Polyphasic characterization of rhizobia ...

Polyphasic characterization of rhizobia microsymbionts of common bean [Phaseolus vulgaris (L.)] isolated in Mato Grosso do Sul, a hotspot of Brazilian biodiversity Maira Rejane Costa, Amaral Machaculeha Chibeba, Fábio Martins Mercante & Mariangela Hungria Symbiosis ISSN 0334-5114 Symbiosis DOI 10.1007/s13199-018-0543-6

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Author's personal copy Symbiosis https://doi.org/10.1007/s13199-018-0543-6

Polyphasic characterization of rhizobia microsymbionts of common bean [Phaseolus vulgaris (L.)] isolated in Mato Grosso do Sul, a hotspot of Brazilian biodiversity Maira Rejane Costa 1,2,3 & Amaral Machaculeha Chibeba 4 & Fábio Martins Mercante 2 & Mariangela Hungria 1,3 Received: 4 October 2017 / Accepted: 29 January 2018 # Springer Science+Business Media B.V., part of Springer Nature 2018

Abstract Common bean [Phaseolus vulgaris (Linnaeus)] is the key source of protein, carbohydrates and micronutrients for over 300 million people in the tropics. Like many legumes, P. vulgaris can fix atmospheric nitrogen in symbiosis with rhizobia, alleviating the need for the expensive and polluting N-fertilizers. The crop is known to nodulate with a wide range of rhizobia and, although Brazil is not a center of genetic origin/domestication of P. vulgaris, a variety of rhizobial species have been found as symbionts of the legume. Mato Grosso do Sul (MS) is one of the largest common bean producer states in Brazil, with reports of high yields and abundant natural nodulation. The objective of this study was to evaluate the diversity of 73 indigenous rhizobia isolated from common bean grown in 22 municipalities of MS. Great morphophysiological and genetic diversity was found, as indicated by the six and 35 clusters formed, considering the similarity level of 75 and 70%, respectively, for the phenotypic and rep-PCR dendrograms. Eleven representative isolates were selected for detailed genetic characterization using 16S rRNA and three protein-coding housekeeping genes, glnII, gyrB and recA. We identified species originated from the centers of origin/domestication of the legume, R. etli and R. phaseoli, species probably indigenous of Brazil, R. leucaenae and others of the Rhizobium/Agrobacterium clade, in addition to putative new species. The results highlight the great rhizobial diversity of the region. Keywords Biological nitrogen fixation . Rhizobium . rep–PCR . 16S rRNA . MLSA

Maira Rejane Costa and Amaral Machaculeha Chibeba contributed equally to this study. Fábio Martins Mercante died before publication of this work was completed. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s13199-018-0543-6) contains supplementary material, which is available to authorized users. * Mariangela Hungria [email protected] Maira Rejane Costa [email protected] Amaral Machaculeha Chibeba [email protected] 1

Department of Microbiology, Universidade Estadual de Londrina (UEL), Londrina, PR C.P. 10.011, 86.057-970, Brazil

2

Embrapa Agropecuária Oeste, Dourados, MS C.P. 449, 79.804-970, Brazil

3

Embrapa Soja, Londrina, PR C.P. 231, 86001-970, Brazil

4

International Institute of Tropical Agriculture (IITA), PO Box 709, Nampula, Mozambique

1 Introduction Common bean [Phaseolus vulgaris (L.)] is the most important food legume in human diets. Grown in a wide range of cropping systems and agro-climates, spanning regions as diverse as Latin America, Africa, Canada, China, Europe, Middle East and North America (Schwartz and Corrales 1989), the legume is the key source of protein, carbohydrates and micronutrients for over 300 million people in the tropics (Cavalieri et al. 2011). Brazil is the world’s largest producer of P. vulgaris, with production estimated at 3.4 million tons in 2016/17 (CONAB 2017). In this country, P. vulgaris is the traditional staple food (Rosa et al. 2014), and the main source of protein, primarily for the lower income strata (Schwartz and Corrales 1989). Similar to other legumes, P. vulgaris has the ability to fix atmospheric nitrogen (N2) in symbiosis with soil bacteria generally known as rhizobia (Graham 1981; Hungria and Neves 1987), obviating the need for N-fertilizers (Hungria et al. 2000; Hungria et al. 2003; Mulas et al. 2011), and potentially improving the productivity of the following crops (Peoples

Author's personal copy Costa M.R. et al.

et al. 2009). While P. vulgaris typically forms nodules with a broad range of rhizobia (Mhamdi et al. 2002; MartínezRomero 2003; Ribeiro et al. 2015), under field conditions it often establishes poor N2-fixing symbioses and does not respond to inoculation (Graham 1981; Buttery et al. 1987). The lack of response to inoculation is chiefly ascribed to the competition imposed by inferior N2-fixing or even ineffective indigenous rhizobial strains (Dowling and Broughton 1986; Thies et al. 1991; Vargas et al. 2000). Encouragingly, mounting evidence suggests that the selection among indigenous rhizobia of strains that hold potential for use in inoculants may be rewarding in P. vulgaris cultivation (Hungria et al. 2000; Mostasso et al. 2002; Hungria et al. 2003; Mulas et al. 2011; Rahmani et al. 2011; Mulas et al. 2015). Furthermore, successful effects of inoculation and re-inoculation of P. vulgaris with elite strains in soils with over 103 cells g−1 have been reported (Hungria et al. 2000; Mostasso et al. 2002; Hungria et al. 2003; de Souza and Ferreira 2017). Strain characterization is a key element in bacterial systematics (Fournier et al. 2006; Tindall et al. 2010). Prokaryotes are currently classified based on a polyphasic taxonomy, which consists of comparing phenotypic and genotypic characteristics of a new bacterium with those of previously described type strains (Das et al. 2014; Ribeiro et al. 2015). The phenotypic characterization is based on morphological (cell shape, Gram staining, colony color, size and form), physiological (growth at different temperatures, salt concentrations, pH values and antibiotic tolerance) and biochemical (cell wall composition, relative ratio of fatty acids and polyamines) features (Tindall et al. 2010; Ramasamy et al. 2014). DNA–DNA hybridization (DDH), 16S rRNA gene sequencing analysis, DNA G + C (guanine+cytosine) content, multilocus sequence analyses (MLSA), and average nucleotide identity (ANI) are the most commonly used methods in genotypic characterization of bacteria (Tindall et al. 2010; Sentausa and Fournier 2013; Rashid et al. 2015; Ribeiro et al. 2015). Mato Grosso do Sul (MS) State can be considered as a hotspot for biodiversity. It encompasses three out of the six Brazilian biomes: Mata Atlântica, Cerrado and Pantanal. In addition, it is among nine, out of the 27 states, whose P. vulgaris productivity was beyond 1000 kg ha−1 in the last five years (CONAB 2017). These high productivity regions, particularly the areas with no history of inoculation, represent an important reservoir of indigenous rhizobial strains with potential for use in inoculants, as well as of rhizobial diversity. As a first step for obtaining elite strains for common bean, the objective of this study was to collect and to evaluate the diversity of indigenous rhizobia isolated from soils grown with P. vulgaris from 22 municipalities of MS, Brazil.

