Applied Soll Ecology 143(201)26-34 Contents lists available at ScienceDirec Applied Soil Ecology ELSEVIER journal homepage:www.elsevier.com/locate/apsoil Bacterial community associated with rhizosphere of maize and cowpea in a subsequent cultivation Ademir sergio ferreira de arauio Ana roberta lima miranda"ricardo silva sousa" Lucas William Mendes,Jadson Emanuel Lopes Antunes",Louise Melo de Souza Oliveira, Fabio Fernando de Araujo,Vania Maria Maciel Melo,Marcia do Vale Barreto Figueiredo ARTICLE INFO ABSTRACT e is the sol stage of dev ng to plant munity. 1.Introduction sent contrasting rhizosphere traits tion requirements (Ro by plar etaowegion ar th 02 nulate the unity in n in with he sa stablishes p sitive interactions with roots an ability of the exudation (Zho 2017),while plant s it is ndes et a n by di of b y ha may sel species (Eisenhauer et al.,2017).Different plant groups,such as distinct bacterial community in the rhizosphere of Lotus comiculatus e(de j) ed form 15 May 2019 Accepted 23 May019
Contents lists available at ScienceDirect Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil Bacterial community associated with rhizosphere of maize and cowpea in a subsequent cultivation Ademir Sergio Ferreira de Araujoa,⁎ , Ana Roberta Lima Mirandaa , Ricardo Silva Sousaa , Lucas William Mendesb , Jadson Emanuel Lopes Antunesa , Louise Melo de Souza Oliveiraa , Fabio Fernando de Araujoc , Vania Maria Maciel Melod , Marcia do Vale Barreto Figueiredoe a Soil Quality Lab., Agricultural Science Center, Federal University of Piauí, Teresina, PI, Brazil b Laboratory of Molecular Ecology, CENA-USP, Piracicaba, SP, Brazil c University of Sao Paulo West, UNOESTE, Campus II, Presidente Prudente, SP, Brazil d Laboratório de Ecologia Microbiana e Biotecnologia, Federal University of Ceara, Fortaleza, CE, Brazil e Agronomic Institute of Pernambuco, Av. San Martin, Recife, PE, Brazil ARTICLE INFO Keywords: Bulk soil Metagenomics Zea mays Vigna unguiculata Soil microbiome ABSTRACT The rhizosphere is the soil zone influenced by the roots and its characteristics vary according to plant species and their stage of development. These different characteristics can influence the bacterial community inhabiting the rhizosphere niche that, in turn, influences plant growth and health. In this study, the bacterial community dynamics in the rhizosphere of maize and cowpea, in subsequent cultivation, were assessed using the 16S rRNA sequencing. Thus, during maize growth, soils were collected at 45 (flowering) and 75 (senescence) days. Afterward, during cowpea growth, the sampling occurred at 35 (flowering) and 65 (senescence) days. Our results showed differences between developmental stages within the same plant species. For maize, Acidobacteria decreased from flowering to senescence; while for cowpea, Proteobacteria, Armatimonadetes, WPS-2, and OP11 increased from flowering to senescence. Comparing the same developmental stage for both plant species, Proteobacteria, Elusimicrobia, WPS-2 decreased from maize flowering to cowpea flowering; while for the senescence stage, Acidobacteria, Armatimonadetes, and OP11 increased from maize to cowpea. Also, the rhizosphere community dynamic was more complex at the senescence stage compared to the flowering stage and bulk soil for both plants species. The results showed that the structure and diversity of bacterial community vary significantly according to plant species and, in a minor extent, their developmental stage. Also, we showed that the variation in rhizosphere activity during the plant growth could drive the responses of the bacterial community. 1. Introduction The rhizosphere is defined as the narrow region of soil that is directly influenced by plant roots (Chen et al., 2001). In this region, plant roots release exudates, i.e., organic compounds such as proteins and sugars, which stimulate the microbial community in comparison in with the bulk soil (Mougel et al., 2006). In the rhizosphere microbiome, bacterial community establishes positive interactions with roots and, thus, acts on essential functions in agriculture, such as nutrient acquisition, plant growth-promotion and protection against pathogens (Cavaglieri et al., 2009; Mendes et al., 2014, 2018a). The characteristics of rhizosphere vary in function of different plant species (Eisenhauer et al., 2017). Different plant groups, such as legumes and grass, present contrasting rhizosphere traits regarding root exudation and nutrient requirements (Rovira, 1969; Gransee and Wittenmayer, 2000). Legume roots can exude more amino acids and sugar than grassroots (Gransee and Wittenmayer, 2000), while grass requires more nutrients than legumes (Ghosh et al., 2009). Also, plants species within the same taxonomic group share similar characteristics of the rhizosphere, such as root biomass, and the amount and availability of the exudation (Zhou et al., 2017), while plant species belonging to different groups could present distinct rhizosphere traits. Therefore, it is expected that the bacterial community in the rhizosphere could be driven by differences in these traits, which may select different groups of bacteria. Indeed, a previous study has shown a distinct bacterial community in the rhizosphere of Lotus corniculatus https://doi.org/10.1016/j.apsoil.2019.05.019 Received 4 February 2019; Received in revised form 15 May 2019; Accepted 23 May 2019 ⁎ Corresponding author. E-mail address: ademir@ufpi.edu.br (A.S.F. de Araujo). Applied Soil Ecology 143 (2019) 26–34 Available online 06 June 2019 0929-1393/ © 2019 Elsevier B.V. All rights reserved. T
