Evaluating the Diversity and Composition of Bacterial Communities Associated with Acacia Gerrardii - the Only Existing Native Tree Species in Kuwait Desert

Canadian Journal of Microbiology

Evaluating the diversity and composition of bacterial communities associated with Acacia gerrardii - the only existing native tree species in Kuwait desert

Journal: Canadian Journal of Microbiology

Manuscript ID cjm-2018-0421.R1

Manuscript Type: Article

Date Submitted by the 30-Oct-2018 Author:

Complete List of Authors: Suleiman, Majda; Kuwait Institute for Scientific Research Dixon, Kingsley ; ARC Centre for Mine Site Restoration Commander,Draft Lucy; The University of Western Australia Nevill, Paul; Curtin University Quoreshi, Ali; Kuwait Institute for Scientific Research Bhat, Narayana; Kuwait Institute for Scientific Research Manuvel, Anitha; Kuwait Institute for Scientific Research Sivadasan, Mini; Kuwait Institute for Scientific Research

Bacterial communities, Kuwait Desert, Acacia gerrardii, Molecular Keyword: Identification, PCR-cloning

Is the invited manuscript for consideration in a Special Not applicable (regular submission) Issue? :

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1 Evaluating the diversity and composition of bacterial communities associated with

2 Acacia gerrardii - the only existing native tree species in Kuwait desert

5 Majda K. SuleimanA*, Kingsley DixonB, Lucy CommanderC, Paul NevillD, Ali M. QuoreshiA,

6 Narayana R. BhatA, Anitha J. ManuvelA, Mini T. SivadasanA

8 Desert Agriculture and Ecosystems Program, Environment and Life Sciences Research

9 Center, Kuwait Institute for Scientific Research, P.O. Box 24885, Safat 13109, Kuwait A; 10 Department of Environment and Agriculture,Draft ARC Centre for Mine Site Restoration Curtin 11 University, Bentley, WA, AustraliaB; School of Biological Sciences, The University of

12 Western Australia, 35 Stirling Highway, Crawley WA 6009, AustraliaC; Department of

13 Environment and Agriculture, Curtin University, Bentley, WA, AustraliaD

15 Running headline: Assessment of bacterial community

18 Corresponding author

19 Majda Khalil Suleiman, Desert Agriculture and Ecosystems Program, Environment and Life

20 Sciences Research Center, Kuwait Institute for Scientific Research, P.O. Box 24885, Safat

21 13109, Kuwait. E-mail: [email protected]

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24 Abstract:

25 We investigated the diversity and composition of bacterial communities in rhizospheric and

26 non-rhizospheric bulk soils as well as root nodule bacterial communities of Acacia gerrardii -

27 the only native tree species existing in the Kuwait desert. Community fingerprinting

28 comparisons and 16S rDNA sequence identifications were used for characterization of the

29 bacterial population using specific primers. The bacterial characterization of soil samples

30 revealed four major phyla, namely: Acidobacteria, Bacteroidetes, Firmicutes and

31 Proteobacteria. In-situ (Desert) samples of both rhizospheric and non-rhizospheric bulk soil

32 were dominated by two bacterial phyla; Firmicutes and Bacteroidetes, whereas phylum 33 Betaproteobacteria was present onlyDraft in non-rhizospheric bulk soil. Ex-situ (nursery growing 34 condition) A. gerrardii resulted in restricted bacterial communities dominated by members of

35 a single phylum, Bacteroidetes. Results indicated that the soil organic matter and rhizospheric

36 environments might drive the bacterial community. Despite harsh climatic conditions, data

37 demonstrated that A. gerrardii roots harbor endophytic bacterial populations. Our findings on

38 bacterial community composition and structure have major significance for evaluating how

39 Kuwait’s extreme climatic conditions affect bacterial communities. The baseline data

40 obtained in this study will be useful and assist in formulating strategies in ecological

41 restoration programs including the application of inoculation technologies.

42 Keywords: bacterial communities, Kuwait desert, Acacia gerrardii, molecular identification,

43 PCR-cloning, rhizosphere and non-rhizosphere bulk soils.

46 2

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47 Introduction

48 The genus Acacia is one of the largest genera of leguminous trees and shrubs belonging to

49 the sub-family Mimosoideae. They have a worldwide distribution with ~ 75% of species

50 found only in Australia (Pedley 1986). In Kuwait, Acacia gerrardii is considered the only

51 native tree species existing in the desert ecosystem (Boulos and Al-Dosari 1994). This iconic

52 tree species, Acacia pachyceras O. Schwartz, synonym Acacia gerrardii Benth., subsequently

53 referred to as Acacia gerrardii, commonly known as “Lonely Tree” with high ecological

54 importance is selected for this study. Anthropogenic disturbances and prevailing extreme

55 weather in Kuwait may have contributed towards the disappearance of this keystone species 56 from its habitat. Thus, emphasizesDraft the critical importance of its ecological preservation. 57 Therefore, it is essential to conduct research studies for improving regeneration of this key

58 stone species including understanding on the microbial communities associated with the

59 species. Soil microorganisms are essential components to primary productivity and play vital

60 role in biogeochemical cycles (Yang et al. 2017; Kaiser et al. 2016; van der Heijden et al.

61 2008). Bacterial communities present in soil system may differ in their structure and

62 composition by various biotic and abiotic factors (Kaiser et al. 2016). The bacterial

63 communities present in the rhizosphere influence important ecosystem processes such as

64 carbon cycle and nutrient uptake (Wagg et al. 2014).