2 Material and methods 2.1 Soil sampling, plant growth and isolation of bacteria Twenty soil samples (0–20 cm) were collected from each of 45 different farms located in 22 municipalities of Mato Grosso do Sul (MS) State, Brazil (Table 1, Fig. 1). All fields had no history of rhizobial inoculation and were cropped with common bean. At the laboratory, the 20 soil samples from each farm were spread onto a sturdy plastic bag before being thoroughly mixed and allowed to dry at room temperature for five days. The soil was then sift using a 5-mm mesh screen. After this, 50 g of soil from each field were inoculated into Leonard jars (Hungria et al. 2016) containing a previously sterilized mixture of soil and vermiculite (2:1, v:v). Sterilized Leonard jars were sown with surface-sterilized seeds (Hungria et al. 2016) of Carioca common bean cultivar and grown under controlled greenhouse conditions. At 40 days of growth, healthy-looking nodules were randomly selected from each plant for isolation of rhizobia. Intact nodules were immersed in 70% (v:v) ethylic alcohol for 10 s and then in 10% (v:v) sodium hypoclorite for 4 min before being rinsed six times with sterile water. The bacteria were then isolated and purified as described before (Hungria et al. 2016). Surface-sterilized nodules were crashed individually with a glass rod and the nodule suspension was streaked onto yeast-mannitol agar (YMA) medium (Hungria et al. 2016) modified to contain 5 g L−1 of mannitol and 0.00125% Congo red (w:v). After confirming the purity of each single type of colony, the isolates were maintained on YMA slants at 4 °C for short-term storage and on yeast-mannitol (YM) with 30% (w:v) glycerol for long-term storage at −80 °C and −150 °C, and lyophilized. A total of 73 isolates were obtained.. Koch’s postulates were followed and the nodulation ability of the 73 isolates was confirmed.

2.2 Phenotypic characterization The 73 obtained isolates were sub-cultured in Petri dishes and used for phenotypic characterization based on the following features: a) growth rate [fast (0–4 days), intermediate (5– 6 days) or slow (≥7 days) growers]; b) growth reaction on YMA medium containing bromothymol blue [alkaline (blue), neutral (green) or acid (yellow)]; c) colony shape (oval, circular or irregular); d) colony elevation (flat, raised or convex); e) margin of colony (smooth, undulate or filamentous); f) surface of colony (smooth, rough or dry); g) consistency (friable, mucoid or butyrous); h) opacity (opaque, translucent or iridescent); i) chromogenesis (white, red or purple). A binary matrix was constructed from the most pronounced rhizobium characteristics, and the isolates were clustered based on the UPGMA (Unweighted Pair Group Method with Arithmetic Mean)

Author's personal copy Polyphasic characterization of rhizobia microsymbionts of common bean [Phaseolus vulgaris (L.)] isolated in... Table 1

Locations from where the isolates were sampled

Municipality

Sites

Biomea

Georeference

Climate

Soil

Lat. (S)

Lon. (W)

Alt. (m)

typeb

typec

Isolates

Identification of the isolates

CPAO 1.1F; 6.2F; 5.2F; 3.4F; 2.2F; 5.1F CPAO 7.2F; 7.5F CPAO 11.5F; 13.3F; 10.1F; 11.1F; 13.2F; 13.5F CPAO 17.5F; 16.4F; 21.2F; 21.3F; 16.3F CPAO 26.6F; 26.5F; 22.5F; 22.2F CPAO 2.7F3 CPAO 7.3F3; 14.5F3; 8.1F3; 8.2F3;60.2F3; T6.4F3; 59.3F3; T6.1F3; 100.4F; 68.10F3; 68.11F3; T4.4F3 CPAO 29.10F; 33.4F; 29.2F; 29.5F CPAO 42.4F; 42.3F CPAO 43.3F

1. Amambai 2. Angélica 3. Bataguassu

2 1 2

A A C

23°06′ 22°04′ 21°43′

55°14′ 53°52′ 52°26′

479 342 349

Cfa Cfa Aw

Fa Qf Fo

6 2 6

4. Bataiporã 5. Deodápolis 6. Douradina 7. Dourados

2 2 2 3

A A T T

22°18′ 22°16′ 22°01′ 22°14′

53°16′ 54°10′ 54°35′ 54°50′

328 403 318 422

Am Cfa Cfa Cfa

Fo Fr Fr Fr

5 4 1 12

8. Eldorado 9. Fátima do Sul 10. Glória de Dourados

2 3 1

A A A

23°43′ 22°20′ 22°25′

54°13′ 54°22′ 54°14′

303 330 403

Cfa Cfa Cfa

Fr Fr Fr

4 2 1

11. Iguatemi 12. Itaporã 13. Itaquiraí 14. Ivenha 15. Laguna Caarapã

1 4 3 1 3

A A A A A

23°41′ 22°04′ 23°22′ 22°18′ 22°33′

54°34′ 54°48′ 54°08′ 53°49′ 55°09’