ASR血rata Applied Soil Ecology 143 (2019)26-34 ed with holcus lanat (eu inity in soil under ryegrass (grass)and MF MS CF CS rial com e高g nunity are shaped a ing to the pattern of root exu of the n the ere n plan osphere+2 devel e V4 region erlgroecosystemsudiesabouthg ain Reaction (PCR)reaction volume ned the fo Mainly for cowpea,theres about the structure of the Madison SA),5.0pL of buffe 5x (Mg L0 unit of platinum community addin ab rhi ect and the diver ty and structure of nd r 30s,with a final extension of 3 min at 72'C to ensure (2)h this study g,the PCR products ed up using Agencour A).ac ding t the fc factur 2.Material and methods 2.1.Experimental site and soil sampling ermined and d then nt was conducted at the De tofsoilscicnce f8.0 soil. he exr ntal design was con data we plot p d using QIME following the UPARSE ive plants m ys. eipictedandn3etooig" ered into OTUs at a %6 similarity cut-off folle amed MF)and 75 (se. 81 2. (bu soil)T and with soil ver 22.DNA extraction and sequencing or th Monte carlo pe tion test
(legume) when compared with Holcus lanatus (graminea) (Ladygina and Hedlund, 2010). Recently, Zhou et al. (2017) have found differences between the bacterial community in soil under ryegrass (grass) and alfalfa (legume). The plant developmental stage is another factor influencing the bacterial community in the rhizosphere (Mougel et al., 2006). During the plant growth, the roots exudation changes according to the stage of development, and the abundance and structure of the rhizospheric microbial community are shaped according to the pattern of root exudation that may vary from young seedling, flowering, to plant senescence (Dunfield and Germida, 2003). Indeed, Houlden et al. (2008) evaluated the response of the microbial community to the different growth stage of pea, wheat and sugar beet and observed changes in the bacterial community following the developmental stage for all the tested plants. Considering the crucial role of the rhizosphere microbiome for plant growth and health, it is essential to elucidate how different plant species at different growth stages select differently the microbial community inhabiting their rhizosphere. Maize (grass) and cowpea (legume) are two important plant species cultivated in the world being used for human and animal feeding and cover crop (Ramirez-Cabral et al., 2017; Boukar et al., 2016). Although these plants are distributed in several agroecosystems, studies about the bacterial community in the rhizosphere of these species are scarce. Mainly for cowpea, there is no information about the structure of the bacterial community in the rhizosphere. Also, it is unclear the effect of the different stage of development in these plants on the soil bacterial community. In order to determine the extent to which different plant species are able to select a distinct rhizospheric microbiome, in this study we hypothesized that (1) maize and cowpea, as different plant species, exert different rhizosphere effect and shape the diversity and structure of bacterial community differently; and (2) the soil bacterial community changes during the flowering and senescence of plants. Thus, this study aimed to evaluate the diversity and structure of the bacterial community in the rhizosphere of maize and cowpea during the flowering and senescence using the 16S rRNA sequencing. 2. Material and methods 2.1. Experimental site and soil sampling The experiment was conducted at the Department of Soil Science from the Federal University of Piauí, Brazil. The soil of the experimental site is classified as Fluvisol soil. The experimental design was completely randomized with three replicates. Each experimental plot presents 20 m2 (12 m2 of usable area). Maize (Zea mays L.) was sowed at a density of five plants m−1 and was grown for 75 days. Afterward, cowpea [Vigna unguiculata (L.) Walp.] was sowed at the density of six plants m−1 and was grown for 65 days. To measure the rhizospheric influence of each plant species on the bacterial community, soil samples adhered to the roots were collected and mixed to form a composite sample in each plot. During maize growth, soils were collected at 45 (flowering, named MF) and 75 (senescence, MS) days. During cowpea growth, the sampling occurred at 35 (flowering, CF) and 65 (senescence, CS) days. Soil samples without plants effects were collected as control (bulk soil). The soil samples were sieved (2-mm) and stored at −20 °C. Soil chemical and physical properties, estimated according to Embrapa (1997), are shown in Table 1. 