beta-glucosidase was similar to that of the control, suggesting one more time the synergetic effect of each treatment. Surprisingly, the CS + ADE treatment also increased arylsulfatase activity, despite the treatments' null effect apart. The addition of ADE and CS increased the correlations among microorganisms Looking at the correlations in soil, we also found increased complexity in soil with the addition of both ADE and CS. CS increased the number of interactions (that is, edges) by six-fold compared with the control, whereas ADE alone increased it by 26-fold. However, when placed together, the complexity was less intense than that for each treatment alone, being only 0.46-fold higher than the control. Besides that, the number of vertexes was similar among all treatments, whereas all other aspects such as average degree, clustering coefficient, density, homogeneity, and centralization were higher in all treatments than in the control. These findings are consistent with the diversity analysis (Fig. 3 ) showing that taxa did not significantly change among treatments. Discussion Microorganisms are crucial for soil health and can drive the functions that improve ecological restoration projects. More than 350,000 km 2 of forest has been deforested in the last 33 years for cattle breeding, and 50% of the Brazilian pastures suffer some level of degradation, with the most important factor being the absence or insufficiency of management in the pastures [ 35 ]. Here, we showed lines of evidence that U. brizantha could promote the growth of beneficial microorganisms in the soil, which can be potentialized using microorganisms from ADE. First, we demonstrated that U. brizantha promotes a negative legacy in new U. brizantha plants (Fig. 01 ). It is known that conspecific feedback among grasses tends to be negative due to the accumulation of specific pathogens or competition among plants [ 36 ], which can favor the ecological succession in a well-managed scenario. However, the use of a small portion of ADE (we used only 2% in the experiment) reverted this negative legacy to neutral, which could be interesting in pastures where initial coverage with grass is required at the beginning of the recovery, promoting the later insertion of trees in a more suitable environment if management is properly applied. A second piece of evidence of the core work from U. brizantha and ADE is related to the taxa and functions they brought to the soil. CS treatment increased the abundance of genera known to degrade carbon or act in the nitrogen cycle by reducing ammonia oxidation or nitrite, as well as increasing the abundance of potential phototrophy (Fig. 4 ), improving carbon storage [ 37 , 38 ]. ADE treatment increased the abundance of several plant growth-promoting genera, such as Paenibacillus , Solirubrobacter , and Pedomicrobium (Table 4). It increased the abundance of potential nitrogen fixers (Fig. 4 ), highlighting the importance of ADE microbes in helping the establishment and growth of plants [ 39 – 41 ]. Treatment with ADE also decreased the amount of Sphingopyxis and Paenarthrobacter , two genera correlated with the degradation of aromatic compounds, such as environmental contaminants [ 42 , 43 ]. When combined in the treatment CS + ADE, the effect was the increase of genera that degrades complex carbohydrates, such as the ones secreted by U. brizantha , into sugars and short-chain organic acids to both plants and other microorganisms, as well as suppressing potential pathogens, showing that the plant can recruit microbes from ADE to improve the root-influenced soil zone [ 44 , 45 ]. In addition, CS treatment showed decreased activity of beta-glucosidase, the enzyme responsible for breaking down complex carbohydrates such as lignin and hemicellulose in soils [ 46 ]. The activity of this enzyme is inversely proportional to the increasing amount of carbon in the soil, which is acquired with the cultivation of U. brizantha [ 47 ]. ADE treatment increased the activity of this enzyme (Fig. 5 ), leading to maintenance in the activity of enzymes that increase the carbon fixation and availability to plants for a longer time, which is beneficial to late succession plants and for the environment. Also, the combination of CS + ADE increased the activity of arylsulfatase, the enzyme responsible for transforming organic sulfur into inorganic forms, a process essential for plant nutrition, as this nutrient is mostly immobilized in soil colloids and is vital for plant growth and yield [ 48 ]. Finally, CS and ADE increased the correlations among the microorganisms, suggesting a more connected microbiome (Fig. 6, Table 3 ). Fortunately, most of the correlations among microorganisms were positive in ADE treatment, with the majority of negative relationships relying only on CS + ADE treatment. It suggests control of some taxa for other ones, one more time suggesting a complementary role of U. brizantha and ADE in the soil and also explaining the highest diversity found in CS + ADE treatment, once there is probably more competition among them [ 49 ]. Table 3 Correlations and topological properties of soil microbiome networks. Attribute Control CS ADE CS + ADE Nodes a 423 446 439 454 Edges b 924 6123 26505 1349 Positive edges c 56.5% 42.2% 57.6% 31.0% Negative edges d 43.5% 57.8% 42.4% 69.0% Average degree e 4.37 27.46 120.75 5.94 Average path length f 3.86 1,76 1.39 3.02 Network diameter g 8.00 3,00 2.00 6.00 Clustering coefficient h 0.02 0.08 0.32 0.01 Density i 0.01 0.06 0.28 0.01 Heterogeneity j 0.76 0.38 0.27 0.52 Centralization k 0.09 0.10 0.21 0.04 a Microbial taxon (at genus level) with at least one significant (p 0.7 or 0.7 with P < 0.001). d Percentage of SpiecEasi-negative correlation ( < − 0.7 with P < 0.001). e The average number of connections per node in the network, the node connectivity. f Average network distance between all pairs of nodes or the average length of all edges in the network. g The longest distance between nodes in the network, measured in the number of edges. h How nodes are embedded in their neighborhood and the degree to which they tend to cluster together. i The degree of interconnectedness or the number of connections within the network. j The similarity or sameness of attributes among connected taxa. k The influence concentration using degree, closeness, and betweenness centrality metrics. The combination of this information leads to a combination of good characteristics that can be brought by both U. brizantha roots and ADE to the soil. Although grass species are known for increasing carbon content in soils (which is extremely important in degraded environments), the ADE brings plant-growth-promoting bacteria to the environment and increases the interconnection among taxa, leading to higher growth and inhibition of negative legacy from plants. We believe that these data support the choice of U. brizantha and ADE for ecological recovery processes as long as management is properly conducted to avoid the overpopulation of grasses and guarantee the survival of other species. Conclusions Here we showed that Urochloa brizantha and microorganisms from Amazonian Dark Earths alter the genetic and functional profile of soil. Our results point to a complementary relationship between these two treatments, converging together to an improvement in the soil microbial community and helping to generate a more suitable environment for plant growth in ecological rehabilitation. Declarations Ethics approval and consent to participate This study did not involve human participants, human data, or animals, and thus, ethical approval and consent to participate were not required. All experimental protocols and methodologies adhered to relevant institutional and international guidelines for research. Consent for publication All authors have reviewed and approved the manuscript for publication. There are no individual person’s data in this study that require consent for publication. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the São Paulo Research Foundation (FAPESP; grant number 2020/08927-0; and fellowships 2021/10.626-0, and 2022/05561-0), the Amazonas Research Foundation (FAPEAM; grant number 01.02.016301.00293/2021), and the Coordination for the Improvement of Higher Education Personnel–Brasil (CAPES; fellowship 887.597909/2021-00) – Finance Code 001. Author Contribution A.S.F. wrote the original draft, performed visualization, methodology, investigation, formal analysis, data curation, and conceptualization. L.F.G.Z., G.S.R., F.M., G.L.M., and S.S.S.Z. contributed to writing – review & editing, data acquisition, and validation. R.E.H. and A.W.M. contributed to conceptualization, provided resources and acquired funding. S.M.T. contributed to writing – review & editing, validation, supervision, resources, project administration, funding acquisition, data curation, and conceptualization. All authors reviewed the manuscript and agree with the submission. Acknowledgement We thank the São Paulo Research Foundation, the National Council for Scientific and Technological Development, the Amazonas Research Foundation, and the Coordination for the Improvement of Higher Education Personnel for their support in this work. Data Availability The raw reads used in this work can be found in the Sequence Read Archive (SRA) under the project number PRJNA1157008.The code for the analyses performed in this study can be found publicly on GitHub at: https://github.com/FreitasAndy/PSFforAmazonianPastures. References Koehler AD, Rossi ML, Carneiro VTC, Cabral GB, Martinelli AP, Dusi DMA. Anther development in Brachiaria brizantha (syn. Urochloa brizantha) and perspective for microspore in vitro culture. Protoplasma. 2023;260:571–87. Merloti LF, Bossolani JW, Mendes LW, Rocha GS, Rodrigues M, Asselta FO, et al. Investigating the effects of Brachiaria (Syn. Urochloa) varieties on soil properties and microbiome. Plant Soil. 2023. https://doi.org/10.1007/s11104-023-06225-x . Liu XB, Guo ZK, Huang GX. Sarocladium brachiariae sp. nov., an endophytic fungus isolated from Brachiaria brizantha. Mycosphere. 2017;8:827–34. Barbosa MV, Pedroso D, de Pinto F, Santos FA, dos Carneiro JV. MAC. Arbuscular mycorrhizal fungi and Urochloa brizantha : symbiosis and spore multiplication. Pesqui Agropecu Trop. 2019;49. da Silva ERO, Pereira MG, de Barros MM, dos Santos LMM, Gomes JHG, SOIL ORGANIC MATTER FRACTIONS AND MULTIVARIATE ANALYSIS IN THE DEFINITION OF PASTURE MANAGEMENT ZONES. Eng Agríc. 2022;42:e20220099. Pedroso D, de Barbosa F, Santos MV, Pinto JV, Siqueira FA, Carneiro JO. M a. C. Arbuscular mycorrhizal fungi favor the initial growth of Acacia mangium, sorghum bicolor, and Urochloa brizantha in soil contaminated with Zn, Cu, Pb, and Cd. Bulletin of Environmental Contamination and Toxicology. 2018;101:386–91. de Freitas AS, Zagatto LFG, Rocha GS, Muchalak F, Silva S, dos S, Muniz AW et al. Amazonian dark earths enhance the establishment of tree species in forest ecological restoration. Front Soil Sci. 2023;3. Lima AB, Cannavan FS, Navarrete AA, Teixeira WG, Kuramae EE, Tsai SM. Amazonian Dark Earth and Plant Species from the Amazon Region Contribute to Shape Rhizosphere Bacterial Communities. Microb Ecol. 2015;69:855–66. de Souza RC, Cannavan F, de Kanzaki S, Mendes LIB, Ferrari LW, Hanada BM. Analysis of a bacterial community structure and the diversity of phzF gene in samples of the Amazonian Dark Earths cultivated with cowpea [Vigna unguiculata (L.) Wald]. AJAR. 2018;13:1980–9. Glaser B, Birk JJ. State of the scientific knowledge on properties and genesis of Anthropogenic Dark Earths in Central Amazonia (terra preta de Índio). Geochim Cosmochim Acta. 2012;82:39–51. Perini M, Souza ML, de Filho JP. Forest restoration in old pasture areas dominated by Urochloa brizantha . Ciência Florestal. 2023;33:e65858–65858. Weidlich EWA, Flórido FG, Sorrini TB, Brancalion PHS. Controlling invasive plant species in ecological restoration: A global review. J Appl Ecol. 2020;57:1806–17. Santana G, TERRA PRETA DE, INDIO NA REGIÃO AMAZÓNICA. Scientia Amazonia. 2012;1:1–8. García-Gaines RA, Frankenstein S. USCS and the USDA Soil Classification System: Development of a Mapping Scheme. Fort Belvoir, VA: Defense Technical Information Center; 2015. van Raij B, de Andrade JC, Cantarella H, Quaggio JA. Análise química para avaliação da fertilidade de solos tropicais. Campinas: Instituto Agronômico; 2001. Venturini AM, Nakamura FM, Gontijo JB, da França AG, Yoshiura CA, Mandro JA, et al. Robust DNA protocols for tropical soils. Heliyon. 2020;6:e03830. Gilbert JA, Jansson JK, Knight R. The Earth Microbiome project: successes and aspirations. BMC Biol. 2014;12:69. Parada AE, Needham DM, Fuhrman JA. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol. 2016;18:1403–14. Apprill A, McNally S, Parsons R, Weber L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat Microb Ecol. 2015;75:129–37. Tabatabai MA. Soil Enzymes. Methods of Soil Analysis. John Wiley & Sons, Ltd; 1994. pp. 775–833. Eivazi F, Tabatabai MA. Phosphatases in soils. Soil Biol Biochem. 1977;9:167–72. Eivazi F, Tabatabai MA. Glucosidases and galactosidases in soils. Soil Biol Biochem. 1988;20:601–6. R Development Core Team. R: A Language and Environment for Statistical Computing. 2022. Wickham H. ggplot2. WIREs Computational Statistics. 2011;3:180–5. Kruskal WH, Wallis WA. Use of Ranks in One-Criterion Variance Analysis. J Am Stat Assoc. 1952;47:583–621. Dinno A. Nonparametric Pairwise Multiple Comparisons in Independent Groups using Dunn’s Test. Stata J. 2015;15:292–300. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41 Database issue:D590–6. McMurdie PJ, Holmes S. phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE. 2013;8:e61217. Liu C, Cui Y, Li X, Yao M. microeco: an R package for data mining in microbial community ecology. FEMS Microbiol Ecol. 2021;97:fiaa255. Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, et al. Vegan: community ecology package. R package vegan, vers. 2.2-1. World Agroforestry Centre Nairobi, Kenya; 2015. Fernandes AD, Macklaim JM, Linn TG, Reid G, Gloor GB. ANOVA-Like Differential Expression (ALDEx) Analysis for Mixed Population RNA-Seq. PLoS ONE. 2013;8:e67019. Louca S, Parfrey LW, Doebeli M. Decoupling function and taxonomy in the global ocean microbiome. Science. 2016;353:1272–7. Kurtz ZD, Müller CL, Miraldi ER, Littman DR, Blaser MJ, Bonneau RA. Sparse and Compositionally Robust Inference of Microbial Ecological Networks. PLoS Comput Biol. 2015;11:e1004226. Projeto MapBiomas. Coleção 4.1 da Série Anual de Mapas de Cobertura e Uso de Solo do Brasil. 2020. Crawford KM, Hawkes CV. Soil precipitation legacies influence intraspecific plant–soil feedback. Ecology. 2020;101:e03142. Sekiguchi Y, Yamada T, Hanada S, Ohashi A, Harada H, Kamagata Y. Anaerolinea thermophila gen. nov., sp. nov. and Caldilinea aerophila gen. nov., sp. nov., novel filamentous thermophiles that represent a previously uncultured lineage of the domain Bacteria at the subphylum level. Int J Syst Evol MicroBiol. 2003;53:1843–51. Liu X, Wang H, Wang W, Cheng X, Wang Y, Li Q et al. Nitrate determines the bacterial habitat specialization and impacts microbial functions in a subsurface karst cave. Front Microbiol. 2023;14. Pellegrinetti TA, Cunha IDCM da, de Chaves MG, de Freitas AS, Silva AVR da, Tsai SM et al. Draft genome sequences of representative Paenibacillus polymyxa, Bacillus cereus, Fictibacillus sp., and Brevibacillus agri strains isolated from Amazonian dark earth. Microbiology Resource Announcements. 2023;12:e00574-23. Navarrete AA, Cannavan FS, Taketani RG, Tsai SM. A Molecular Survey of the Diversity of Microbial Communities in Different Amazonian Agricultural Model Systems. Diversity. 2010;2:787–809. Cunha I. CM da, Silva AVR da, Boleta EHM, Pellegrinetti TA, Zagatto LFG, Zagatto S dos SS,. The interplay between the inoculation of plant growth-promoting rhizobacteria and the rhizosphere microbiome and their impact on plant phenotype. Microbiological Research. 2024;283:127706. Rosas-Díaz J, Escobar-Zepeda A, Adaya L, Rojas-Vargas J, Cuervo-Amaya DH, Sánchez-Reyes A, et al. Paenarthrobacter sp. GOM3 Is a Novel Marine Species With Monoaromatic Degradation Relevance. Front Microbiol. 2021;12:713702. Sharma M, Khurana H, Singh DN, Negi RK. The genus Sphingopyxis: Systematics, ecology, and bioremediation potential - A review. J Environ Manage. 2021;280:111744. Kim S-J, Ahn J-H, Weon H-Y, Hong S-B, Seok S-J, Kim J-S, et al. Chujaibacter soli gen. nov., sp. nov., isolated from soil. J Microbiol. 2015;53:592–7. Rodrigues M, Bortolini PC, Neto CK, de Andrade EA, dos Passos AI, Pacheco FP, et al. Unlocking higher yields in Urochloa brizantha: the role of basalt powder in enhancing soil nutrient availability. Discov Soil. 2024;1:4. Sengupta S, Datta M, Datta S. Chapter 5 - β-Glucosidase: Structure, function and industrial applications. In: Goyal A, Sharma K, editors. Glycoside Hydrolases. Academic; 2023. pp. 97–120. de Oliveira WCM, Bonfim-Silva EM, Araújo da Silva TJ, Pereira Freire Ferraz A, Lima Guimarães S, Menegaz Meneghetti LA. Soil Organic Matter and Microbial Biomass Under Cultivation of Urochloa Brizantha Fertilized with Wood Ash in the Cerrado of Mato Grosso. Commun Soil Sci Plant Anal. 2024;55:2090–102. Tabatabai MA, Bremner JM. Arylsulfatase Activity of Soils. Soil Sci Soc Am J. 1970;34:225–9. Mendes LW, Tsai SM, Navarrete AA, de Hollander M, van Veen JA, Kuramae EE. Soil-Borne Microbiome: Linking Diversity to Function. Microb Ecol. 2015;70:255–65. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Jan, 2025 Read the published version in BMC Microbiology → Version 1 posted Editorial decision: Revision requested 11 Dec, 2024 Reviews received at journal 04 Dec, 2024 Reviews received at journal 04 Dec, 2024 Reviewers agreed at journal 26 Nov, 2024 Reviewers agreed at journal 24 Nov, 2024 Reviewers agreed at journal 13 Nov, 2024 Reviewers invited by journal 13 Nov, 2024 Editor assigned by journal 12 Nov, 2024 Submission checks completed at journal 07 Nov, 2024 First submitted to journal 05 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-5393010","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":381927322,"identity":"7f8fe185-39fc-4e5e-a18e-cc1406e1ba58","order_by":0,"name":"Anderson Santos de Freitas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYHACAzDJ3sDAcABIy4E4zERp4QGqPwDExqRpAVmT2EBIC//s5o2PK/7Y5PFIHz54+ENNXfqG82cPMBfuwa1F4s6xYsOzbWnFPHxpCQcOHDucu+FGXgLzjGd4rLmRYybZ2HA4cT8Pj8GBA2wHgFp4DJjBzsQB5G/kmP9s+HM4sYeH/8OBA//q0g3On8GvxQBoC2MDG0gLD8OBg23MCQYHcvBrMbyRVizZ2JYG1MJmcOBs32HDmUC/HJ6BR4vcjeSNHxv+2AC1MD/+UPGtTp7v/NmDjwvwaMEGeBhI1ADSMgpGwSgYBaMAGQAALEFcGRr23uYAAAAASUVORK5CYII=","orcid":"","institution":"University of São Paulo","correspondingAuthor":true,"prefix":"","firstName":"Anderson","middleName":"Santos","lastName":"de Freitas","suffix":""},{"id":381927323,"identity":"de6356bd-01cf-4840-8ffa-eaf7e5b98bdf","order_by":1,"name":"Luís Felipe Guandalin Zagatto","email":"","orcid":"","institution":"Netherlands Institute of Ecology","correspondingAuthor":false,"prefix":"","firstName":"Luís","middleName":"Felipe Guandalin","lastName":"Zagatto","suffix":""},{"id":381927324,"identity":"ae821a0e-3234-4a9d-9d8d-4b12ef3b5570","order_by":2,"name":"Gabriel Silvestre Rocha","email":"","orcid":"","institution":"Netherlands Institute of Ecology","correspondingAuthor":false,"prefix":"","firstName":"Gabriel","middleName":"Silvestre","lastName":"Rocha","suffix":""},{"id":381927325,"identity":"2b642bda-8dfc-4d34-8fa8-72a0429335d5","order_by":3,"name":"Franciele Muchalak","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Franciele","middleName":"","lastName":"Muchalak","suffix":""},{"id":381927326,"identity":"11f43899-0ed5-47c4-91bb-838d03319be3","order_by":4,"name":"Guilherme Lucio Martins","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Guilherme","middleName":"Lucio","lastName":"Martins","suffix":""},{"id":381927327,"identity":"13388669-6364-4f1f-898d-0921840c392b","order_by":5,"name":"Solange Santos Silva-Zagatto","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Solange","middleName":"Santos","lastName":"Silva-Zagatto","suffix":""},{"id":381927328,"identity":"fe1f4e46-4a5a-4358-b10c-9de64b60618f","order_by":6,"name":"Rogério Eiji Hanada","email":"","orcid":"","institution":"National Institute for Amazonian Research","correspondingAuthor":false,"prefix":"","firstName":"Rogério","middleName":"Eiji","lastName":"Hanada","suffix":""},{"id":381927329,"identity":"41cfbd47-e902-4781-9b88-8bfbd90430c6","order_by":7,"name":"Aleksander Westphal Muniz","email":"","orcid":"","institution":"Brazilian Agricultural Research Corporation","correspondingAuthor":false,"prefix":"","firstName":"Aleksander","middleName":"Westphal","lastName":"Muniz","suffix":""},{"id":381927330,"identity":"301d58d1-f9c5-4f8f-a6c2-e9e97fce891e","order_by":8,"name":"Siu Mui Tsai","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Siu","middleName":"Mui","lastName":"Tsai","suffix":""}],"badges":[],"createdAt":"2024-11-05 07:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5393010/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5393010/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12866-024-03741-3","type":"published","date":"2025-01-17T15:57:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":69830893,"identity":"40950383-68f4-42dd-b33a-ab1f36be26b8","added_by":"auto","created_at":"2024-11-25 15:37:09","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":104921,"visible":true,"origin":"","legend":"\u003cp\u003eGrowth of \u003cem\u003eU. brizantha \u003c/em\u003eafter 120 days of experiment in four different treatments. (A) Production of aerial dry matter. (B) Plant height. (C) Stem diameter at ground level. *Significantly different from Control calculated by the Kruskal Wallis chi-squared test (p\u0026lt;0.05) post hoc Dunn test.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5393010/v1/3354a0511426541d3c60324b.jpg"},{"id":69830896,"identity":"bb9e33f3-ea87-4e7b-b9dc-2b80874bcd3d","added_by":"auto","created_at":"2024-11-25 15:37:09","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":211883,"visible":true,"origin":"","legend":"\u003cp\u003eMicrobial structure of soil cultivated with \u003cem\u003eU. brizantha \u003c/em\u003ein four different treatments. (A) Observed diversity calculated by the total number of different taxa found in each treatment. Whiskers represent the standard deviation. *significantly different from control (p\u0026lt;0.05). (B) Dominance calculated by the inverse Simpson index. No differences were assigned at 95% of confidence. (C) Beta diversity calculated by Euclidean distance and plotted in a non-metric multidimensional scaling. (D) Distribution of the top 6 phyla in each treatment and split by sample.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5393010/v1/d3885044f808527c06c049ae.jpg"},{"id":69830895,"identity":"5375be11-569f-4713-a6e2-cd1981db900e","added_by":"auto","created_at":"2024-11-25 15:37:09","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":115698,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap illustrating the predicted functional profiles of microbial communities across different soil treatments. Each row represents a specific microbial function, while each column corresponds to a treatment group. The color intensity of the spots varies from red to blue, with red indicating a higher relative abundance of the associated function, while blue represents a lower abundance. This figure underscores the dynamic shifts in microbial community functions, providing insights into the role of specific treatments in enhancing or suppressing certain microbial activities.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5393010/v1/6047204e5b8611f35347ea9e.jpg"},{"id":69830894,"identity":"f82cfe8a-c70d-4863-a995-0bbbe603bd22","added_by":"auto","created_at":"2024-11-25 15:37:09","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":107515,"visible":true,"origin":"","legend":"\u003cp\u003eBar chart depicting the enzymatic activity levels observed across soil treatments. Each bar represents the mean enzymatic activity for a specific treatment, with error bars indicating the standard deviation. Asterisks (*) denote statistically significant differences between treatments, with p-values \u0026lt; 0.05, as determined by the Kruskal-Wallis chi-squared test followed by Dunn's post hoc test.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5393010/v1/dabe8e7ef9740bbed82d3933.jpg"},{"id":74284863,"identity":"859af8ab-f662-4fc5-a5c7-7b1878ac8bf1","added_by":"auto","created_at":"2025-01-20 16:13:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1551945,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5393010/v1/92eda951-08a5-402d-89eb-0f84021d548c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Harnessing the Synergy of Urochloa brizantha and Amazonian Dark Earth Microbiomes for Enhanced Pasture Recovery","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cem\u003eUrochloa brizantha\u003c/em\u003e cv. Marandu, commonly known as signalgrass, is the most used species for pastures in the Brazilian Amazon rainforest due to its resistance to harsh conditions, such as fire and grazing, and high biomass production[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Once studies have highlighted its ability to increase soil organic matter content, it could be a dynamic player in soil health and ecological rehabilitation, fostering a microbial haven that improves nutrient cycling and carbon storage[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Furthermore, its dense root system promotes soil aggregation, enhancing water infiltration and erosion resistance[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Researchers also demonstrated its effectiveness in improving soil fertility and microbial diversity in previously impoverished soils, providing a most suitable environment for future plants in ecological succession[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmazonian Dark Earths (ADE), by turn, are high-fertility soils formed in part by pre-Columbian Amerindian societies in the Amazon basin, thousands of years ago. These soils and their properties have also been connected with ecological restoration in recent studies due to the presence of a pathogen-suppressive and plant growth-promoting microbial