65 The rhizosphere can be defined as the area of soil closely adjacent to roots of plants that

66 usually supports higher levels of bacterial activity, retains varied metabolic abilities, and play

67 an essential role in soil fertility (Yang et al. 2017; Marschner et al. 2004). The non-

68 rhizospheric soil, also called the bulk soil, and usually this soil is free of plant roots and not

69 mixed with any rhizosphere soil (Olahan et al. 2016). In general, soil bacteria play essential

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70 role in controlling many soil processes, and are responsible for plant growth, fitness and

71 productivity (Na et al. 2018; van der Heijden 2008). Although many studies have reported

72 that the microbiota community is normally different between rhizosphere and non-rhizosphere

73 bulk soils, no reports are available about the bacterial communities inhabiting the desert soils

74 in Kuwait. In particular, no attempt has been commenced so far to reveal the rhizosphere and

75 root bacterial community structure associated with A. gerrardii, which is considered about to

76 be extinct and the only remaining native tree in Kuwait desert. This unique tree only survives

77 in the Talha area of Sabah Al-Ahmed Natural Reserve in Kuwait (Suleiman et al. 2017).

78 Acacia species have a unique ability to form a symbiotic relationship with root nodule 79 nitrogen fixing bacteria (Rhizobia) Draft where they fix atmospheric nitrogen (Brockwell et al. 80 2005). This symbiotic association is an effective means of N supply to Acacia species (Zahran

81 1999). It is a well-known fact that drought and poor nutritional condition in soils are the main

82 factors limiting the development and existence of plants in desert environments (He et al.

83 2014). Reductions in soil microbial composition and/ or their activities are typically related to

84 land degradation and desertification (Kennedy and Smith 1995; Requena et al. 1996, 2001).

85 To improve growth of Acacias, soil/plant can be inoculated with nitrogen fixing rhizobial

86 bacteria. For instance, growth and development of A. nilotica is improved when the

87 association with nitrogen fixing rhizobial bacteria is established (Sarr et al. 2005a, 2005b). In

88 addition, many reports indicate that rhizobial inoculation could considerably improve the

89 growth and establishment of Australian Acacia in disturbed soils, and in semi-arid and arid

90 environments (Duponnois and Plenchette 2003; Bilgo et al. 2012; Sene et al. 2013). As

91 microbial communities present in the soil system perform a significant role in soil system

92 functioning, evaluation and characterization of soil microbes, rhizobial symbiosis, particularly

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93 in degraded ecosystems become vital. Until today, no reports are available to identify

94 indigenous soil and endophytic bacterial populations associated with root systems of this

95 important species in Kuwait. In this study, we have undertaken an effort to reveal a clear

96 research gap in the current knowledge of bacterial community structure and composition

97 represents in the roots of A. gerrardii and its rhizosphere soils in Kuwait desert.

98 The main objective of this study was to reveal the bacterial diversity and community

99 composition of samples from both the root systems and rhizosphere soils of A. gerrardii

100 under in-situ (desert) and ex-situ (nursery) conditions. We also evaluate the plant growth

101 performance of selected A. gerrardii related to bacterial associations under nursery 102 conditions. Characterization of bacterialDraft populations and functional structures were 103 investigated using advanced DNA-based molecular techniques. In this investigation, we are

104 particularly interested in addressing the following scientific questions: (i) how the diversity

105 and composition of bacterial communities vary between the rhizospheric and non-

106 rhizospheric soils under desert and nursery conditions. (ii) are organic matter and rhizospheric

107 effects drivers of phylogenetic structure of bacterial populations of A. gerrardii? iii) are the

108 seedling growth media and growing conditions of different A. gerrardii shaping bacterial

109 diversity and compassion?

110 Materials and methods

111 Study site and sampling

112 Field sampling

113 The experimental site was located at the Sabah Al-Ahmed Natural Reserve, Kuwait (N

114 29°34.909’, E047°47.734’ around the only surviving single A. gerrardii tree, locally known

115 as the Lonely Tree (LT). Soil samples were collected using soil corer of 3 × 30 cm from 0 to

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116 30 cm depth for rhizospheric soil. Lateral roots were followed through the soil excavation

117 channels created around 80-100 cm distance from the main trunk. Three replicate soil samples

118 were collected, and each replicate was a composite of 3-4 soil samples collected from

119 different points near the roots. The composite soil samples were mixed well by placing in a

120 zip lock plastic bag (LT-RS). Similarly, an additional three replicate soil samples were

121 collected 100 m away from the Lonely Tree at three different points, and served as the non-

122 rhizospheric control bulk soil (LT-CS). The representative soil and root samples (LT-ND)

123 were collected and brought to the laboratory and stored in a refrigerator at 4 ° C until further

124 analysis. Root nodules and few roots were cut into 1-2 cm pieces and stored in 2% cetyl 125 trimethylammonium bromide (CTAB)Draft at -20 °C for subsequent molecular characterization of 126 bacterial community.

127 Nursery sampling

128 Two month old seedlings of native and non-local A. gerrardii were transplanted into one-

129 gallon pots containing a soil mixture of agricultural soil, peat moss, potting soil and perlite (at

130 2:1:1:1 ratio, v/v basis) and is named hereafter as the commercial soil mix. The commercial

131 soil mix is used conventionally in Kuwaiti nurseries for producing large-scale nursery

132 seedlings for the restoration program at a national scale. Therefore, the current study was also

133 intended to investigate bacterial community structures in the commercial soil mix used for

134 growing local and non-local A. gerrardii. Fifteen local and non-local A. gerrardii seedlings

135 each were grown in one-gallon plastic pots in the nursery and arranged in three replicate rows

136 with five plants in each row. Crude commercial soil mix was used as control soil (N-CS) and

137 regarded as non-rhizospheric nursery soil sample. Seedlings were destructively sampled for

138 plant and soil sample collection. Soil from five pots from each replicate row was pooled

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139 together and thoroughly mixed in a plastic bag to form a single composite sample per

140 replicate in both seedling groups. Samples were labelled as N-LTRS and N-SARS for the

141 local (Loney Tree) and non-local (Saudi Arabia) A. gerrardii seedlings, respectively. The root

142 nodule samples collected from the nursery seedlings were labelled as N-LTND and N-SAND

143 for local and non-local A. gerrardii seedlings, respectively. Representative soil, root samples,

144 and root nodules collected were stored for molecular characterization as described for field

145 soil and root samples collection.