347 362 286 367 502

Cfa Cfa Cfa Cfa Cfa

Fo Fr Fa Fr Fr

1 1 1 1 8

CPAO 48.5F CPAO 27.4F3 CPAO 55.4F CPAO 56.3F CPAO 33.9F3; 34.4F3; 33.3F3; 35.5F3; 35.2F3; 33.12F3; 33.1F3; 33.5F3

16. Maracaju

2

C

21°37′

55°10′

377

Am

Fr

6

17. Mundo Novo 18. Naviraí 19. Nova Andradina

2 1 1

A A A

23°58′ 23°04′ 22°14′

54°17′ 54°12′ 53°21′

264 350 329

Cfa Cfa Cfa

Fo Fa Fa

4 2 1

CPAO 41.1F3; 41.12F3; 39.10F3; 41.9F3; 41.7F3; 39.4F3 CPAO 65.4F; 66.5F; 64.4F; 66.3F CPAO 67.1F; 67.4F CPAO 70.4F

20. Novo Horizonte do Sul 21. Ponta Porã 22. Rio Brilhante Total

2 2 3

A C T

22°40′ 22°31′ 21°48′

53°52′ 55°43′ 54°33′

318 657 316

Cfa Cfa Am

Fa Ao Fr

2 2 1 73

a

A – Atlantic Forest; C – Cerrados; T – transition A-C

b

Climate codes based on Köppen-Geiger climate classification (Alvares et al. 2013)

CPAO 73.4F; 75.5F CPAO 82.1F; 84.1F CPAO 50.9F3

Soil type: Fa – Acric ferralsols; Qf – Ferralic arenosol; Fo – Orthic ferralsols; Fr – Rhodic ferralsols; Ao – Orthic acrisols, based on FAO soil classification (FAO 2016) c

algorithm (Sneath and Sokal 1973) and the Jaccard coefficient (Jaccard 1912), using the software Bionumerics® 7.5 (Applied Mathematics, Sint-Martens-Latem, Belgium).

2.3 Genotypic characterization 2.3.1 DNA extraction and rep-PCR fingerprinting Genomic DNAs of the 73 isolates were extracted with Axyprep Bacterial Genomic DNA Miniprep kit (Axygen®, USA). DNA quality was verified through electrophoreses at 60 V for 30 min, in gels of 1% (w:v) agarose and TEB (TrisEDTA-Borate) buffer subsequently stained with ethidium

bromide and visualized under ultra-violet (UV) light using a Konica digital camera (Kodak®, China). For the rep-PCR analysis, the DNA of each of the 73 isolates was amplified with the BOX-A1R primer (Invitrogen® Life Technologies®, Brazil) (Versalovic et al. 1994) using the procedures described elsewhere (Kaschuk et al. 2006). The PCR reactions were performed on an Eppendorf® Mastercycler Gradient (Hamburg, Germany). Amplified fragments were separated through electrophoreses at 120 V for 7 h, in gels of 1.5% (w:v) agarose. A molecular markers (1 kb Plus DNA Ladder,Invitrogen®) was placed at both ends and in the middle of each gel. The gels were stained with ethidium bromide and were visualized and photographed under UV light using a digital camera. The fingerprinting


Legends Brazilian Cerrado Atlantic Forest Pantanal Fig. 1 Localization of the sites of origin of the common bean rhizobial isolates obtained in this study

Author's personal copy Polyphasic characterization of rhizobia microsymbionts of common bean [Phaseolus vulgaris (L.)] isolated in...

products were clustered considering a level of similarity of 70% (Kaschuk et al. 2006) in the cluster analysis with the UPGMA algorithm (Sneath and Sokal 1973) and the Jaccard coefficient (Jaccard 1912) with 1.0% tolerance and 0.4% optimization. The software Bionumerics® 7.5 (Applied Mathematics, Sint-Martens-Latem, Belgium) was used to perform the analysis. 2.3.2 Amplification and sequencing of the 16S rRNA and housekeeping (glnII, gyrB and recA) genes Based on the analysis of the dendrogram built with the repPCR fragments, 35 isolates were selected for amplification and sequencing of the 16S rRNA and housekeeping genes. The primers and PCR conditions under which the DNAs were amplified are indicated in Supplementary Table S1. The amplified products were purified with PureLink® Quick PCR Purification Kit (Invitrogen®, Life Technologies®, Germany). The concentration of the samples was verified by electrophoresis on 1% (w:v) agarose gels at 60 V for 30 min, adjusted to 40 ng DNA μL−1, and stored at −20 °C until

further analysis. Sequencing was performed on a 3500XL Genetic Analyzer (Hitachi®, Applied Biosystems®, USA) and the obtained gene sequences were deposited in the GenBank under the accession numbers indicated in Supplementary Table S2. For the analyses of the sequences, pairwise and multiple-sequence alignments were performed with CLUSTAL W (Larkin et al. 2007). The best model of sequence evolution was determined with Modeltest (Posada and Crandall 1998) based on the lowest Bayesian Information Criterion (BIC) score (Schwarz 1978). Eighteen out of the 35 representative isolates whose sequences had at least 1000 bp were selected for the 16S rRNA analysis. For the analysis of protein-coding housekeeping genes, one or more representative isolates were selected from each of the five clusters formed in the previous analysis. In clusters a, c and d the isolates whose percentage of nucleotide identity was lower than 100, based on the sequences of the 16S rRNA gene (Table 2), were selected for the MLSA. In cluster e, because all the isolates were identical, two representatives were randomly selected. In total, 11 isolates were selected for the MLSA. Tree reconstruction was performed by

Table 2 Similarity (% nucleotide identity) among 11 rhizobial isolates from Mato Grosso do Sul and between the 11 isolates and the closest type strains based on 16S rRNA, glnII, gyrB and recA gene sequences Pair-wise comparison