community on them [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition, the nutrient content of ADE is commonly associated with a beneficial environment for plant development, such as trees and subsistence agriculture, leading to a huge potential to be sustainably explored [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough both \u003cem\u003eU. brizantha\u003c/em\u003e and ADE are promising tools for rehabilitation, many challenges arise. \u003cem\u003eU. brizantha\u003c/em\u003e exhibits rapid growth and adaptation, but it increases the risk of invasiveness and reduces the establishment of novel species [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], whereas ADE, a non-renewable resource, is protected by genetic and archeological heritage, making it impossible to directly use this soil on a large scale for ecological rehabilitation[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. For these reasons, it's crucial to understand the interplay between \u003cem\u003eU. brizantha\u003c/em\u003e and ADE, to open their \u0026ldquo;black box\u0026rdquo; and comprehend how to build strategies for the management of \u003cem\u003eU. brizantha\u003c/em\u003e, as to identify the key factors to mimic the beneficial microbiota provided by ADE in ecological rehabilitation to promote the sustainable use of its microbiome.\u003c/p\u003e \u003cp\u003eHere, we designed an experiment with \u003cem\u003eU. brizantha\u003c/em\u003e growing up in degraded soil from a pasture in the Amazon rainforest and later growing up with this conditioned soil (CS), with a small amount of 2% of ADE, and with the combination of CS and ADE (CS\u0026thinsp;+\u0026thinsp;ADE). Our aims were: (i) establish the relationship between growth and bacterial diversity in successive cultivation of \u003cem\u003eU. brizantha\u003c/em\u003e, and (ii) study how the interplay between ADE and \u003cem\u003eU. brizantha\u003c/em\u003e affects soil bacterial diversity and composition. Understanding these characteristics is fundamental for planning sustainable strategies to restore the soil and promote long-term health in the Central Amazon pasturelands.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSoil source\u003c/h2\u003e \u003cp\u003eWe collected 100kg of control soil from a degraded pasture in a farm located in the municipality of Presidente Figueiredo, state of Amazonas, Brazil, in the Central Amazon (2\u0026deg;2\u0026rsquo;4\u0026rdquo; S, 60\u0026deg;1\u0026rsquo;33\u0026rdquo;' W). According to the USDA classification system, the soil was classified as Oxisol[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Amazonian Dark Earths (approximately 20kg) were collected from the Embrapa Experimental Station, located in Iranduba, Amazonas, Brazil (03\u0026deg;26\u0026rsquo;00\u0026rsquo;\u0026rsquo; S, 60\u0026deg;23\u0026rsquo;00\u0026rsquo;\u0026rsquo; W). Both samplings were made in the first 20 cm of soil, representing the arable layer, at five different locations and were mixed.\u003c/p\u003e \u003cp\u003ePart of the soil was sent to the EMBRAPA\u0026rsquo;s Laboratory of Soil Analysis, in Manaus-AM, for analysis of organic matter, pH, phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), aluminum (Al\u003csup\u003e3+\u003c/sup\u003e), sulfur (S), copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), sand, clay, and silt. These analyses were carried out following the methods and standards suggested by van Raij and colleagues for Brazilian soils[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The other part was kept under refrigeration (4\u0026deg;C) for two days and then sent to Piracicaba, S\u0026atilde;o Paulo, Brazil, where the experiment was conducted. This study was registered in the Brazilian National System for Management of Genetic Patrimonial and Associated Traditional Knowledge (SISGEN) under the access number AD13FB3.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental design\u003c/h3\u003e\n\u003cp\u003eThe greenhouse experiment was conducted in two phases. In phase I (conditioning phase), twenty 3L pots were filled with control soil (from degraded pasture collected in the Amazon) and seeds of \u003cem\u003eUrochloa brizantha\u003c/em\u003e cv. Marandu were sowed in 15 of them. The remaining five pots were kept without plants, as a Negative Control during the experiment. After seed germination, the number of plants in each pot was normalized to all pots having the same number of ramets. These plants were kept in the greenhouse for 60 days and were watered until reaching the field capacity once every 48 hours. After that, the aerial part of the plants was then removed and the soil with the remaining roots was used as an inoculum for treatments in phase II.\u003c/p\u003e \u003cp\u003eIn phase II, we tested the growth of new seeds of \u003cem\u003eU. brizantha\u003c/em\u003e in four treatments: 100% of control soil (Control), 80% of Control Soil\u0026thinsp;+\u0026thinsp;20% of Conditioned Soil with \u003cem\u003eU. brizantha\u003c/em\u003e (CS), 98% of Control Soil\u0026thinsp;+\u0026thinsp;2% of fresh Amazonian Dark Earths (ADE), and 78% of Control Soil\u0026thinsp;+\u0026thinsp;20% of Conditioned Soil\u0026thinsp;+\u0026thinsp;2% of fresh ADE (CS\u0026thinsp;+\u0026thinsp;ADE). The interest in these treatments lies in evaluating the feedback effects of pasture roots microbiota, ADE microbiota, and the combined effects of these two factors on plant growth. All treatments were also applied to pots without plant as a negative control. The experiment included five replicates per treatment in phase II, with 40 experimental pots, and was kept in the greenhouse for 120 days at 23.8 \u0026ordm;C (\u0026plusmn;\u0026thinsp;2.9 \u0026ordm;C) and 64% (\u0026plusmn;\u0026thinsp;11%) of air moisture, watered with deionized water until reaching the field capacity once every 48 hours.\u003c/p\u003e\n\u003ch3\u003eSampling\u003c/h3\u003e\n\u003cp\u003eAt the end of the experiment, we measured plant height for each plant using a measuring tape, considering the distance between the soil and the higher plant leaf. The canopy area was measured by measuring two perpendicular pairs of points in the canopies and computing the multiplication of these two distances. All the aerial parts were collected and dried in an oven at 60 \u0026ordm;C for 48 hours and then weighed to measure the dry matter. Soil samples were collected from the surrounding area close to the roots for DNA extraction and enzyme activity analyses. Samples for DNA extraction were frozen at -20 \u0026ordm;C until the extraction time, and samples for enzymes were kept with a breather and refrigerated at 5 \u0026ordm;C until the measurements.\u003c/p\u003e\n\u003ch3\u003eMolecular Procedures\u003c/h3\u003e\n\u003cp\u003eMicrobial DNA was extracted from 0.25g of soil using the DNeasy PowerLyzer PowerSoil Kit (Qiagen, Hilden, Germany) using the manufacturers\u0026rsquo; instructions and the modifications suggested by Venturini and colleagues[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The quality was measured using a Nanodrop\u0026trade; 2000c spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), considering as suitable for downstream analysis all samples with DNA concentrations higher than 10 ng uL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and A260/A280 ratios between 1.70 and 2.00.\u003c/p\u003e \u003cp\u003eAmplification and sequencing were performed by Novogene Corporation Inc. (Sacramento, CA, USA) using standard approaches as defined by the Earth Microbiome Project[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The V3-V4 region of the 16S rDNA was amplified to determine the abundance of prokaryotes (bacteria and archaea) in samples using the updated primers 515F[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and 816R[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The paired-end sequencing with 2 x 250 bp reads was performed using the Illumina HiSeq 2500 platform. The raw reads used in this work can be found in the Sequence Read Archive (SRA) under the project number PRJNA1157008.\u003c/p\u003e \u003cp\u003eBesides, enzyme activity analyses were performed for the soil of each pot. We tested the activity of acid phosphatases using the colorimetric method proposed by Tabatabai, at pH 5.5[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. β-glucosidase activity was evaluated using ρ-nitrophenyl-β-D-glucopyranoside as a substrate[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Finally, the activity of arylsulfatase was analyzed by the hydrolysis of potassium p-nitrophenyl sulfate, incubating the soil sample for 1 h at 37 \u0026ordm;C[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. All products were evaluated by colorimetric determination at 410 nm using an ELISA microplate reader LMR FLEX UV-VIS i (Loccus Biotecnologia, Cotia, SP, Brazil).