146 Soil chemical characteristics

147 All the test soil samples collected for the experiment were analyzed for their chemical 148 composition according to the procedureDraft described in USDA, (1996) and USEPA, (1998). 149 Chemical analysis of irrigation water used for raising nursery plants was also carried out.

150 Molecular characterization of bacterial population from soil samples

151 PCR amplification

152 Isolation of genomic DNA from 250 mg of soil was performed using PowerSoil DNA

153 Isolation kit (MOBIO Laboratories Inc.) according to the manufacturer’s protocol. Three

154 replicate samples were used for all DNA extraction and PCR amplication. Amplification was

155 conducted using the bacterial universal primers 358F (5’-CTACGGGAGGCAGCAG-3’;

156 Muyzer et al. 1993) / 907R (5’-CCGTCAATTCMTTTRAGTTT-3; Lane et al. 1985). The

157 forward primer used for DGGE incorporated a GC clamp (5’-

158 GGCGGGGCGGGGGCACGGGGGG CGCGGCGGGCGGGGCGGGGG-3’) at the 5’ end.

159 This GC-clamp is essential for subsequent DGGE gel processing. The GC-clamp strengthens

160 the melting feature of the amplified fragments (Sheffield et al. 1989).

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161 Polymerase chain amplification (PCR) was carried out in a 25-µL reaction and consisted of

162 1 µL soil DNA, 1 U of Taq (Sigma-Aldrich), 1.5 mM MgCl2 and 0.2 mM dNTP mix. The

163 following thermocycle program was used for amplification: 94 °C for 4 min followed by 30

164 cycles of 94, 54 and 72 °C for 50 s each, and an extension period of 72 °C for 10 min using a

165 MJ Research PTC-225 Peltier Thermal Cycler. It is noteworthy that PCR amplification of soil

166 bacterial DNA with U341F/U758R was attempted, but only 14 out of 18 samples successfully

167 amplified.

168 Denaturing Gradient Gel Electrophoresis (DGGE)

169 Characterization of amplicon’ polymorphisms was conducted utilizing the denaturing 170 gradient gel electrophoresis (DGGE)Draft as explained by Labbé et al. (2007) and Lefrançois et al. 171 (2010). First, 500 ng of PCR products was loaded onto a 40-60% denaturing gradient

172 polyacrylamide gel. Aliquot of PCR products (500 ng/lane) were loaded onto denaturing

173 gradient gel, and DGGE was completed with 1× TAE buffer at 60 °C at a constant voltage of

174 180 V for 4 h. After silver staining the DGGE gels, they were illuminated under UV using a

175 Biorad Gel Documentation System. All samples were loaded in one DGGE gel twice to verify

176 the reproducibility.

177 Bacterial identification and phylogeny

178 The rDNA bands that were easily visualized and clearly separated from others were

179 excised from DGGE gels and incubated immediately overnight at 4 °C in distilled water to

180 elute DNA. 2 µL of eluted DNA was amplified using the PCR conditions described above;

181 however, the forward primer did not possess a GC-clamp at the 5’-end. Two DGGE gels were

182 run with amplicons from parallel amplifications to verify reproducibility of the method. The

183 size of the PCR product was assessed by an agarose gel method, and DNAs were sequenced

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184 using the Sanger method with two 16-capillary genetic analyzers 3130XL (Applied

185 Biosystems). DNA sequences were edited using BioEdit software, version 7.0.5 (Hall 1999)

186 in order to resolve oligonucleotide ambiguities. The BLASTn algorithm (GenBank:

187 http://www.ncbi.nlm.nih.gov/BLAST/) was used to query GenBank (NCBI) for highly similar

188 sequences. Multiple alignments of sequence matrices were processed using ClustalW software

189 (Thompson et al. 1994) implemented in MEGA 6.0 (Tamura et al. 2013). Evolutionary

190 distances were calculated as described by Jukes and Cantor (1969), and evolutionary trees

191 were inferred by the neighbor-joining method (Saitou and Nei 1987). The tree was

192 constructed with the help of Maximum likelihood (ML) method based on the Kimura two- 193 parameter (K2P) distance correlationDraft model, as described by Kimura (1980), and 1,000 194 bootstrap replicates (Felsenstein 1985).

195 Molecular characterization of endophytic bacterial community from roots and nodules

196 Before isolating the genomic DNA, roots and nodules were surface sterilized in six

197 successive baths comprising of 2 min in sterile distilled water, 10 s in 95% ethanol, 2 min in

198 3% sodium hypochlorite, and three consecutive 2 min-long baths in sterile distilled water.