2.2. DNA extraction and sequencing Total DNA was extracted from 0.5 g (total humid weight) of soil using the PowerLyzer PowerSoil DNA Isolation Kit (MoBIO Laboratories, Carlsbad, CA, USA), according to the manufacturer's instructions. The DNA extraction was performed in triplicate for each soil sample, totalizing 15 samples [(bulk soil + 2 rhizosphere + 2 developmental stage) × 3 replicates]. The V4 region of the 16S rRNA gene was amplified with regionspecific primers (515F/806R) (Caporaso et al., 2011). Each 25 μL Polymerase Chain Reaction (PCR) reaction volume contained the following: 12.25 μL of nuclease-free water (Certified Nuclease-free, Promega, Madison, WI, USA), 5.0 μL of buffer solution 5× (MgCl2 2 Mm), 0.3 mM dNTP's 0.3 μM of each primer (515 YF 40 μM e 806 R 10 μM), 1.0 unit of Platinum Taq polymerase High Fidelity in concentration of 0.5 μL (Invitrogen, Carlsbad, CA, USA), and 2.0 μL (10 ng μL−1 ) of template DNA. Moreover, a control reaction was performed by adding water in place of DNA. The conditions for PCR were as follows: 95 °C for 3 min to denature the DNA, with 35 cycles at 98 °C for 20 s, 55 °C for 20 s, and 72 °C for 30 s, with a final extension of 3 min at 72 °C to ensure complete elongation. After indexing, the PCR products were cleaned up using Agencourt AMPure XP – PCR purification beads (Beckman Coulter, Brea, CA, USA), according to the manufacturer's manual, and quantified using the dsDNA BR assay Kit (Invitrogen, Carlsbad, CA, USA) on a Qubit 2.0 fluorometer (Invitrogen, Carlsbad, CA, USA). Once quantified, an equimolar concentration of each library (50 ng) was pooled into a single tube. After quantification, the molarity of the pool was determined and diluted to 2 nM, denatured, and then diluted to a final concentration of 8.0 pM with a 20% PhiX (Illumina, San Diego, CA, USA) spike for loading into the Illumina MiSeq sequencing machine (Illumina, San Diego, CA, USA). Sequence data were processed using QIIME following the UPARSE standard pipeline according to Brazilian Microbiome Project (Pylro et al., 2014), to produce an OTU table and a set of representative sequences. Briefly, the reads were truncated at 240 bp and quality-filtered using a maximum expected error value of 0.5. Pre-filtered reads were dereplicated, and singletons were removed and filtered for additional chimeras using the RDP_gold database using USEARCH 7.0. These sequences were clustered into OTUs at a 97% similarity cut-off following the UPARSE pipeline. After clustering, the sequences were aligned and taxonomically classified against the Greengenes database (version 13.8). 2.3. Statistical analysis The community structure and its correlation with soil parameters were visualized using Redundancy analysis (RDA). All matrices were initially analyzed using Detrended Correspondent Analysis (DCA) to evaluate the distribution of the data, revealing that the best-fit mathematical model for the data was RDA. Forward selection (FS) and the Monte Carlo permutation test were applied with 1000 random permutations to verify the significance of environmental parameters upon the microbial community structure. RDA plots were generated using Table 1 Chemical and physical properties of soil. BS MF MS CF CS pH (water) 5.6 6.3 6.7 6.2 6.0 EC (dS m−1 ) 0.3 0.5 0.7 0.5 0.5 TOC (g kg−1 ) 5.9 5.9 6.7 5.4 5.6 P (mg kg−1 ) 5.5 5.8 6.0 4.8 4.3 K (mg kg−1 ) 70 89 85 81 78 Ca (mg kg−1 ) 213 317 328 320 296 Mg (mg kg−1 ) 38 61 64 61 58 Na (mg kg−1 ) 69 98 93 85 91 Sand (%) 60 60 60 60 60 Silt (%) 28 28 28 28 28 Clay (%) 12 12 12 12 12 BS – Bulk soil; MF – maize flowering; MS – maize senescence; CF – cowpea flowering; CS – cowpea senescence; TOC – total organic C; EC – electric conductivity. A.S.F. de Araujo, et al. Applied Soil Ecology 143 (2019) 26–34 27
Applied Soil Ecology 143 (2019)26-34 Ca oco 4.5 softy ware (Biometrics,Wageningen,the Netherlands) to test MANOVA)wa ao uniy structures.A 0 由e higher valus of pH,K.Na,and verify the proport ton of grou d shared betweer tre in se ng that bacteria that remain du ring s 210 that could change e the based on P.values and th ences related to the stage of development only for cowpea. mics the p the 3.2.Bacterial community composition and diversity nd Alm,2012).For the cal on he per sm that were used for P<0.01.The 28 1%6 of the 12150 genus lev the antly positive cutes (11%), eria (8.7 flexi (8.7%)an ng STAM higher abunda teri. ples.there was an increase i ce of the phy 3 Results the rhi 0.05ou betwe 3.1.Bacterial community structur teobacteria.Armatimo adet 50%of thev WPS-2,and P1 increased eA● PERMANOVA F=4.75 P =0.034 05B PERMANOVA F-2.46 P-0.005 0.4 0.3 02 0.1 8 ● 0.0 0.1 CEC 02 0 0 0.20.10.00.10.20.30.40.50.6 ●o NMDS1 -08 Axis1(29.1% 08 Rhizosphere (B)Not 一山。a 28
Canoco 4.5 software (Biometrics, Wageningen, the Netherlands). Permutational multivariate analysis of variance (PERMANOVA) was used to test whether sample categories harbored significantly different microbial community structures. Alpha diversity was calculated from a matrix of richness at the genus level using Shannon's index. PERMANOVA and alpha diversity indexes were calculated with the software PAST 3 (Hammer et al., 2001). Venn diagrams were also constructed to verify the proportion of groups exclusive and shared between treatments using the web tool Venny 2.1.0 (Oliveros, 2007). To visualize the differential microbial community composition among treatments, we used the Statistical Analysis of Metagenome Profile software (STAMP) (Parks et al., 2014). The OTU table generated from the 16S profiling was used as input. The comparison was based on P-values