\u003c/p\u003e\n\u003ch3\u003eData analyses\u003c/h3\u003e\n\u003cp\u003eAll bioinformatics and statistical analyses were performed in the R environment (version 4.3.0) using the RStudio software (version 2023.09.1\u0026thinsp;+\u0026thinsp;494)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The code for the analyses performed in this study can be found publicly on GitHub at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/FreitasAndy/PSFforAmazonianPastures\u003c/span\u003e\u003cspan address=\"https://github.com/FreitasAndy/PSFforAmazonianPastures\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Figures were produced using the ggplot2 package[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and some of these figures were edited only for aesthetic purposes (i.e. changing colors and fonts) using the Inkscape 1.3.2 program. Because the data did not adjust to the normal distribution, we proceeded a downstream analysis suitable for non-parametric data.\u003c/p\u003e \u003cp\u003eWe used Kruskal-Wallis followed by the \u003cem\u003epost hoc\u003c/em\u003e Dunn test[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] to test differences in plant growth (dry matter, root length, canopy area, and plant height), chemical properties (OM, pH, P, K, Ca, Mg, H, Al\u003csup\u003e3+\u003c/sup\u003e), and enzymatic activity (acid phosphatase, beta-glucosidase, and arylsulfatase).\u003c/p\u003e \u003cp\u003eThe raw reads from sequencing were analyzed using the DADA2 pipeline[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], considering acceptable sequences with a mean quality score greater than 30. Filtered reads were grouped into amplicon sequence variants (ASVs) and matched to taxonomy using the SILVA database v. 138.1[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The resulting ASV table was imported into both a phyloseq object[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and a microeco\u0026rsquo;s R6 object[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] for downstream analysis.\u003c/p\u003e \u003cp\u003eAlpha diversity was calculated by considering the number of different taxa identified in each sample (observed diversity), and dominance of taxa was calculated by the inverse Simpson index, considering a confidence level of 95% by the Kruskal-Wallis test post hoc the Dunn\u0026rsquo;s test. Beta diversity was calculated by transforming the dataset into a centered log ratio (clr), to reflect the compositional structure of the data. Data ordination was performed using Euclidean, and nonmetric multidimensional scaling was plotted on the two first axes. Significance was calculated by permutational multivariate analysis of variance (PERMANOVA), at the level of significance of 5% and 999 permutations, using the adonis function from the package vegan[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDifferential abundance analysis of each treatment per plant against the control was accessed by the ALDEx2 algorithm[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], considering significant differences between those with p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01 calculated by Welch\u0026rsquo;s test, and also with effect size bigger than 1.\u003c/p\u003e \u003cp\u003eThe functional estimation for each sample was carried out using the FAPROTAX tool, which presumes the function of microorganisms from an ASV table based on previously published studies with those taxa[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The results were plotted as a heatmap representing key potential functions in soil health and management. Finally, correlation network analyses were performed at the genus level using the SpiecEasi algorithm[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], considering significant correlations higher than 70% with p-values lower than 0.001, thereby capturing only strong and most trustable correlations.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eInitial soil came from a very degraded environment\u003c/h2\u003e \u003cp\u003eTo perform this experiment, we collected soil from a degraded pasture in the Central Amazon that has been covered with \u003cem\u003eU. brizantha\u003c/em\u003e for over 20 years. Besides the expected conditions of increased compaction and low grass abundance, this soil presented lower organic matter content and nutrient balance (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), especially phosphorus (P), potassium (K), and sodium (Na), in comparison with ADE. In contrast, ADE samples collected from a secondary forest had lower calcium (Ca) and magnesium (Mg) levels. Although the pH did not differ between the soils, the aluminium levels were higher in degraded oxisol (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of chemical variables for each collected soil.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmazonian Dark Earth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePasture Oxisol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH (CaCl\u003csub\u003e2\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ens\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganic Matter (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e46.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e26.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP (mg.dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e160.3\u0026thinsp;\u0026plusmn;\u0026thinsp;38.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK (mmolc.dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e45.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNa (mmolc.dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCa (mmolc.dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMg (mmolc.dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH\u0026thinsp;+\u0026thinsp;Al\u003csub\u003e3\u003c/sub\u003e (mmolc.dm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBase Saturation (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e82.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e45.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ep-values were calculated for the Kruskal Wallis chi-squared test, considered as significant values with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. ns\u0026thinsp;=\u0026thinsp;not significantly different.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eADE mitigated the negative legacy of\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eU. brizantha\u003c/span\u003e\u003c/p\u003e \u003cp\u003eThe growth aspects in the degraded soil showed that the worst environment for \u003cem\u003eU. brizantha\u003c/em\u003e to establish and grow was in the conditioned soil by itself. Plants in conspecific soil (CS) presented lower mass, height, and a smaller stem than the Control. However, the inclusion of 2% ADE drove all these factors to the same level as the control with or without the presence of \u003cem\u003eU. brizantha\u003c/em\u003e, suggesting that ADE inhibits its conspecific negative effects. No difference was observed in root size, once the roots were spread all over the pots in all treatments.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eADE highly influences the soil microbial structure\u003c/h3\u003e\n\u003cp\u003eADE was this study's key driver for diversity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e02\u003c/span\u003e). All groups were separated by two-dimensional ordination, but the ADE treatment presented the most varied samples, all of them with a high distance from all other groups but heterogeneous among themselves (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e02\u003c/span\u003e-A). The ADE\u0026thinsp;+\u0026thinsp;CS treatment was the most diverse in taxa, with all other treatments presenting diversity similar to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e02\u003c/span\u003e-B). However, there was no difference in the dominance indexes, even though it was highly variable in each treatment, especially in the CS and ADE groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e03\u003c/span\u003e-C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe phyla distribution in all treatments was also similar, with Proteobacteria, Acidobacteriota, Actinobacteria, Chloroflexi, Verrucomicrobia, and Firmicutes being the most common ones, with small variance either among samples or groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e03\u003c/span\u003e-D), with supposed differences in deeper taxonomic levels.