199 DNA extraction was realized on 5-6 nodules per seedling. Tissues were ground in 1.5 ml

200 tubes with micro pestle and liquid nitrogen after which they were bead-grinded with a Tissue

201 Lyser II (Qiagen) in the lysis buffer AP1 of the DNeasy Plant Mini Kit from Qiagen. After the

202 grounding step, 4 µl of RNase A supplied with the kit was added, and the remaining steps of

203 the manufacturer’s protocol were performed. Amplification was performed using the specific

204 primers designed for Rhizobiales order: 63f (5’-AGGCCTAACACATGCAAGTC-3’) and

205 Rhiz-1244r (5’-CTCGCTGCCCACTGTCAC-3’) (Singh et al. 2006; Tom-Petersen et al.

206 2003).

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207 The reaction was carried out in a 25-µL reaction and consisted of 2 µL of total DNA, 1 U

208 of Taq (Sigma-Aldrich), 1.5 mM of MgCl2, 0.2 mM of dNTP mix, 0.5 µM of each primer and

209 BSA at 0.2 mg/ml. The following thermocycle program was used for amplification: 94 °C for

210 4 min followed by 30 cycles of 1 min at 94 °C, 1 min at 55 °C and 2 min at 72 °C, and an

211 extension period of 72 °C for 5 min using a MJ Research PTC-225 Peltier Thermal Cycler.

212 PCR amplicon was migrated in a 1.2% agarose gel stained with ethidium bromide and

213 visualized under UV light.

214 Then 150 ng of amplicons was cloned into a pGEM®-T Easy Vector System II (Promega)

215 following the manufacturer’s protocol and bacteria were stored in TTE buffer (triton X-100 216 1%; Tris-HCl pH 8.0 20 mM; EDTADraft pH 8.0 2 mM) at -20 oC until required. Briefly, PCR 217 products were ligated into a suitable vector, which was transformed into and replicated by E.

218 coli, following the manufacturer's instructions. Finally, 10 clones per sample were sequenced

219 using the Sanger method with two 16-capillary genetic analyzers 3130XL (Applied

220 Biosystems).

221 Numerical analyses

222 Sequences were edited, aligned and queried on GenBank (NCBI) as explained in section

223 bacterial identification and phylogeny. Sequences with at least 97% similarity were

224 considered in the same Operational Taxonomic Units (OTU), which could represent one

225 species (Quince et al. 2008). One representative of each OTU was used to continue

226 phylogenetic analyses. Phylogenetic analyses were conducted using MEGA 6.0 (Tamura et al.

227 2013). Firstly, analyses were performed using the Neighbor-Joining (NJ) method (Saitou and

228 Nei 1987) and adopting the Kimura two-parameter method (Kimura 1980). Secondly,

229 maximum likelihood (ML) method based on the Kimura two-parameter model (Kimura 1980)

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230 was used to compute the final tree. Finally, Bayesian inference of phylogeny was calculated

231 using MrBayes version 3.2.2 (Ronquist et al. 2012), assuming a 4 × 4 model and non-variable

232 substitution rates among sites – gamma rates. Analyses were constructed on two runs of four

233 Markov chain Monte Carlo analyses where 2,000,000 generations were produced with

234 burning fraction at 0.5 rate. These were sampled every 100 generations for 10,000 trees

235 generated (Ronquist et al. 2012). The family and genus groups were determined in line with

236 Kwon et al. (2005); Willems (2006); Degefu et al. (2013); Mousavia et al. (2014).

237 Statistical analyses

238 In order to determine the extent of similarity between DGGE banding profiles, a 239 dendrogram was built using the PhoretixDraft 1D Pro software (Total Lab Limited, Nonlinear 240 Dynamics, Newcastle Upon Tyne, UK) based on the similarity matrix index using Dice’s

241 similarity coefficient method (Dice 1945). The comparison of band patterns was based on

242 band position. Simpson’s (D), Shannon–Wiener (H) and Pielou’s evenness (E) diversity

243 indices were calculated using the following formula:

244 D =1−Σ (pi)2, H = −Σpi log(pi), where pi = proportion of frequency of the ith phylotype in a

245 sample. Phylotype evenness was calculated as E = H/log(S), where H = Shannon Wiener

246 diversity and S = phylotype richness (i.e., total number of phylotypes). Endophytic bacterial

247 community diversities were compared and the specific levels of taxonomic resolution

248 (rarefaction) were determined. Coverage saturation (C) was also calculated in order to verify

249 the sufficiency of the sampling effort, using the expression:

250 C = 1 – (n1/N), where n1 is the number of phylotypes that occurred once, and N is the total

251 number of phylotypes inspected.

252 Results

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253 Soil chemical characteristics

254 The soil chemical properties are shown in Table 1. Soil organic matter measured was very

255 low typically observed in desert soils. However, relatively higher amount of organic matter,

256 carbon, and essential nutrients were detected in rhizospheric soils of Lonely tree (LT-RS)

257 compared to control (LT-CS) soils. Furthermore, higher levels of organic matter, soil carbon,

258 and essential nutrients found with nursery-potting soils when compared to desert soils.

259 Denaturing Gradient Gel Electrophoresis (DGGE) profiling of bacterial 16S rDNA

260 community

261 Two replicates DGGE gels loaded with the same samples to verify the reproducibility of 262 the method were found similar. TheDraft fingerprints showed relatively little variation between 263 different replicates, suggesting good reproducibility of DNA extraction, PCR amplification,

264 and DGGE analysis. Visual inspection of the PCR-DGGE fingerprinting showed

265 distinguishable profiles in which some bands of various intensities were preferentially

266 associated with a specific soil rhizosphere when compared to the bulk soil (Fig. S1). All

267 successfully sequenced bands are indicated with an arrow as shown in supplementary material

268 fig. S1. In contrast, some bands were found common to all samples and represent a well-

269 established group or groups of bacteria.