calculated using the two-sided Welch's t-test and the correction was made using Benjamini-Hochberg false discovery rate (Benjamini and Hochberg, 1995). To further assess the microbial community dynamics among the samples we conducted co-occurrence network analysis using the Phyton module ‘SparCC’ (Friedman and Alm, 2012). For the calculations, a table of frequency of hits affiliated at genus level was used for the analysis. For each network, SparCC correlations were calculated between microbial taxa and filtered based on the significance at P 50% of the variation in the first two axes of the plot (Fig. 1A), with the samples clustering according to the niche, i.e. bulk soil and rhizosphere (PERMANOVA, F = 4.75, P = 0.034). The RDA analysis also showed that the bacterial community of the bulk soil correlated with higher values of Ca. For rhizosphere samples, the bacterial community associated to maize correlated with higher values of Mg, P, TOC, and CEC, while for cowpea the community was associated with higher values of pH, K, Na, and EC. Also, the results showed a correlation between maize and cowpea rhizosphere in senescence, showing that bacteria that remain during senescence may be similar in both plant species, maybe due to the same rhizospheric soil that could change in different soils. To compare the bacterial community structure considering only rhizosphere samples, we computed a Bray-Curtis similarity matrix and coordinated into two dimensions using NMDS (Fig. 1B). The samples were grouped according to the plant species (PERMANOVA, F = 2.46, P = 0.005), with differences related to the stage of development only for cowpea. 3.2. Bacterial community composition and diversity After quality trimming, the bacterial community profiling using 16S rRNA gene sequencing generated 230,000 reads (an average of 15,000 sequences per sample) that were used for downstream analysis. The most abundant bacterial groups were affiliated to Actinobacteria (28.1% of the sequences), followed by Proteobacteria (21.5%), Firmicutes (11%), Acidobacteria (8.7%), Chloroflexi (8.7%) and Planctomycetes (8.6%) (Supplementary Fig. 1). When samples were compared using STAMP software, the abundance of specific bacterial phyla showed shifts from bulk soil to rhizospheric soils (Fig. 2). Bulk soil showed a higher abundance of Acidobacteria, Proteobacteria, Elusimicrobia, Armatimonadetes, and OP3; on the other hand, in the rhizosphere samples, there was an increase in abundance of the phyla Actinobacteria, Chlamydiae, Firmicutes and TM6 (P < 0.05). Comparing the rhizosphere sample within the same plant species, we found differences between developmental stages (Fig. 2). For maize, Acidobacteria decreased from flowering to senescence; while for cowpea, Proteobacteria, Armatimonadetes, WPS-2, and OP11 increased from flowering to senescence. Comparing the same developmental stage for both plant species, the results showed a decrease in Proteobacteria, Fig. 1. Structure of bacterial communities in bulk soil and rhizosphere of maize and cowpea plants at flowering and senescence developmental stages. (A) Redundancy analysis (RDA) of bacterial communities and soil characteristics. Arrows indicate correlation between environmental parameters and bacterial profile. (B) Non-metric multidimensional scaling ordination (NMDS) of Bray-Curtis similarity matrix of the bacterial profile from rhizosphere samples. The lines between dots represent the minimal spanning tree, which connects all points with minimal total length, based on the similarity index. Dashed lines in the graph indicate significant clusters (PERMANOVA, P < 0.05). MF = Maize flowering; MS = Maize senescence; CF = Cowpea flowering; CS = Cowpea senescence. A.S.F. de Araujo, et al. Applied Soil Ecology 143 (2019) 26–34 28
ASR血rgtd Applied Soil Ecology 143 (2019)26-34 BUlk ME MS CF CS ion of the most differ (P005) Elusimicrobia,WPS-from for the s ,Acidob nd OP11 orlie ng others (Supplementary fig. 2A 1B).I Gaiellace 0319-6A21 30 al stages ch plan distributed in the rhizosphere of maize and cowpea,respectively n trea S M based on Tukey surements revealed a de ng:CS-Cowpea senescenc 31.wd9 ea plant in compa hat ther ding on the na we four that bul k s ly preser the rhi est propor m e genera (1.7)(Fig. to%in thes ce (Fig 4A).On the other hand,the p t g 29
Elusimicrobia, WPS-2 from maize flowering to cowpea flowering; while for the senescence stage, Acidobacteria, Armatimonadetes, and OP11 increased from maize to cowpea. Interestingly, the phyla DeinococcusThermus and OP1 were exclusively abundant in maize and cowpea rhizosphere, respectively. In a lower taxonomic level, we compared bulk soil with the rhizosphere of maize and cowpea considering both developmental stages. In general, we observed an enrichment of specific families in the rhizosphere samples (Supplementary Fig. 2). Bulk soil presented a higher abundance of the families Isosphaeraceae, Chitinophagaceae, Nitrosomonadaceae among others (Supplementary Fig. 2A and B). In rhizosphere samples, there was an increased number of sequences af- filiated to the families Paenibacillaceae, Bacillaceae, Gaiellaceae, among others. Comparing the rhizosphere community between the plant species, we observed that 15 families were