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eADE induces major microbial differences\u003c/h2\u003e \u003cp\u003eIn the CS treatment, when \u003cem\u003eU. brizantha\u003c/em\u003e showed less growth than the control, there was a depletion in several genera, such as \u003cem\u003eAnaerolinea\u003c/em\u003e, \u003cem\u003eBrevundinomas\u003c/em\u003e, \u003cem\u003eCurtobacterium\u003c/em\u003e, \u003cem\u003eLeptothrix\u003c/em\u003e, \u003cem\u003eRB41\u003c/em\u003e, and \u003cem\u003eSphingopyxis\u003c/em\u003e. On the other hand, \u003cem\u003eSphingorhabdus\u003c/em\u003e and \u003cem\u003eTychonema CCAP 1459-11B\u003c/em\u003e were increased in CS (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of microbial taxa with significant differences between treatments and control group after 120 days of growth of \u003cem\u003eU. brizantha\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eCS (20%) x Control\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erab.Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003erab.CS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eeffect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eoverlap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ewe.ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnaerolinea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBrevundimonas\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCurtobacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLeptothrix\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRB41\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSphingopyxis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSphingorhabdus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTychonema CCAP 1459-11B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADE (2%) x Control\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erab.Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003erab.ADE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eeffect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eoverlap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ewe.ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStreptomyces\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePaenibacillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLysinibacillus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eActinoallomurus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSolirubrobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCohnella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePseudonocardia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKitasatospora\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLuedemannella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePhaselicystis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eActinoplanes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eClostridium sensu stricto 12\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGaiella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcidothermus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eConexibacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePedomicrobium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRuminiclostridium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMycobacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMicromonospora\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRugosimonospora\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eClostridium sensu stricto 1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDactylosporangium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePlantactinospora\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eActinomadura\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePaenarthrobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSphingopyxis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCS\u0026thinsp;+\u0026thinsp;ADE x Control\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erab.Control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003erab.CS\u0026thinsp;+\u0026thinsp;ADE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eeffect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eoverlap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ewe.ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChujaibacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCurtobacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSphingopyxis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTychonema CCAP 1459-11B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003erab.: relative abundance, median centered log-ratio value for the group mentioned; effect: effect size of the difference, a median of difference between groups on a log base 2 scale/largest median variation within groups, positive values indicate a higher abundance in the treatment group whereas negative values indicate higher abundance control group; overlap: confusion in assigning an observation Control or treatment; we.ep: the expected value of the Welch test p-value. The table includes all OTUs with effect\u0026thinsp;\u0026gt;\u0026thinsp;1 and p-value\u0026thinsp;\u0026le;\u0026thinsp;0.01.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe addition of ADE without conditioned soil, which did not alter the plant growth but hardly altered the microbiota, increased the abundance of different genera, such as \u003cem\u003eStreptomyces\u003c/em\u003e, \u003cem\u003ePaenibacillus\u003c/em\u003e, \u003cem\u003eConella\u003c/em\u003e, and \u003cem\u003eLysinibacillus\u003c/em\u003e. Besides, ADE depleted the abundance of \u003cem\u003ePaenarthobacter\u003c/em\u003e and \u003cem\u003eSphingopyxis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eFinally, the addition of both CS and ADE, although the increase in observed diversity, was the closest treatment to control differential abundance. CS\u0026thinsp;+\u0026thinsp;ADE presented an increase in \u003cem\u003eChujaibacter\u003c/em\u003e and a decrease in \u003cem\u003eCurtobacterium\u003c/em\u003e, \u003cem\u003eSphingopyxis\u003c/em\u003e (also decreased in only ADE treatment), and \u003cem\u003eTychonema CCAP 1459-11B\u003c/em\u003e (also decreased in only CS treatment).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePutative functions were driven by both CS and ADE\u003c/h2\u003e \u003cp\u003eIn addition to increasing the abundance of beneficial bacteria, both CS and ADE (alone or together) altered the genetic and functional profile of degraded soil. Treatments with the addition of \u003cem\u003eU. brizantha\u003c/em\u003e roots (CS and CS\u0026thinsp;+\u0026thinsp;ADE) presented a higher number of phototrophic microorganisms (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), as well as other carbon-fixing organisms, such as photosynthetic cyanobacteria. ADE treatment, in turn, increased the potential for nitrogen fixation and cellulolysis. When combined, these treatments presented both characteristics higher than the control, highlighting the cumulative effect of then.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEnzymatic activity is increased by treatments\u003c/h2\u003e \u003cp\u003eRegarding enzymes, treatment with just conditioned soil (CS) decreased beta-glucosidase activity with no differences in acid phosphatase and arylsulfatase activities. ADE treatment, on the other hand, increased the activity of beta-glucosidase but did not affect any other enzymes. In the combined effect of both treatments (CS\u0026thinsp;+\u0026thinsp;ADE), the activity of beta-glucosidase was similar to that of the control, suggesting one more time the synergetic effect of each treatment. Surprisingly, the CS\u0026thinsp;+\u0026thinsp;ADE treatment also increased arylsulfatase activity, despite the treatments' null effect apart.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eThe addition of ADE and CS increased the correlations among microorganisms\u003c/h2\u003e \u003cp\u003eLooking at the correlations in soil, we also found increased complexity in soil with the addition of both ADE and CS. CS increased the number of interactions (that is, edges) by six-fold compared with the control, whereas ADE alone increased it by 26-fold. However, when placed together, the complexity was less intense than that for each treatment alone, being only 0.46-fold higher than the control. Besides that, the number of vertexes was similar among all treatments, whereas all other aspects such as average degree, clustering coefficient, density, homogeneity, and centralization were higher in all treatments than in the control. These findings are consistent with the diversity analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e) showing that taxa did not significantly change among treatments.