270 Phylogenetic diversity and rhizospheric effect on soil bacterial communities

271 Sixty-six bacterial sequences were derived from DGGE bands (all data not shown) excised

272 from the full-gradient range of the gels. A phylogenetic tree is shown in figure 1. All the 16S

273 rDNA sequences retrieved from prominent DGGE bands of bacteria were related to four

274 major taxonomic groups, namely Acidobacteria, Bacterioidetes, Firmicutes and Proteobacteria

275 (Table 2). In general, the majority of bacterial 16S rDNA sequences had high sequence

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276 similarity (up to 100%) with environmental clones or known species in the NCBI database.

277 However, there are a few bacterial sequences, which did not reach 90% similarity with the

278 species in the NCBI database.

279 Sequence analysis showed that members of the phylum Bacterioidetes were the dominant

280 group in all soil samples. Sixteen bacterial sequences belonged to this group and showed high

281 similarities to their closest relatives, mostly uncultured bacteria from diverse environments.

282 Firmicutes were the second largest contributor in terms of phylogenetic diversity. Five

283 sequences dominated by the genus Bacillus were affiliated to this phylum. The remaining

284 sequences were clustered with members of the beta sub-group Proteobacteria and 285 Acidobacteria with one and two 16S DraftrDNA sequences, respectively. 286 The degree to which bacterial populations are influenced in the rhizospheres of plants

287 compared to the control bulk soils was analyzed. A differential distribution pattern of the

288 bacterial phyla among the different soil rhizospheres was observed (Table 2). In more detail,

289 the rhizosphere soils (LT-RS) were clearly dominated by members of the Bacteroidetes

290 phylum (62.5% of the community) followed by members of the Firmicutes, which accounted

291 for 37.5%. In contrast, the non-rhizosphere (control bulk soil) samples (LT-CS) showed the

292 higher biodiversity in terms of community structure (Table 2). The Bacteroidetes, Beta

293 Proteobacteria and Firmicutes accounted for up to 34% of the soil bacterial community in LT-

294 CS samples. The N-LTRS soils (grown in optimal nursery conditions) contain members of a

295 single phylum, Bacteroidetes, which increased its abundance in rhizosphere plants (N-LTRS).

296 Interestingly, soil samples N-LTRS and N-SARS treatments shared similar DGGE bands

297 represented and it was observed that DGGE bands in a single gel that appeared to be identical

298 based on mobility did indeed produce more than 97% identical nucleotide sequences. In

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299 contrast, the N-CS bulk soil samples were affiliated to three phyla: Bacteroidetes (57.1%),

300 Acidobacteria (28.6%) and Firmicutes (14.28%).

301 According to cluster analysis as shown in fig. S2, marked differences exist in the bacterial

302 community composition: two main clusters sharing less than 50% of similarity were

303 distinguished. The first cluster included the rhizosphere soils collected from both local and

304 non-local A. gerrardii (N-LTRS and N-SARS treatments) grown in nursery conditions and,

305 the second cluster comprised the Lonely Tree (LT-RS) and bulk soil (LT-CS and N-CS)

306 samples. N-LTRS-2B was replicated in order to verify the reliability of the DGGE method

307 and both replicates were included in the same branch cluster. E. coli was excluded and formed 308 a single cluster. Draft 309 Endophytic bacterial community in the root system

310 Twenty clone libraries were produced from nodule materials (Table 3) on which 3 to 13

311 clones were successfully sequenced per library. Thirty-three OTUs could be identified among

312 all 190 successfully sequenced clones when the 97% criterion was adopted (Table 3). Only

313 five sequences gave the BLAST result with “no significant similarity found.” At least one

314 representative of each OTU was included in the sequence alignment to construct the

315 phylogenetic trees. The definition of OTU was based on pairwise alignment of sequences.

316 Sequences with at least 97% similarity were classified in the same OTU. However,

317 sometimes, members of the same OTU yielded different, yet considerably close, BLAST

318 sequences. Two to three representatives of each BLAST sequence were included in the

319 phylogenetic trees (Figs. 2, 3, 4). Fig. 2 indicates OTUs that showed similarity with

320 Rhizobium, Agrobacterium and Shinella genera, where 14 OTUs are present. On the other

321 hand, Fig. 3 shows Bradyrhizobium, Mesorhizobium and Ensifer (formerly Sinorhizobium)

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322 species; showing 6 OTUs. Finally, Fig. 4 comprises other alpha-proteobacteria, of which 19

323 OTUs are shown.

324 For bacterial composition and frequency in the different communities studied, it can be

325 noted that in LT-ND, the dominant OTUs are OTU-1- closely matched to Rhizobium

326 huautlense, OTU-14 in the Devosia genus (close to Devosia sp. R41and Devosia riboflavin

327 Table 3). However, another OTU-7 close to Rhizobium vallis is also dominant, but is only

328 present in location 1 of the investigated locations. All these species are known to form

329 nodules (Wang et al. 1998; Rivas et al. 2003; Wang et al. 2010). OTU-6 is also dominant and

330 present in two locations, but is not classified in a known group. Dominant OTUs in the N- 331 LTND community are OTU-12 (in Draftthe Agrobacterium group)which can cause plant disease 332 (Martínez et al. 1987), and OTU-11, which is a Rhizobium closely matched to R.

333 subbaronis—an endolithic bacterium isolated from beach sand. It should be noted that as R.