differently abundant. For example, the families Chthoniobacteraceae and 0319-6A21 (Nitrospirales) were more abundant in cowpea, while Oxalobacteraceae, Acetobacteraceae, Coxiellaceae, and Mycobacteriaceae were more abundant in maize rhizosphere (Supplementary Fig. 2C). We also compared the different developmental stages within each plant species and observed that nine and five bacterial families were differently distributed in the rhizosphere of maize and cowpea, respectively (Supplementary Fig. 3). The pattern of richness and diversity measurements revealed a decreased diversity in the rhizosphere of the cowpea plant in comparison with maize and bulk soil (Fig. 3). When the treatments were compared at the genus level using Venn diagrams, we found that bulk soil and rhizosphere samples shared > 50% of the detected genera (Fig. 4A, B). For maize, the proportion of genera exclusively present in the rhizosphere compared to the bulk soil increased from zero in the flowering, to 8.7% in the senescence (Fig. 4A). On the other hand, the proportion of genera exclusively present genera in cowpea decreased from the flowering (3.6%) to the senescence (2.4%) (Fig. 4B). This result reveals that there is a different rhizosphere effect depending on the plant species and the developmental time. When only the rhizosphere samples were compared, we observed that 51.9% of the detected genera are shared among all the samples, while the senescence of maize presented the highest proportion of exclusive genera (12.7%) (Fig. 4C). Fig. 2. Distribution of the most differential bacterial phyla based on 16S rRNA profile of samples from bulk soil and rhizosphere of maize and cowpea plants at flowering and senescence developmental stages. Boxes indicate IQR (75th to 25th of the data). The median value is shown as a line within the box and outliers are represented by dots. Different lower case letters refer to significant differences between treatments within each soil type based on Tukey's test (P < 0.05). MF = Maize flowering; MS = Maize senescence; CF = Cowpea flowering; CS = Cowpea senescence. Fig. 3. Taxonomic (A) richness and (B) diversity based on genus level at 97% similarity of the 16S rRNA gene sequencing. Error bars represent the standard deviation of three independent replicates. Different lower case letters refer to significant differences between treatments based on Tukey's HSD test (P < 0.05). MF = Maize flowering; MS = Maize senescence; CF = Cowpea flowering; CS = Cowpea senescence. A.S.F. de Araujo, et al. Applied Soil Ecology 143 (2019) 26–34 29
Apphed Soil 143(20)26-34 MS (A) (C) MS CF ME u CS a子 Bulk (B) Bulk and pro ween the bacterial so properties and 4.Discussion e of the ow ring and ser quent cultivation.In nted> 20%6 of the s n with chemical parameters was ria in soils (Liehr 2008.M t al 20m ndan study,the sc able pH (6.2)and content of nutrient e of ne of Ac nich are bett pted to ac Actinol acteria a d Prote a were favored by the condition minate in neutral and( number of of the bact minor extent, DA101,ad for Cs were Bacus and Micro ion and urient input. Thu
3.3. Correlation between the bacterial community and soil properties and community network The correlation of bacterial phyla with soil chemical properties was analyzed by Spearman's rank correlation (Table 2). The soil factors that presented correlation with more number of bacterial phyla were pH (9 phyla in total), followed by P (6), EC (4) and CEC (3). Interestingly, the phylum that presented more correlation with chemical parameters was Gemmatimonadetes (4 factors in total). The co-occurrence network analysis showed that, in general, rhizosphere samples at the senescence stage presented the highest complexity compared to the flowering stage and bulk soil for both plants species (Fig. 5). In all treatments, the number of positive correlations was higher than negatives; however, we observed an increase of negative correlation in the senescence stage for both plants. More speci- fically, CS was the most complex network, with 152 significant correlations (52% positives), high modularity (8.43) and average degree and coefficient of 4.28 and 0.369, respectively. The MS network was the second most complex, with 133 correlations (52% positives), modularity of 5.22 and average degree and coefficient of 4.83 and 0.516, respectively. Also, based on the number of connections and betweenness centrality we identified the key groups in each network. For bulk soil, the keynote was DA101; for MF were Bacillus and Mycobacterium; for MS were Bacillus, Mycobacterium, and Symbiobacterium; for CF was DA101, and for CS were Bacillus and Microlunatus. 