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMicroorganisms are crucial for soil health and can drive the functions that improve ecological restoration projects. More than 350,000 km\u003csup\u003e2\u003c/sup\u003e of forest has been deforested in the last 33 years for cattle breeding, and 50% of the Brazilian pastures suffer some level of degradation, with the most important factor being the absence or insufficiency of management in the pastures [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Here, we showed lines of evidence that \u003cem\u003eU. brizantha\u003c/em\u003e could promote the growth of beneficial microorganisms in the soil, which can be potentialized using microorganisms from ADE.\u003c/p\u003e \u003cp\u003eFirst, we demonstrated that \u003cem\u003eU. brizantha\u003c/em\u003e promotes a negative legacy in new \u003cem\u003eU. brizantha\u003c/em\u003e plants (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e01\u003c/span\u003e). It is known that conspecific feedback among grasses tends to be negative due to the accumulation of specific pathogens or competition among plants [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], which can favor the ecological succession in a well-managed scenario. However, the use of a small portion of ADE (we used only 2% in the experiment) reverted this negative legacy to neutral, which could be interesting in pastures where initial coverage with grass is required at the beginning of the recovery, promoting the later insertion of trees in a more suitable environment if management is properly applied.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA second piece of evidence of the core work from \u003cem\u003eU. brizantha\u003c/em\u003e and ADE is related to the taxa and functions they brought to the soil. CS treatment increased the abundance of genera known to degrade carbon or act in the nitrogen cycle by reducing ammonia oxidation or nitrite, as well as increasing the abundance of potential phototrophy (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), improving carbon storage [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. ADE treatment increased the abundance of several plant growth-promoting genera, such as \u003cem\u003ePaenibacillus\u003c/em\u003e, \u003cem\u003eSolirubrobacter\u003c/em\u003e, and \u003cem\u003ePedomicrobium\u003c/em\u003e (Table\u0026nbsp;4). It increased the abundance of potential nitrogen fixers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), highlighting the importance of ADE microbes in helping the establishment and growth of plants [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Treatment with ADE also decreased the amount of \u003cem\u003eSphingopyxis\u003c/em\u003e and \u003cem\u003ePaenarthrobacter\u003c/em\u003e, two genera correlated with the degradation of aromatic compounds, such as environmental contaminants [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. When combined in the treatment CS\u0026thinsp;+\u0026thinsp;ADE, the effect was the increase of genera that degrades complex carbohydrates, such as the ones secreted by \u003cem\u003eU. brizantha\u003c/em\u003e, into sugars and short-chain organic acids to both plants and other microorganisms, as well as suppressing potential pathogens, showing that the plant can recruit microbes from ADE to improve the root-influenced soil zone [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition, CS treatment showed decreased activity of beta-glucosidase, the enzyme responsible for breaking down complex carbohydrates such as lignin and hemicellulose in soils [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The activity of this enzyme is inversely proportional to the increasing amount of carbon in the soil, which is acquired with the cultivation of \u003cem\u003eU. brizantha\u003c/em\u003e [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. ADE treatment increased the activity of this enzyme (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), leading to maintenance in the activity of enzymes that increase the carbon fixation and availability to plants for a longer time, which is beneficial to late succession plants and for the environment. Also, the combination of CS\u0026thinsp;+\u0026thinsp;ADE increased the activity of arylsulfatase, the enzyme responsible for transforming organic sulfur into inorganic forms, a process essential for plant nutrition, as this nutrient is mostly immobilized in soil colloids and is vital for plant growth and yield [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFinally, CS and ADE increased the correlations among the microorganisms, suggesting a more connected microbiome (Fig.\u0026nbsp;6, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Fortunately, most of the correlations among microorganisms were positive in ADE treatment, with the majority of negative relationships relying only on CS\u0026thinsp;+\u0026thinsp;ADE treatment. It suggests control of some taxa for other ones, one more time suggesting a complementary role of \u003cem\u003eU. brizantha\u003c/em\u003e and ADE in the soil and also explaining the highest diversity found in CS\u0026thinsp;+\u0026thinsp;ADE treatment, once there is probably more competition among them [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelations and topological properties of soil microbiome networks.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttribute\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eADE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCS\u0026thinsp;+\u0026thinsp;ADE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNodes\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEdges\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1349\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive edges\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative edges\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage degree\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage path length\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNetwork diameter\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClustering coefficient\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDensity\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterogeneity\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentralization\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003eMicrobial taxon (at genus level) with at least one significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and strong correlation (\u0026gt;\u0026thinsp;0.7 or \u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;0.7).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003eNumber of connections/correlations obtained by the SpiecEasi algorithm.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ec\u003c/sup\u003ePercentage of SpiecEasi-positive correlation (\u0026gt;\u0026thinsp;0.7 with P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ed\u003c/sup\u003ePercentage of SpiecEasi-negative correlation (\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;0.7 with P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ee\u003c/sup\u003eThe average number of connections per node in the network, the node connectivity.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ef\u003c/sup\u003eAverage network distance between all pairs of nodes or the average length of all edges in the network.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eg\u003c/sup\u003eThe longest distance between nodes in the network, measured in the number of edges.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eh\u003c/sup\u003eHow nodes are embedded in their neighborhood and the degree to which they tend to cluster together.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ei\u003c/sup\u003eThe degree of interconnectedness or the number of connections within the network.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ej\u003c/sup\u003eThe similarity or sameness of attributes among connected taxa.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ek\u003c/sup\u003eThe influence concentration using degree, closeness, and betweenness centrality metrics.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe combination of this information leads to a combination of good characteristics that can be brought by both \u003cem\u003eU. brizantha\u003c/em\u003e roots and ADE to the soil. Although grass species are known for increasing carbon content in soils (which is extremely important in degraded environments), the ADE brings plant-growth-promoting bacteria to the environment and increases the interconnection among taxa, leading to higher growth and inhibition of negative legacy from plants. We believe that these data support the choice of \u003cem\u003eU. brizantha\u003c/em\u003e and ADE for ecological recovery processes as long as management is properly conducted to avoid the overpopulation of grasses and guarantee the survival of other species.