334 subbaronis was closer to Sinorhizobia and Ensifer—2 unknown Rhizobia—they are included

335 in the tree in as shown in Fig. 3. Other OTUs that were dominant in the N-LTND were OTU-

336 9 and OTU-24, along with an unknown Novosphingobium genus that include potential

337 bacteria used in bioremediation (Ramana et al. 2013; Tiirola et al. 2005). All these last

338 dominant OTUs are present in at least two libraries and plants each. OTU-5, (similar to

339 Bartonella elizabethae) a human pathogen, was also found within the N-LTND bacterial

340 community, albeit in plant and one library only. Finally, the dominant OTUs in the N-SAND

341 community were OTU-1 (Rhizobium huautlense), OTU-4 (R. etli), OTU-7 (R. vallis), three

342 potential root-nodulating bacteria and OTU-12 (Agrobacterium sp.), OTU-13

343 (Hyphomicrobium sp.) and OTU-18 a, Sphingomonas sp. While OTU-4 and OTU-18 were

344 found in one plant and library each, OTU-1 was included in two libraries in the same location.

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345 Other OTUs were present in at least two plants and different libraries, respectively (data not

346 shown).

347 Table 4 shows that there is no evidence of drift shift between bacteria composition of the

348 Lonely Tree in nature (LT-ND) or in nursery (N-LTND). Rarefaction index was calculated to

349 verify that with the standardization of the abundance of clones sequenced at 60 individuals for

350 each sample, the same order of magnitude is obtained as that yielded by the calculation of

351 OTU richness (Table 4). In terms of the comparison between OTU compositions in nodule

352 communities, N-LTND and N-SAND share two dominant OTUs (OTU-9 and OTU-12) that

353 are not present in LT-ND nodule communities (Table 3). Interestingly, OTU-7 is present in all 354 plant types (LT, N-LT, and N-SA). DraftFor other OTUs, no trend of similarity between nodule 355 communities could be established. Correspondence analyses (CA) (Fig. 5) is an important tool

356 used by molecular biologist and found in most recent published results. Analyses in this

357 research revealed closer relationships among bacterial communities in nodules of seedlings

358 tested. CA indicated that native LT and non-local SA seedlings promote the same group and

359 diversity of endophytic bacteria in nodules when they grow in the nursery, suggesting

360 apparent influence of growing media characteristics and nursery growing conditions rather

361 than tree species. More specifically, with the exception of one nursery community (N-SAND-

362 1), the Lonely Tree (N-LTND) and the Saudi Arabia tree (N-SAND) exhibit more similar

363 features in comparison with bacterial communities in nodules of the Lonely Tree growing in

364 nature (LT-ND).

365 Discussion

366 Soil bacterial community composition

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367 The soil is considered a very complex ecosystem itself, and the microbes harboring in soil

368 system play a key role in soil functioning. The present work provides us with a glimpse of the

369 bacteria associated with both rhizosphere and non-rhizosphere bulk soils of A. gerrardii from

370 the Sabah Al-Ahmad Natural Reserve of the Kuwait desert. For the overall community

371 composition of analyzed samples, the bacterial phylotypes detected were classified into four

372 major Phyla: Bacterioidetes, Firmicutes, Proteobacteria (subdivision of beta) and

373 Acidobacteria. Previous research supports the assumption that bacterial community structures

374 in desert lands are different according to location, land use types and soil characteristics. For

375 example, in a study on the Tengger desert, Zhang et al. (2012) found that the 16S rRNA gene 376 sequences retrieved from prominent DraftDGGE bands bacteria belonged to subdivisions of alpha, 377 beta, and gamma Protobacteria, which were most dominant group in all depths and

378 rhizosphere soils followed by Cyanobacteria and Acidobacteria. In another study using high-

379 throughput pyrosequencing and quantitative polymerase chain reaction techniques, Wang et

380 al. (2012) reported that soil microbial community structures investigated along the Heihe

381 River basin were dominated by Actinobacteria, Alphaproteobacteria, Bacteroidetes, and

382 Firmicutes, which accounted for 71.4% of the total sequences. Four other phylotypes with

383 very low abundance, such as Acidobacteria, Chloroflexi, Nitrospira,

384 and Gammaproteobacteria were also revealed from the same site. A higher bacterial diversity

385 belonging to 14 bacterial groups was reported in a study from Atacama Desert soil in which

386 Actinobacteria, Firmicutes, Bacteroidetes and Proteobacteria were the most abundant groups

387 (Orlando et al. 2010). Another study from Atacama Desert indicated that the bacterial

388 community was mainly comprised of Actinobacteria, Proteobacteria and Firmicutes (Lester et

389 al. 2007). Many studies have reported that members of the Protobacteria phylum are favorably

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390 represented in desert environment. The reason for only four phyla found in our study

391 compared to other studies elsewhere could be due to the samples we analyzed are only from

392 one restricted area and associated with one unique tree. However, it should be noted that a

393 huge number of bacteria remain unclassified in the current analysis. In our study, we found

394 little less diverse and greater abundance of bacterial communities in the rhzosphere soils

395 compared to bulk soils. This observation correlates with many other previous studies (Dennis

396 et al. 2010; Uroz et al. 2010). The above results and our current study data from the Kuwait

397 desert specify the greater variation prevailed in bacterial composition among different desert

398 lands and soil conditions. In general, desert soil contains very low levels of organic matter, 399 organic carbon as well as essential nutrientsDraft (Thomas et al. 2012). Results of this study on soil 400 chemical properties also showed very low level of organic matter, organic carbon, and

401 essential nutrients compared to nursery potting soil. The data on bacterial community

402 structure and diversity indicate that soil organic matter and rhizospheric effects may play

403 important roles in altering microbial communities. For example, microbial community profile

404 results from the control bulk desert soil showed relatively lower bacterial diversity and

405 composition compared to plants growing on nursery potting soils and A. gerrardii (Lonely

406 Tree) rhizosphere soils. The low level of average OTUs Richness and Shanon-Wiener Index

407 (S) with Lonely Tree control soils revealed that microbial community composition depend on

408 soil types and properties, and the vegetation status. Various organic compounds released by

409 plant roots thought to be one of the major factors influencing the diversity of microorganisms

410 in the rihzosphere. Our results are in agreement with a recent study, which concluded that the

411 abundance and diversity of microbial community in rhizosphere were higher than bulk soil

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412 (Yang et al. 2017). Clearly, the bacterial communities were influenced by proximity to the

413 roots, suggesting a rhizosphere effect (Marschner et al. 2001).