4. Discussion Our study assessed the bacterial community in the rhizosphere of maize (grass) and cowpea (legume) as compared with bulk soil during the flowering and senescence period in subsequent cultivation. In a general view, our study found a dominance of Actinobacteria and Proteobacteria that represented > 20% of the sequences. There are several studies that have found a high abundance of Proteobacteria and Actinobacteria in soils (Liebner et al., 2008, Männistö et al., 2013; Araújo et al., 2017). However, we observed a lower abundance of Acidobacteria in comparison with Actinobacteria and Proteobacteria. In this study, the soil presented suitable pH (6.2) and content of nutrients, i.e. improved soil fertility, and these conditions contributed for a decreased abundance of Acidobacteria, which are better adapted to acid soils and oligotrophic environments (Kielak et al., 2016). In contrast, Actinobacteria and Proteobacteria were favored by these soil conditions since they predominate in neutral and nutrient-rich soils (Yang et al., 2017). The results showed changes in the bacterial community in the rhizosphere as compared with bulk soil, as confirmed by RDA. For the structure of the bacterial community in both rhizosphere soils, the NMDS pattern showed segregation between plant species and, in a minor extent, differences between plant developmental stages. This result was expected since the rhizospheric environment influences the bacterial community via root exudation and nutrient input. Thus, Actinobacteria, Chlamydiae, and Firmicutes increased their abundance Fig. 4. Venn diagrams showing the number and proportion of unique and shared genera at 97% similarity between (A) bulk soil and rhizosphere microbiome of maize; (B) bulk soil and rhizosphere microbiome of cowpea; and (C) between rhizosphere samples at the different developmental stage. MF = Maize flowering; MS = Maize senescence; CF = Cowpea flowering; CS = Cowpea senescence. A.S.F. de Araujo, et al. Applied Soil Ecology 143 (2019) 26–34 30
ASR血ranja et al Arplied Soil Ecology 143 (2019)26-34 aank orelation ttisic ewudnreatiy tc Soil factors p随 EC -0.83* -072 ac 069+ 8 0.75 079 -0.64 -073 -078 82 -0.57 -0.57 -0.58 -054 0.60 0.68 0.59 0.57 0.81*+ -0.66*+ -0.59 -0.55 -0.53* correlation are shown."P 0.05,"*P 0.01.Thermi Deino TOC-total organicC rom bulk soil to rhizo phere due to the enrichment of soil with nutrien 2010),these changes in root exudation,i.e.the diffe ent amount of results co te previous stu s alter the high DeAn and legum )On the other h and,the dec (Me bach et al. 1999 e legume teatyootcudhionsinC that les d ass differentially influence the struct obacteria,Elus ring of et al., 1990),and al on soi al proper es driven by thes ha cne roo en gras butes to in al pro )Thus,weobs crobial communities(Alvey).According to Urz et sphere as compared with cowpea rhizosphere.The phylum Fig 5. es the b The to key genera as fol
from bulk soil to rhizosphere due to the enrichment of soil with nutrient sources surrounding the roots. These results corroborate previous studies that found Actinobacteria, Chlamydiae and Firmicutes presenting high abundance in rhizospheric soils (Roesch et al., 2007; DeAngelis et al., 2009; Weinert et al., 2011; Mendes et al., 2011; Mendes et al., 2014). On the other hand, the decrease in Acidobacteria from bulk soil to rhizosphere may have occurred because the enrichment of the soil environment by root exudation since this group predominates in the oligotrophic environment as discussed above. Considering the bacterial community in the rhizosphere, the results support our hypotheses that different plant species and developmental stage affect the community assembly in the rhizosphere. The influence of plant species on the bacterial community is due to the physiological and biochemical differences between grass and legumes (Isobe et al., 2001). These differences are related with different quantity and quality of root exudation between plant species that vary over time (Miller et al., 1990), and alterations on soil chemical properties driven by these plants (Zhou et al., 2017). In this study, we did not characterize the root exudates, but it is well reported the differences between grass and legumes. These plants exudate compounds with different chemical pro- files into the rhizosphere, causing significant shifts in rhizosphere microbial communities (Alvey et al., 2003). According to Uroz et al., (2010), these changes in root exudation, i.e. the different amount of carbohydrates, carboxylic acids, and amino acids alter the rhizosphere environment and then discriminate the bacterial community. There is a distinct pattern of C source in the rhizosphere of grass and legume (Garland, 1996), where rhizosphere of grass species releases more carbohydrates (Merbach et al. 1999), while legume releases more amino acids (Isobe and Tsuboki, 1998). Previous studies have also shown that legume and grass differentially influence the structure and composition of the microbial community (Ladygina and Hedlund, 2010; Turner et al., 2013). Our data corroborate these previous observations, revealing that the rhizosphere community was distinct between the plant species (PERMANOVA P 0.7 (positive correlation – blue edges) or < −0.7 (negative correlation – red edges) and statistically significant (P < 0.01). Each node represents different bacterial genera. The size of the nodes is proportional to the number of connections (degree) and the color intensity indicates the betweeness centrality (darker color for higher values). The number inside the nodes refers to key genera as following: 1. DA101; 2. Mycobacterium; 3. Bacillus; 4. Symbiobacterium; 5. Microlunatus. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) A.S.F. de Araujo, et al. Applied Soil Ecology 143 (2019) 26–34 31