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eHere we showed that \u003cem\u003eUrochloa brizantha\u003c/em\u003e and microorganisms from Amazonian Dark Earths alter the genetic and functional profile of soil. Our results point to a complementary relationship between these two treatments, converging together to an improvement in the soil microbial community and helping to generate a more suitable environment for plant growth in ecological rehabilitation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThis study did not involve human participants, human data, or animals, and thus, ethical approval and consent to participate were not required. All experimental protocols and methodologies adhered to relevant institutional and international guidelines for research.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eAll authors have reviewed and approved the manuscript for publication. There are no individual person\u0026rsquo;s data in this study that require consent for publication.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the S\u0026atilde;o Paulo Research Foundation (FAPESP; grant number 2020/08927-0; and fellowships 2021/10.626-0, and 2022/05561-0), the Amazonas Research Foundation (FAPEAM; grant number 01.02.016301.00293/2021), and the Coordination for the Improvement of Higher Education Personnel\u0026ndash;Brasil (CAPES; fellowship 887.597909/2021-00) \u0026ndash; Finance Code 001.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.S.F. wrote the original draft, performed visualization, methodology, investigation, formal analysis, data curation, and conceptualization. L.F.G.Z., G.S.R., F.M., G.L.M., and S.S.S.Z. contributed to writing \u0026ndash; review \u0026amp; editing, data acquisition, and validation. R.E.H. and A.W.M. contributed to conceptualization, provided resources and acquired funding. S.M.T. contributed to writing \u0026ndash; review \u0026amp; editing, validation, supervision, resources, project administration, funding acquisition, data curation, and conceptualization. All authors reviewed the manuscript and agree with the submission.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the S\u0026atilde;o Paulo Research Foundation, the National Council for Scientific and Technological Development, the Amazonas Research Foundation, and the Coordination for the Improvement of Higher Education Personnel for their support in this work.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe raw reads used in this work can be found in the Sequence Read Archive (SRA) under the project number PRJNA1157008.The code for the analyses performed in this study can be found publicly on GitHub at: https://github.com/FreitasAndy/PSFforAmazonianPastures.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKoehler AD, Rossi ML, Carneiro VTC, Cabral GB, Martinelli AP, Dusi DMA. Anther development in Brachiaria brizantha (syn. 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Ecology. 2020;101:e03142.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSekiguchi Y, Yamada T, Hanada S, Ohashi A, Harada H, Kamagata Y. Anaerolinea thermophila gen. nov., sp. nov. and Caldilinea aerophila gen. nov., sp. nov., novel filamentous thermophiles that represent a previously uncultured lineage of the domain Bacteria at the subphylum level. Int J Syst Evol MicroBiol. 2003;53:1843\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu X, Wang H, Wang W, Cheng X, Wang Y, Li Q et al. Nitrate determines the bacterial habitat specialization and impacts microbial functions in a subsurface karst cave. Front Microbiol. 2023;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePellegrinetti TA, Cunha IDCM da, de Chaves MG, de Freitas AS, Silva AVR da, Tsai SM et al. Draft genome sequences of representative Paenibacillus polymyxa, Bacillus cereus, Fictibacillus sp., and Brevibacillus agri strains isolated from Amazonian dark earth. 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Academic; 2023. pp. 97\u0026ndash;120.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Oliveira WCM, Bonfim-Silva EM, Ara\u0026uacute;jo da Silva TJ, Pereira Freire Ferraz A, Lima Guimar\u0026atilde;es S, Menegaz Meneghetti LA. Soil Organic Matter and Microbial Biomass Under Cultivation of Urochloa Brizantha Fertilized with Wood Ash in the Cerrado of Mato Grosso. Commun Soil Sci Plant Anal. 2024;55:2090\u0026ndash;102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTabatabai MA, Bremner JM. Arylsulfatase Activity of Soils. Soil Sci Soc Am J. 1970;34:225\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMendes LW, Tsai SM, Navarrete AA, de Hollander M, van Veen JA, Kuramae EE. Soil-Borne Microbiome: Linking Diversity to Function. Microb Ecol. 2015;70:255\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Amplicon Data, Ecological Restoration, Microbial Ecology, Next-Generation Sequencing, Soil Science","lastPublishedDoi":"10.21203/rs.3.rs-5393010/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5393010/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAmazonian Dark Earths (ADEs) are fertile soils from the Amazon rainforest that harbor microorganisms with biotechnological potential. This study aimed to investigate the individual and potential synergistic effects of a 2% portion of ADEs and \u003cem\u003eUrochloa brizantha\u003c/em\u003e cv. Marandu roots (Brazil's most common grass species used for pastures) on soil microbial communities and overall soil attributes in degraded soil. We conducted a comprehensive plant succession experiment, utilizing next-generation sequencing for 16S rDNA metabarcoding, enzymatic activity assays, and soil chemical properties analysis. Univariate and multivariate analyses were performed to understand better the microbial interactions within soil environments influenced by ADEs and \u003cem\u003eU. brizantha\u003c/em\u003e roots, including differential abundance, diversity, and network analyses. Our findings reveal a complementary relationship between \u003cem\u003eU. brizantha\u003c/em\u003e and ADEs, each contributing to distinct positive aspects of soil microbial communities and quality. The combined influence of \u003cem\u003eU. brizantha\u003c/em\u003e roots and ADEs exhibited synergies that enhanced microbial diversity and enzyme activity. This balance supported plant growth and increased the general availability of beneficial bacteria in the soil, such as \u003cem\u003eChujaibacter\u003c/em\u003e and \u003cem\u003eCurtobacterium\u003c/em\u003e, while reducing the presence of potentially pathogenic taxa. This research provided valuable insights into the intricate dynamics of plant-soil feedback, emphasizing the potential for complementary interactions between specific plant species and unique soil environments like ADEs. The findings highlight the potential for pasture ecological rehabilitation and underscore the benefits of integrating plant and soil management strategies to optimize soil characteristics.\u003c/p\u003e","manuscriptTitle":"Harnessing the Synergy of Urochloa brizantha and Amazonian Dark Earth Microbiomes for Enhanced Pasture Recovery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-25 15:37:05","doi":"10.21203/rs.3.rs-5393010/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-11T08:48:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-04T17:15:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-04T05:26:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"163433065284298475347866164591380357322","date":"2024-11-26T05:14:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"168843692884128856409251815052799227508","date":"2024-11-25T02:21:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121265024225683321611185019903111080911","date":"2024-11-13T15:07:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-13T14:23:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-13T03:52:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-07T11:40:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2024-11-05T07:12:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f8583b26-8436-478b-bd1b-a8b3852da5fe","owner":[],"postedDate":"November 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-20T16:07:04+00:00","versionOfRecord":{"articleIdentity":"rs-5393010","link":"https://doi.org/10.1186/s12866-024-03741-3","journal":{"identity":"bmc-microbiology","isVorOnly":false,"title":"BMC Microbiology"},"publishedOn":"2025-01-17 15:57:51","publishedOnDateReadable":"January 17th, 2025"},"versionCreatedAt":"2024-11-25 15:37:05","video":"","vorDoi":"10.1186/s12866-024-03741-3","vorDoiUrl":"https://doi.org/10.1186/s12866-024-03741-3","workflowStages":[]},"version":"v1","identity":"rs-5393010","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5393010","identity":"rs-5393010","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}