414 We noticed that Bacteroidetes were the most abundant phyla among the entire sample

415 analyzed. Their sufficient distribution in the different soil samples reflects their ability to

416 tolerate and support both nutrient-rich (nursery) and -poor (field) soils, and may suggest that

417 these bacteria play an ecological role in the studied environments. The distribution pattern of

418 Bacteroidetes in studies by Acosta-Martínez et al. (2010) and by Wang et al. (2012) also

419 showed that they were favored in carbon-rich soils (Fierer et al. 2007). Bacteroidetes are also

420 reported to have the ability to rapidly explore organic matter (Acosta-Martínez et al. 2010) 421 and stimulate nutrient cycling (WangDraft et al. 2012). The most abundant phyla Bacteroides 422 observed in both the soil types support the statement that their ability to tolerate both rich and

423 poor soil conditions. However, in this study, soil chemical analysis detected the soil pH of

424 entire sample analyzed ranged between 7.1 and 7.7, which is considered being near neutral to

425 slightly alkaline. The soil pH may be an essential factor in the composition of bacterial

426 community (Lauber et al. 2009; Rousk et al. 2010). Firmicutes were also well distributed in

427 the desert soils as previously suggested by many other studies on arid ecosystems (Andrew et

428 al. 2012; Orlando et al. 2010; Zhang et al. 2012). Firmicutes were reported to be enriched in

429 soils with lower moisture content (Acosta-Martínez et al. 2010), as is the case with this

430 current Kuwaiti soil samples. In addition, endospore formation is common characteristics

431 among Firmicutes. The endospores are specialized resistance structures that allow the survival

432 of microorganisms for extended periods in dry soils (Gao and Gupta 2005), and also give

433 protection against several environment stressors (Griffiths and Philippot 2013).

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434 Acidobacteria were detected in samples from the nursery experiment (bulk nursery soils)

435 but were absent in those from the field site, indicating that Acidobacteria may thrives in ideal

436 soil moisture conditions rich in organic matter, also reported as organic matter decomposer

437 and have the nutrient cycling ability (Van Horn et al. 2013). Following a similar pattern,

438 Acidobacteria were also completely absent from one site at the hyper-arid margin from

439 Atacama Desert and comprised just 0.2 and 0.09% of the two soil communities (Neilson et al.

440 2012). It was absent from eight of the eleven sites evaluated in a cold, shale desert located in

441 Southeast Utah (Direito et al. 2011). In contrast, Acidobacteria represented 17 and 22%,

442 respectively, of the bacterial communities from the hot desert of Tataouine (South Tunisia) 443 and an arid soil from the Atacama DesertDraft (Chanal et al. 2006; Costello et al. 2009). 444 In this study, control bulk desert soil with no vegetation had lower ECe, N, P, K, organic

445 matter, and organic carbon may explain the differences in bacterial populations compared to

446 other studies. Additionally, a large number of bacterial 16S rDNA sequences had high

447 similarities with a wealth of uncultured bacteria from diverse environmental conditions and

448 remain unclassified at the genus level. The use of these organisms in various restoration and

449 remediation strategies is important and requires a separate study.

450 Rhizosphere effect on soil bacterial communities

451 The second objective was to evaluate the rhizosphere effect of local and non-local A.

452 gerrardii on soil bacterial community structures. This was done by assessing bacterial

453 diversity in soils from the same species grown in optimal nursery environments and plant

454 performance under different microbial associations. Furthermore, the study intended to

455 evaluate and compare the rhizospheric microbial communities of these two species (local and

456 non-local A. gerrardii) when raised under nursery conditions. Results from the bacterial

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457 community analyses revealed that rhizospheric soils analyzed from nursery grown both local

458 and non-local species shared a similar phylum, Bacteroidetes. However, non-rhizospheric

459 control nursery potting soils (N-CS) without plants had a greater bacterial diversity including

460 Acidobacteria and Firmicutes. The results of this study show that as plant-induced

461 stimulation, as the root grows in any growing media have the ability to shape in dominance to

462 bacterial community based on several factors such as plant species, growth rates, and release

463 of carbon compounds (Morgan et al. 2005). Furthermore, different root zones on the same

464 plant can support distinct bacterial communities, maybe due to qualitative and quantitative

465 characteristics of root exudation (Yang and Crowley 2000). Phylogenetic analyses of this 466 research addressed the research questionsDraft that the structures of bacterial communities 467 associated with rhizosphere and non-rhizosphere soils are different and have rhizospheric

468 effects but share a phylum in common, Bacteroidetes which has the ability to tolerate both

469 rich and poor soil conditions. The soil chemical properties are considered in shaping

470 microbial communities and reported in many studies (Tian et al. 2017). In this study, chemical

471 properties of rhizospheric and non-rhizospheric commercial soil mix had not shown much

472 difference. However, close to neutral soil pH, relatively lower P concentration and relatively

473 higher K, Ca, and Mg concentration associated with non-rhizospheric control soil might

474 explain for higher abundance of bacterial phyla compared to rhizospheric soils.