16S rRNA

glnII

gyrB

recA

Concatenated

CPAO T4.4F3 CPAO T4.4F3 CPAO T4.4F3 CPAO 41.7F3 CPAO 41.7F3 CPAO 68.11F3 CPAO T4.4F3 CPAO 41.7F3

CPAO 41.7F3 CPAO 67.1F CPAO 68.11F3 CPAO 67.1F CPAO 68.11F3 CPAO 67.1F R. phaseoli ATCC 14482T R. phaseoli ATCC 14482T

99.7 99.7 99.7 100.0 100.0 100.0 99.7 100.0

97.3 97.3 97.3 100.0 100.0 100.0 98.9 98.3

97.4 97.4 97.4 100.0 100.0 100.0 97.6 98.9

99.2 99.2 99.2 100.0 100.0 100.0 98.5 99.2

97.8 97.8 97.8 100.0 100.0 100.0 98.2 98.8

CPAO 67.1F CPAO 68.11F3 CPAO 5.1F CPAO 5.1F R. leucaenae USDA 9039T CPAO 11.5F CPAO 11.5F CPAO 26.6F CPAO 33.12F3 CPAO 33.12F3 CPAO 34.4F3 CPAO 33.5F3 CPAO 33.5F3 CPAO 33.5F3 CPAO 68.10F3 CPAO 68.10F3 Agrobacterium fabrum C58T

R. phaseoli ATCC 14482T R. phaseoli ATCC 14482T R. leucaenae USDA 9039T R. leucaenae CFN 299FT R. leucaenae CFN 299FT CPAO 26.6F R. etli CFN42T R. etli CFN42T CPAO 34.4F3 R. skierniewicense Ch11T R. skierniewicense Ch11T CPAO 68.10F3 Agrobacterium fabrum C58T R. pusense NRCPB10T Agrobacterium fabrum C58T R. pusense NRCPB10T R. pusense NRCPB10T

100.0 100.0 100.0 99.7 99.7 99.6 99.6 99.5 98.5 97.6 99.0 100.0 100.0 99.8 100.0 99.8 99.8

98.3 98.3 100.0 100.0 100.0 95.9 94.9 97.3 100.0 95.9 95.9 98.3 – −99.6 – −98.6 –

98.9 98.9 – 100.0 – 96.8 96.2 97.6 100.0 79.2 79.2 99.1 87.6 98.5 87.6 98.5 86.5

99.2 99.2 100.0 100.0 100.0 95.1 96.2 96.2 100.0 85.0 85.0 99.6 92.1 100.0 91.7 99.6 92.1

98.8 98.8 – 100.0 – 96.1 95.8 97.2 100.0 85.5 85.5 99.0 – 99.2 – 98.8 –

16S rRNA (994 bp), glnII (307 bp), gyrB (495 bp), recA (273 bp)


maximum likelihood statistical method (Felsenstein 1981) and the branching support was evaluated with 1000 bootstraps (Felsenstein 1985). Pair-wise degree of similarity between nucleotide sequences was established with the software Bioedit® 7.2.5 (Hall 1999). All tree reconstruction analyses were performed with the software package MEGA® (Molecular Evolutionary Genetics Analysis) version 6 (Tamura et al. 2013). The GeneBank accession numbers of all employed bacteria are shown in parenthesis in each single-gene tree.

3 Results 3.1 Phenotypic characterization The dendrogram analysis considering all phenotypic characteristics of the 73 obtained isolates identified six clusters at a similarity level of 75% (Fig. 2). Eight isolates (CPAO T6.4F3, CPAO 66.5F, CPAO 42.3F, CPAO 2.2F, CPAO 1.1F, CPAO 66.3F, CPAO 39.4F3 and CPAO 27.4F3) were not grouped in any of the clusters. Cluster 2 had the highest number of isolates, 24 (33%), followed by clusters 4 and 1, with 16 (22%) and 12 (16%), respectively. Clusters 2, 4 and 1 were also the most widely distributed across the sampling sites, being present in 12 (55%), 11 (50%) and nine (41%) municipalities, respectively (Table 1, Fig. 2). All isolates exhibited fast growth rate (3 days), and had smooth margins and surface of colonies. Chromogenesis in YMA with Congo red and optical characteristics were the most variable phenotypic characters even among isolates of the same clusters (Supplementary Table S3). Isolates abundantly produced exopolysaccharides.

3.2 Genetic characterization 3.2.1 rep-PCR fingerprinting In the analysis of the BOX-A1R PCR products of the 73 isolates, 35 clusters were identified in the BOX-PCR analysis, at a 70% similarity cutoff (Fig. 3). The majority (80%) of the clusters were small-sized with one or two isolates. The largest cluster (7) had eight isolates, followed by cluster 19, with seven isolates, and clusters 4, 10 and 14, with five isolates. Most isolates had a broad geographic distribution. Thirteen (81%) out of the 16 clusters with two or more isolates were composed of at least 80% of isolates from different municipalities (Table 1, Fig. 3). Some clusters were composed of isolates sampled over 100 km apart, in different climate and soil types. That was the case of clusters 1 (with isolates sampled at Deodópolis and Novo Mundo), 4 (Botaguassu and Dourados), 7 (Eldorado and Maracaju), 13 (Nova Andradina and Novo Mundo) and 19 (Botaguassu and Dourados) (Table 1, Fig. 3).