Applied Soil Ecology 143 (2019)26-34 Pro sents high metabolic versatility and includes a large group of ba t of the also f Is,mainly in the the th studies( ng et a Whe ed os bet d pH i nay ha ely pr D rding 2017)that reported root exu s and soil chemie cal properties lies have shown that the host genotype,to a extent,shape 2017:Mendes t al it is stil uncle arwhether 即ng On the other hand the iner sed abundance of Acidohe Finally,we use tiemtrepositioninth il.The these g oups of bacteria tinely.ou le.both ering and bulk soil.Als th bed as oligc probable c tition bet tha e,the g wi nalysis om wer prefere nt in m important in the net s in soils.b ized cial role b initiating the degra tion of c For thi phere of both the t et al.,2012).In th linke e comple occus-Ther antly found in maia 2013)and pr ogens this phylu the phere of ma ntly found i ia found in s nts and,althou t transformation (Li et al.2014).In cov ea.Mic ell c oting b the rhia Taken ether the c alysis revealed that th sof the ommu that the group Mi d o)Th 5.Conclusion m has small ge and a pr ed symbiotic or pa udied.this found in the hi ,nds taL,20184d 2014 can present similar.or nd diversity than hizosphe ng the s then et al.20 05).Chaudh et a erial community and iatro and did not find can infl ce Acknowledgments ed by This study was funded by on 30506920181T thar to the Centro de C e matica(CeGenBio
Proteobacteria presents high metabolic versatility and includes a large group of bacteria found in soils, mainly in the rhizosphere (Janssen, 2006). Proteobacteria was also found abundantly in the rhizosphere of maize in previous studies (Chauhan et al., 2011; Yang et al., 2017). On the other hand, cowpea presents the ability to change soil pH in the rhizosphere (Rao et al., 2002), which may have contributed to decrease the abundance of Proteobacteria. These results agree with Zhou et al. (2017) that reported root exudates and soil chemical properties as factors driving the soil microbial community, especially pH that is the primary chemical driver of the bacterial community in soil (Lauber et al., 2009). On the other hand, the increased abundance of Acidobacteria, Armatimonadetes, and OP11 in cowpea senescence suggests depletion of nutrients in the soil, since cowpea grew after maize and there was not nutrient reposition in the soil. Thus, these groups of bacteria were in- fluenced by the presence of oligotrophic soils as discussed previously. The increase of these groups in the senescence stage can also be linked to the decrease of rhizospheric effect. For example, both Acidobacteria and Armatimonadetes are described as oligotrophic groups that grow in environments with low input of nutrients (Tamaki et al., 2011; Kielak et al., 2016). The rhizospheric effect, i.e. the rhizodeposition of nutrients by plant roots, occurs up to the plant flowering, decreasing with the plant developmental stage. The differential abundance of some groups between flowering and senescence is also related to the type of exudate. Bacteria present in the rhizosphere of young plants have a preference for simple amino acids, while the groups present in mature plants prefer more complex carbohydrates (Houlden et al., 2008). This change in abundance of specific groups is an indicative of a change in the quality of plant root exudates. For example, Firmicutes plays a crucial role by initiating the degradation of complex substrates such as plant cells walls, starch particles and mucin (Flint et al., 2012). In this context, the increasing of these groups in the senescence of maize can be linked to the ability to use complex carbohydrates and respond under competition for nutrients. Interestingly, Deinococcus-Thermus was abundantly found in maize rhizosphere as compared with cowpea rhizosphere and it agrees with previous studies that found this phylum in the rhizosphere of maize (Chauhan et al., 2011; Correa-Galeote et al., 2016). Deinococcus comprises a group of bacteria found in several environments and, although this phylum is not well characterized, there is information that they can act as plant growth-promoting bacteria in the rhizosphere (Lai et al., 2006). Specifically, Deinococcus-Thermus was found acting as biological control of soil-borne pathogens in the rhizosphere of cotton (Zhang et al., 2011). It is also worthy to note that the group OP11 presented a significant enrichment only in cowpea senescence. This bacterial group was recently named Microgenomates and proposed to belong to the superphylum Patescibacteria (Rinke et al., 2013). This superphylum has small genomes and a presumed symbiotic or parasitic lifestyle (Sanchez-Osuna et al., 2016). Although Microgenomates is still poorly studied, this group was already found in the rhizosphere of maize, tomato, and soybean (Liang et al., 2014; Correa-Galeote et al., 2016; Sanchez-Osuna et al., 2016). The richness and diversity did not vary between bulk soil and maize rhizosphere, while decreased in cowpea rhizosphere. Usually, bulk soil can present similar, or higher richness and diversity than rhizosphere since plant rhizosphere selects a subset of bacterial groups from the soil, then decreasing the diversity (Weisskopf et al., 2005). Chaudhry et al. (2012) evaluated the microbial diversity in the rhizosphere of switchgrass and jatropha