3.2.2 16S rRNA gene analysis The 16S rRNA gene-based phylogeny grouped the isolates into five clusters (Fig. 4). Three pairs of isolates, CPAO 17.5F–CPAO 11.5F, CPAO 41.7F3–CPAO 70.4F, and CPAO 68.10F3–CPAO 33.9F3, were tightly clustered in both the BOX-PCR dendrogram (Fig. 3) and the 16S rRNA gene sequence phylogeny (Fig. 4), revealing that they are members of the same clone or clonal complex. However, large discrepancies were also observed between the two analyses. Isolates CPAO T4.4F3, CPAO 5.2F, CPAO 67.1F, CPAO 68.11F3 and CPAO 70.4F were tightly clustered in the 16S rRNA gene sequence phylogeny (Fig. 4), but were positioned far apart in the BOX-PCR based dendrogram (Fig. 3). Similarly, the isolates pairs CPAO 33.12F3–CPAO 34.4F3 and CPAO 81.4F–CPAO 68.10F3 were closely clustered in the 16S rRNA gene sequence phylogeny, but were far apart in the BOX-PCR based dendrogram (Figs. 3 and 4), indicating that they are distinct strains. 3.2.3 Protein-coding housekeeping gene analyses From the 18 analyzed isolates for the 16S rRNA gene (Fig. 4), maximum-likelihood gene trees were inferred, as well as for the concatenated matrix. The phylogeny of the three concatenated housekeeping genes revealed the division of the 11 selected rhizobial isolates into five clusters, with high (99–100%) bootstrap support (Fig. 5). Strong congruencies among single-locus (Supplementary Figs. S1, S2 and S3), concatenated (Fig. 5), and 16S rRNA (Fig. 4) gene sequences phylogenies were observed. Isolates CPAO T4.4F3, CPAO 41.7F3, CPAO 67.1F and CPAO 68.11F3 clustered tightly together with strain R. phaseoli ATCC 14482T, with 99.7–100%, 98.3–98.9%, 97.6–98.9%, 98.5–99.2% and 98.2–98.8% gene-sequence similarities, respectively, for the 16S rRNA, glnII, gyrB, recA and concatenated genes (Table 2). Isolate CPAO 5.1F shared 100% genesequence similarity with R. leucaenae CFN 299T (Table 2), with 99–100% bootstrap support, for the single-locus (Supplementary Figs. S1, S2 and S3), and concatenated (Fig. 5) genes. In cluster c (Fig. 5; Supplementary Figs. S1, S2 and S3), isolate CPAO 26.6F shared over 97% gene-sequence similarity with R. etli CFN 42T for the concatenated genes (Table 2). Isolate CPAO 11.5F shared less than 97% gene-sequence similarity with CPAO 26.6F for the concatenated genes. Further, isolate CPAO11.5F shared less than 97% gene-sequence similarity with R. etli CFN 42T, the closest type strain, for the concatenated genes. In cluster d (Fig. 5), isolates CPAO33.12F3 and CPAO34.4F3 clustered tightly (99– 100% bootstrap support) for the three single-loci (glnII, gyrB and recA) (Supplementary Figs. S1, S2 and S3), and concatenated (Fig. 5) genes, and shared less than 97% sequence similarity with R. skierniewicense Ch11T (Table 2), the closest type strain. In cluster e (Fig. 5), isolates CPAO33.5F3 and CPAO68.10F3 shared 98.3–100% gene sequence similarity for the three

Author's personal copy Polyphasic characterization of rhizobia microsymbionts of common bean [Phaseolus vulgaris (L.)] isolated in... Isolates | Clusters 100

90

80

70

60

50

Level of similarity (%)

.CPAO 42.4F .CPAO 33.1F3 .CPAO 29.10F .CPAO 6.2F .CPAO 5.2F .CPAO 60.2F3 .CPAO 73.4F .CPAO 11.1F .CPAO 21.3F .CPAO 14.5F3 .CPAO 29.5 .CPAO 22.2F .CPAO 41.12F3 .CPAO 33.12F3 .CPAO 21.2F .CPAO 10.1F .CPAO 59.3F3 .CPAO 41.7F3 .CPAO 22.5F .CPAO 7.5F .CPAO 68.11F3 .CPAO 41.1F3 .CPAO 41.9F3 .CPAO 33.3F3 .CPAO 70.4F .CPAO 43.3F .CPAO 55.4F .CPAO 3.4F .CPAO 8.2F3 .CPAO 11.5F .CPAO 26.5F .CPAO 5.1F .CPAO 17.5F .CPAO 35.2F3 .CPAO 65.4F .CPAO 13.3F .CPAO 33.5F3 .CPAO 13.5 .CPAO 50.9F3 .CPAO 8.1F3 .CPAO 39.10F3 .CPAO 68.10F3 .CPAO 33.9F3 .CPAO 7.2F .CPAO T6.4F3 .CPAO 66.5F .CPAO T6.1F3 .CPAO 13.2F .CPAO 16.4F .CPAO 67.1F .CPAO 75.5F .CPAO 33.4F .CPAO 100.4F .CPAO 64.4F .CPAO 26.6F .CPAO 67.4F .CPAO 7.3F3 .CPAO 34.4F3 .CPAO 84.1F .CPAO 2.7F3 .CPAO 82.1F .CPAO 35.5F3 .CPAO 42.3F .CPAO 2.2F .CPAO 48.5F .CPAO T4.4F3 .CPAO 29.2 .CPAO 1.1F .CPAO 66.3F .CPAO 39.4F3 .CPAO 16.3F .CPAO 56.3F .CPAO 27.4F3

1

2

3

4

5

6

Fig. 2 Phenotypic dendrogram of 73 common bean rhizobial isolates from Mato Grosso do Sul, Brazil, constructed using the most pronounced morphological characteristics based on the UPGMA algorithm. The clusters were obtained considering the similarity level of 75%

single-locus and concatenated genes (Table 2). Both isolates shared at least 98.5% gene-sequence similarity with R. pusense NRCPB10T for the single-locus and concatenated genes. Genetic and phenotypic properties were often not congruent. Isolates CPAO T4.4F3, CPAO 41.7F3 and CPAO 67.1F were in the same cluster in the phylogenies based on the 16S rRNA (Fig. 4) and protein-coding gene sequences (Fig. 5, Supplementary Figs. S1, S2 and S3), but were in three

different clusters in the dendrogram based on phenotypic characterization (Fig. 1). Likewise, the isolate pairs CPAO 11.5F– CPAO 26.6F and CPAO 33.12F3–CPAO 34.4F3 were clustered together in most phylogenies (Figs. 4 and 5, Supplementary Figs, S1, S2 and S3), but were assigned to different clusters in the phenotypic based dendrogram (Fig. 1). However, the isolate pairs CPAO 41.7F3–CPAO 68.11F3 and CPAO 33.5F3–CPAO 68.10F3 (Fig. 4, Supplementary


100

90

Isolates | Clusters 80

70

60

50

Level of similarity (%)

CPAO 26.6F CPAO 65.4F CPAO 43.3F CPAO 17.5F CPAO 60.2F3 CPAO 11.5F CPAO 13.3F CPAO 16.4F CPAO 67.1F CPAO 42.4F CPAO 29.10F CPAO 21.2F CPAO 10.1F CPAO 26.5F CPAO 33.4F CPAO 73.4F CPAO 14.5F3 CPAO 41.12F3 CPAO 34.4F3 CPAO T6.4F3 CPAO 82.1F CPAO 33.3F3 CPAO 81.4F CPAO 67.4F CPAO 39.10F3 CPAO 55.4F CPAO 1.1F CPAO 50.9F3 CPAO 66.5F CPAO 41.9F3 CPAO 59.3F3 CPAO 41.7F3 CPAO 42.3F CPAO 70.4F CPAO 64.4F CPAO T6.1F3 CPAO 7.2F CPAO 22.5F CPAO 6.2F CPAO 48.5F CPAO 2.7F3 CPAO 35.5F3 CPAO 35.2F3 CPAO 33.12F3 CPAO 33.1F3 CPAO 5.2F CPAO 8.1F3 CPAO 22.2F CPAO 7.5F CPAO 11.1F CPAO 13.2F CPAO 21.3F CPAO 3.4F CPAO 100.4F CPAO 8.2F3 CPAO 16.3F CPAO 27.4F3 CPAO T4.4F3 CPAO 5.1F CPAO 29.2F CPAO 29.5F CPAO 13.5F CPAO 66.3F CPAO 75.5F CPAO 39.4F3 CPAO 33.5F3 CPAO 56.3F CPAO 2.2F3 CPAO 68.11F3 CPAO 68.10F3 CPAO 33.9F3 CPAO 41.1F3 CPAO 7.3F3

1 2 3

4

5 6

7

8 9

10

11 12 13

14

15 16 17 18

19

20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

Fig. 3 Cluster analysis based on the UPGMA method and the Jaccard coefficient of the products obtained by BOX-PCR analysis of 73 common bean rhizobial isolates from soils of Mato Grosso do Sul, Brazil. The 35 clusters were obtained considering the similarity level of 70%


Figs. S1, S2 and S3) were clustered similarly in both the genotypic and phenotypic analysis (Fig. 1).

4 Discussion The diversity of 73 indigenous bacteria isolated from common bean nodules after inoculation with soils of 22 municipalities of Mato Grosso do Sul was studied by a polyphasic approach. In addition to confirm the ability of nodulating and fixing N2 with common bean, all isolates exhibited Rhizobium–like features, such as fast growth rate, white and glistening colonies with smooth margins (Somasegaran and Hoben 1994). Additionally, all isolates showed either acid or neutral reaction in YMA medium, which is the typical characteristic of fast-growing rhizobia (Khokhar et al. 2001; Sankhla et al. 2015), suggesting that rapid-growing rhizobial populations are the main microsymbionts of common bean in the sampled areas. Moreover, the observed morphophysiological characteristics are consistent with the genera Agrobacterium/Rhizobium (Young et al. 2003), known to exhibit rapid growth rates (Somasegaran and Hoben 1994; Hungria et al. 2016). In the genetic analyses, considerable discrepancies were observed between the dendrogram based on BOX-PCR fingerprinting (Fig. 3), and the phylogenies based on the 16S rRNA (Fig. 4) and protein-coding gene sequences (Fig. 5). This is consistent with previous observations that in the BOX-PCR analyses isolates belonging to the same species may be assigned to different clusters (Hungria et al. 2006; Menna et al. 2009; Chibeba et al. 2017). Nevertheless, the robustness of BOX-PCR for detecting diversity among isolates is unquestionable (Menna et al. 2009; Chibeba et al. 2017). In this study, enormous genetic diversity was detected, as indicated by the numerous (35) BOX-PCR clusters formed, and the high diversity was further confirmed by the final similarity level of only 40%. The great level of morphophysiological and genetic diversity found in this study corroborates earlier reports on rhizobia sampled in common bean nodules in Brazil (Mostasso et al. 2002; Kaschuk et al. 2006), and substantiates the promiscuity of the legume (Mhamdi et al. 2002; Martínez-Romero 2003). The BOX-PCR analysis showed that some clusters were composed of isolates sampled at sites located over 100 km apart, in some cases under different climate and soil types (Table 1, and Fig. 3). High diversity of common bean strains detected by rep-PCR has been recorded in Brazil (Kaschuk et al. 2006; Stocco et al. 2008), and are believed to reflect wider environmental adaptation and superior competitive abilities (Yan et al. 2016).