and did not find differences between bulk soil and rhizosphere soils. Comparing plant species, we found a difference in richness and diversity between legumes and grass, a similar result reported by Zhou et al. (2017), which indicated that bacterial community indices associated with legume were different from that associated with grass. When the rhizosphere samples were compared to the bulk soil, we found that 11% of the genera detected in the rhizosphere were not found, in a detectable ratio, in the bulk soil. On the other hand, most of the genera (67%) are shared between bulk soil and rhizosphere. In this sense, the rhizospheric community is a subset of the bulk soil, which is the main source of microbial species colonizing the rhizosphere (Mendes et al., 2014). When compared the rhizosphere groups between the two different plants, we detect a small proportion of genera exclusively present in each plant, reinforcing our observations of differential community assembly according to the plant species. Recent studies have shown that the host genotype, to a minor extent, shapes the root microbiota profiles (Bulgarelli et al., 2012; Pérez-Jaramillo et al., 2017; Mendes et al., 2018a); however, it is still unclear whether microbiome divergence is more significant in host species belonging to different plant families (Abbo et al., 2014). Finally, we used network analysis to understand the microbial community dynamics between bulk soil and rhizosphere and the different developmental stages of the plants. Interestingly, our data revealed that the rhizosphere community in the senescence was more complex than the flowering and bulk soil. Also, in the senescence period, there was an increase in negative correlations. These results suggest a probable competition between microorganisms since that, during the senescence, the rhizosphere activity and root exudation decrease (Miranda et al., 2018). Therefore, these characteristics of rhizosphere during the senescence may contribute to increase the complexity of the bacterial community. According to the network analysis, some keystone species of bacteria were identified in each treatment. In the bulk soil, we found that the genus DA101 was the most important in the network structure. This genus belongs to Verrucomicrobia phylum and was recently described as abundant and ubiquitous in soils, being characterized as an aerobic heterotroph with many putative amino acid and vitamin auxotrophies (Brewer et al., 2016). For rhizosphere of both maize and cowpea, the genus Bacillus was detected as keystone species in the network (specifically for MF, MS and CS treatment). The genus Bacillus has long been considered dominant in the rhizosphere of plants being recognized for their functions in several important biological processes related to plant growth (Mendes et al., 2013) and protection against pathogens (Mendes et al., 2018b). In maize, we also detected the genus Mycobacterium as a key group in the community network. This genus was abundantly found in the rhizosphere of maize and harbors diverse functional genes for nutrient transformation (Li et al., 2014). In cowpea, Microlunatus was detected as key species, and this group is related to phosphorus metabolism in soils (Kawakoshi et al., 2012). Taken together, the co-occurrence network analysis revealed that the dynamics of the communities in the rhizosphere change according to the plant developmental stage, and the key groups are involved in beneficial traits related to plant nutrition and health. 5. Conclusion In this study, the response of the bacterial community was different between bulk and rhizospheric soils, confirming the power of the rhizosphere environment to shape the microbial community. Also, this study showed that the structure and diversity of bacterial community vary significantly according to plant species and, in a minor extent, their developmental stage. Interestingly, the complexity of bacterial community increases during the senescence as compared with the flowering. It confirms that the variation in rhizosphere activity during the plant growth can drive the responses of the bacterial community, which in turn, can influence plant growth and health. Acknowledgments This study was funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq/Brazil (grant 305069/2018-1). The authors thank to the Centro de Genetica e Bioinformatica (CeGenBio) from the Unit of Research (NPDM/UFC). Ademir Sergio Ferreira de Araujo, Vania Maria Maciel Melo, and Marcia do Vale Barreto A.S.F. de Araujo, et al. Applied Soil Ecology 143 (2019) 26–34 32
ASR血ratd Applied Soil Ecology 143 (2019)26-34 Figueiredo thankCNP for their fellowship of research Ethical approval Declaration of competing interest The authors decare that they have. AppendixA.Supplementary dat so References an-O3, k,2010月 rsity and carbo on from a p Cerrado.Antonie Va Y,1 r.0 17.75 TS H KM C M. lomn.MM..2013.Acic nd soll 12011 R. 5E8157-152 crob.Ecol 64.450-46 G.. R..Ru HB.. 19 162 ers in Pla a7106 Offre,P,Ranjard,L Corberand,T.Gamalero,E,Robin,C.Lemanceau, apus).Appl 201 G.W..H P.,Beiko,R.G,20 2012.Microbial degradation o e.M Fertio. oot ph 224 n by rhize ALC. A.M el,E,Maier,U.G.,Br 2832940
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