The MLSA analysis has been successfully used for phylogenetic analysis and taxonomic classification of Rhizobium, preferentially with five or more genes (Martens et al. 2008; Ribeiro et al. 2009; Aujoulat et al. 2011). More recently, however, identification of Rhizobium species has been achieved with only three genes (glnII, gyrB and recA) (Ribeiro et al. 2015; Ormeño-Orrillo et al. 2016), and the similarity level of 97% for the concatenated genes has been suggested as the threshold that circumscribes species (Ribeiro et al. 2013; Cao et al. 2014). In our study, four isolates, CPAO T4.4F3, CPAO 41.7F3, CPAO 67.1F and CPAO 68.11F3, were identified as members of R. phaseoli based on the similarity level greater than 97% in the three single-locus and concatenated genes phylogenies. Likewise, isolate CPAO 5.1F clustered tightly with R. leucaenae CFN 299T in all housekeeping genes phylogenies with the maximum similarity level and was therefore identified as this species. Despite forming a considerably strong cluster in the gyrB and recA gene trees, isolates CPAO 11.5F and CPAO 26.6F shared only 96.1% sequence similarity of the concatenated genes, and were considered as distinct species. In support to this observation, isolate CPAO 11.5F was distantly related to R. etli CFN 42T (95.8% similarity of concatenated gene sequences), and was considered a different lineage, while CPAO 26.6F was closely related to R. etli CFN 42T (97.2% similarity in concatenated genes), and was considered as member of this species. Isolates CPAO 33.12F3 and CPAO 34.4F3 shared 100% similarity of concatenated gene sequences, but were distantly related to known species, suggesting that they might represent a novel species. On the other hand, CPAO 33.5F3 and CPAO 68.10F3 shared close genetic relatedness to R. pusense NRCPB10T based on all the singlelocus and concatenated phylogenies, suggesting to be members of this species. It is also worth mentioning that we had isolates from soils of the biomes of Atlantic Forest, Cerrados, and of the transition zone between both biomes, but diversity was not specifically related to any biome, e.g. R. phaseoli isolates were present in all areas. Common bean is native to the Americas, with two major centers of origin/domestication, the Mesoamerican and the Andean (Gepts 1990; Bitocchi et al. 2013). Wild common beans are not found in Brazil, but the legume has been long cultivated in the country, with strong evidences of centuries of seed trade and migration among Mesoamerican, Andean and Brazilian Indian populations (Grange et al. 2007). Several rhizobial species, including both alpha- and beta-rhizobia are described as symbionts of common bean, and all of them (except for R. gallicum) have been found in Brazilian soils (Martínez-Romero et al. 1991; Hungria et al. 2000; Andrade et al. 2002; Mostasso et al. 2002; Grange and Hungria 2004; Grange et al. 2007; Pinto et al. 2007; Stocco et al. 2008; Ribeiro et al. 2009; Ribeiro et al. 2012; Dall’Agnol et al. 2013; Ribeiro et al. 2013; Dall’Agnol et al. 2014; Ribeiro et al. 2015;

Author's personal copy Costa M.R. et al. Rhizobium phaseoli ATCC 14482T (EF141340.1) Rhizobium pisi DSM 30132T (AY509899.1) Rhizobium leguminosarum USDA 2370T (U29386.1) Rhizobium laguerreae FB206T (JN558651.2) Rhizobium fabae CCBAU 33202T (NR 115872.1) Rhizobium ecuadorense CNPSo 671T (JN129381.1) Rhizobium anhuiense CCBAU 23252T (KF111868.2) 79 Rhizobium acidisoli FH13T (KJ921033.1) a CPAO T4.4F3 (KY971006) CPAO 70.4F (KY971008) CPAO 68.11F3 (KY9710018) CPAO 67.1F (KY9710013) CPAO 5.2F ( KY971003) CPAO 41.7F3 (KY971011) CPAO 3.4F (KY971004) Rhizobium sophorae CCBAU 03386T (KJ831229.2) CPAO 5.1F (KY971007) 84 b Rhizobium leucaenae USDA 9039T (X67234.2) Rhizobium leucaenae CFN 299T (NR 116335.1) 78 Rhizobium multihospitium CCBAU 83401T (EF035074.2) Rhizobium freirei PRF 81 CNPSO 122T (EU488742.2) Rhizobium tropici CIAT 899T (U89832.1) 99 Rhizobium hainanense I66T (U71078.2) Rhizobium lusitanum P1-7T (AY738130.2) Rhizobium rhizogenes ATCC 11325T (AY945955) Rhizobium jaguaris CCGE525T (JX855169.1) Rhizobium paranaense PRF 35T (EU488753.1) 90 Rhizobium vallis CCBAU 65647T (FJ839677.1) CPAO 26.6F (KY9710016) Rhizobium etli CFN 42T (U28916.1) Rhizobium lentis BLR27T (JN648905.2) Rhizobium sophoriradicis CCBAU 03470T (KJ831225.2) c CPAO 11.5F (KY9710014) CPAO 17.5F (KY9710012) Rhizobium bangladeshense BLR175T (JN648931.2) Rhizobium binae BLR195T (JN648932.2) Rhizobium mesoamericanum CCGE 501T (JF424606.1) Rhizobium altiplani BR 10423T (KX022634.1) Rhizobium grahamii CCGE 502T (JF424608.1) Rhizobium tibeticum CCBAU 85039T (EU256404.1) Rhizobium mesosinicum CCBAU 25010T (DQ100063.1) Rhizobium gallicum R602spT (U86343.1) Rhizobium flavum YW14T (KC904963.1) Rhizobium pakistanense BN-19T (AB854065.3) Rhizobium oryzae ALT 505T (EU056823.1) Rhizobium pseudoryzae J3-A127T (DQ454123.3) Rhizobium paknamense L6-8T (AB733647.1) 99 Rhizobium giardinii H152T (U86344.1) Rhizobium herbae CCBAU 83011T (GU565534.1) Rhizobium alvei TNR-22T (HE649224.1) Rhizobium vitis K309T (NR 036780.1) Rhizobium selenitireducens B1T (EF440185.1) 72 Rhizobium radiobacter ATCC 19358T (AJ389904.1) Rhizobium skierniewicense Ch11T (HQ823551.1) 81 Rhizobium nepotum 39/7T (FR870231.1) CPAO 33.12F3 (KY9710010) d 87 CPAO 34.4F3 (KY971002) Rhizobium larrymoorei 3-10T (Z30542.1) Agrobacterium fabrum C58T (NR 074266.1) CPAO 33.5F3 (KY9710015) 75 CPAO 33.9F3 (KY9710017) e CPAO 68.10F3 (KY971009) 98 CPAO 8.2F3(KY971001) CPAO 81.4F (KY971005) Rhizobium pusense NRCPB10T (FJ969841.2) T Rhizobium borbori DN316 (EF125187.1) Rhizobium soli DS-42T (EF363715.1) Rhizobium galegae ATCC 43677T (D11343.1) 88 Rhizobium vignae CCBAU 05176T (GU128881.1) Rhizobium alkalisoli CCBAU 01393T (EU074168.1) Rhizobium yantingense H66T (KC934840.3) Bradyrhizobium diazofficiences USDA 110T (NC 004463.1) 0.01


Fig. 4

Phylogenetic tree based on the 16S rRNA gene sequences (994 bp) of 18 rhizobial isolates from soils of Mato Grosso do Sul, Brazil (in bold), and type strains (T). The tree was reconstructed by the maximum-likelihood method using the best model of sequence evolution and the robustness of branching was estimated with 1000 bootstraps. Only confidence levels ≥70% are shown at the internodes. The scale bar indicates 1 substitution per 100-nucleotide positions; a–e represent the five clusters formed with the 18 isolates

Cordeiro et al. 2017; Dall'Agnol et al. 2017). Particularly interesting, are the R. tropici and R. leucaenae strains very effective in fixing N2 isolated from soils of Mato Grosso do Sul State (Pinto et al. 2007; Mercante et al. 2017), and in the next step, some of the isolates identified in our study will be evaluated for their efficiency in fixing N 2 . Interestingly, we identified isolates classified in the clade of Rhizobium/Agrobacterium, in which R. pusense (species isolated from the rhizosphere of chickpea―Cicer arietinum L.―but not reported as able to nodulate this legume, Panday et al. 2011) is included, in agreement

with previous reports of symbionts of common bean in Brazil (Grange and Hungria 2004; Ribeiro et al. 2013). These strains may represent an interesting link between the evolution from symbiosis to pathogenicity, or viceversa. The remarkable diversity reported in our study, and the detection of rhizobial species originated from centers of origin/domestication of the legume (R. etli and R. phaseoli) and of species probably indigenous to Brazil (R. leucaenae), indicate the outstanding capacity of adaptation of the microsymbionts in a broad range of edaphoclimatic conditions, and of the host legume to co-evolve with exotic and indigenous rhizobia. This study represents the first step for obtaining elite indigenous strains for common bean from Mato Grosso do Sul. Greenhouse screening experiments for N2 fixation effectiveness followed by field testing of the best performing strains will be conducted to select the best symbionts for use in inoculants for common bean in the region.

100

Rhizobium fabae CCBAU 33202T (EF579935.1) Rhizobium pisi DSM 30132T (JN580715.1) Rhizobium gallicum R602spT (AF529015.1) 73 83 Rhizobium leguminosarum USDA 2370T (AF169586.1) 70 Rhizobium anhuiense CCBAU 23252T (KF111913.1) Rhizobium ecuadorense CNPSo 671T (JN129306.1) Rhizobium sophorae CCBAU 03386T (KJ831241.1) Rhizobium sp. CPAO 11.5F (KY040491) c Rhizobium etli CFN 42T (CP000133.1) 85 99 83 Rhizobium sp. CPAO 26.6F (KY040488) Rhizobium sp. CPAO T4.4F3 (KY040490) Rhizobium phaseoli ATCC 14482T (JN580716.1) 99 a Rhizobium sp. CPAO 68.11F3 (KY040487) 95 Rhizobium sp. CPAO 41.7F3 (KY040489) 99 Rhizobium sp. CPAO 67.1F (KY040486) Rhizobium flavum YW14T (KF931400.1) Rhizobium pseudoryzae J3A127T (HM132108.1) Rhizobium paknamense L68T (AB739027.1) 72 Rhizobium skierniewicense Ch11T (KX131141.1) 100 Rhizobium sp. CPAO 33.12F3 (KY040494) d 74 Rhizobium sp. CPAO 34.4F3 (KY040493) Rhizobium sp. CPAO 68.10F3 (KY040496) 99 e T 100 Rhizobium pusense NRCPB10 (MRDJ01000021.1) 81 Rhizobium sp. CPAO 33.5F3 (KY040495) 100 Rhizobium leucaenae CFN 299FT (EU488777.1) b 100 Rhizobium sp. CPAO 5.1F (KY040492) Rhizobium paranaense PRF 35T (EU488787.1) Rhizobium lusitanum P17T (EF639841.1) 77 Rhizobium freirei PRF 81T (EU488789.1) Rhizobium hainanense CCBAU 57015T (GU726294.1) 76 78 Rhizobium tropici CIAT 899T (EU488791.1) Rhizobium altiplani BR 10423T (KX022654.1) 99 Rhizobium grahamii CCGE 502T (JF424618.1) Rhizobium giardinii H152T (EU488778.1) Bradyrhizobium diazoefficiens USDA 110T (BA000040.2) 0.10

Fig. 5 Phylogenetic tree based on concatenated [glnII (307 bp) + gyrB (495 bp) + recA (273 bp)] gene sequences of 11 rhizobial isolates from soils of Mato Grosso do Sul, Brazil, (in bold) and type strains (T). The tree was reconstructed by the maximum-likelihood method using the best

model of sequence evolution and the robustness of branching was estimated with 1000 bootstraps. Only confidence levels ≥70% are shown at the internodes. The scale bar indicates 1 substitution per 10-nucleotide positions; a–e represent the five clusters formed with the isolates

Author's personal copy Costa M.R. et al. Acknowledgements This study was idealized by Dr. Fabio Martins Mercante (1963-2016), an extraordinary Brazilian scientist who dedicated his career to studies of biological nitrogen fixation with common bean, giving a remarkable contribution to the area, including from the description of new species to the identification of elite strains for the crop. The authors thank the assistance of Renan A. Ribeiro and Jakeline R.M. Delamuta (Embrapa Soja) on the BOX-PCR, 16S rRNA and housekeeping gene analyses and Rubson N.R. Sibaldelli (Embrapa Soja) for confection of Fig. 1. Our research group is supported by the INCT-PlantGrowth Promoting Microorganisms for Agricultural Sustainability and Environmental Responsibility (CNPq 465133/2014-4, Fundação Araucária-STI, CAPES). M.R. Costa acknowledges a PhD fellowship from CAPES-Embrapa (15/2014) and M. Hungria a research fellowship from CNPq (300878/2015-0).

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