475 Nursery-grown plants appear to drastically lower the diversity of bacterial community

476 structures, with rhizosphere soils broadly dominated by members of a single phylum,

477 Bacteroidetes. In contrast, a more diverse bacterial community was found in the bulk soils

478 with members of three phyla namely Bacteroidetes, Acidobacteria and Firmicutes. In contrast,

479 rhizospheric soils when associated with growing root systems, under optimum moisture

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480 conditions, and possible rhizospheric effects might favor to single phylym Bacteroidetes and

481 depressed others. A rhizosphere effect was also noted in our field samples but became more

482 pronounced in the nursery experiment. Plant-dependent enrichment and seasonal shifts were

483 previously reported in works by Smalla et al. (2001) and Kavamura et al. (2013). Other

484 studies have also reported a lack of increase in bacterial diversity with plant cover (Farias et

485 al. 2009; Sene et al. 2013) or plant species richness (Ushio et al. 2013) whereas Lin et al.

486 (2013) found a more diverse bacterial community around tree roots. These analyses and data

487 from this study points out the complexity of the interdependency of bacterial diversity with

488 plant species. 489 Microbial community fingerprintingDraft showed that soil samples that corresponded to the 490 rhizospheres of local and non-local A. gerrardii shared similar DGGE bands. It seems that

491 non-local A. gerrardii also influenced the bacterial communities similarly as local A.

492 gerrardii. We acknowledge that this assumption needs further confirmation, but still some

493 conclusions can be drawn from this observation. Obviously, it can be stated that the bacterial

494 communities were influenced in the surrounding of both A. gerrardii roots, with a stimulatory

495 effect on root plants on the Bacteroidetes group. Besides the local and non-local A. gerrardii

496 tested in this study, other tree species could be considered in further studies in order to

497 identify which species is more appropriate for restoring tree vegetation patches, including

498 conservation of soil bacterial biodiversity. However, it is reasonable to speculate that the

499 differences in rhizosphere bacterial community composition observed between the two test

500 plant species in the nursery and LT-RS may have different root growth habits and may induce

501 different root exudates that may alter soil micro conditions and therefore contribute to

502 observed bacterial community.

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503 Endophytic bacterial community in the root system

504 The current research demonstrated that despite Kuwait’s harsh climate, the studied Lonely

505 Tree roots maintained a diverse endophytic bacterial community (Figs 2, 3, 4). However, the

506 diversity of bacterial community in the nursery-grown A. gerrardii seedlings was even further

507 greater than that in the natural habitat of the Lonely Tree (Fig 2, 3 4). Our study on revealing

508 endophytic bacterial community from A. gerrardii in the desert habitat identified about 13

509 strains from 11 genera. In contrast, about 29 strains from17 genera were identified from

510 nursery grown local and non-local A. gerrardii. Similar observation was reported with native

511 Acacia spp. from Algerian desert region, in which at least 24 representative strains were 512 genetically characterized (BoukhatemDraft et al. 2016). In another study, Hoque et al. (2011) 513 reported about 19 endophytic bacterial genera identified from Acacia stenophylla and Acacia

514 salicina, native to Australia. Our results are similar to the results obtained by these two

515 studies with Acacia species. Overall, our results suggest that the diversity of bacterial

516 communities in the nursery grown seedlings were greater owing to soil chemical richness and

517 substrate, and nursery optimal growing conditions compared to harsh desert environmental

518 conditions (Bardgett et al. 1999). The greatest diversity was noted among nodules that come

519 from seedlings in nursery, indicating that diversity in the natural conditions is lower. The

520 results addressed our research questions that soil substrate status and rhizospheric effects may

521 drive the structure and composition of bacterial populations.

522 In this investigation, the Devosia genus was found only in desert location in LT-ND

523 samples (Table 3). The presence of nitrogen fixing Devosia sp. in root nodules or in desert

524 soils in this study was not rare incident or due to any contamination. The possibility of

525 contamination arising from irrigation waters or the presence of endophytic bacterial species in

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526 nursery growing media for nursery seedlings was addressed further by molecular analysis of

527 irrigation water and nursery growing media. Several studies have isolated Devosia sp. from

528 various sources, such as soil, greenhouse soil, dump site, and root nodules (Kumar et al. 2008;

529 Bautista et al. 2010; Hoque et al. 2011).

530 Although the same three families were observed in the nursery grown local and exotic

531 Acacia species, the diversity of genus was more pronounced in nursery grown Acacia when

532 compared to the Lonely Tree that survives in the desert soil conditions. Correspondence

533 analyses also showed closer relationship among bacterial communities. Correspondence

534 analyses indicated that native LT and non-local SA seedlings promote the same group and 535 diversity of endophytic bacteria inDraft nodules when they grow in the nursery, suggesting 536 apparent influence of growing media characteristics and nursery growing conditions rather

537 than tree species. This is evident that soil conditions influence the endophytic bacterial

538 diversity more than the tree species characteristics. The results of this study in terms of the

539 identified three families were consistent with the results of earlier studies (Boukhatum et al

540 2016; Hoque et al 2011; Rivas et al 2004). Boukhatum et al. 2016 had reported the presence

541 of Ensifer sp. and Rhizobium sp. in native Acacia grown in desert region of Algeria. Similarly,

542 the existence of Devosia genus had also been reported in the roots of Acacia across South-

543 East Australia (Hoque et al 2011). Spingomonas, Inquilinus that coexist with the symbiotic

544 bacteria in the root nodule were reported to be present in the root nodules of wild legumes

545 (Deng et al. 2011). The presence of Spingomonas reported in the phyllosphere of Acacia in

546 central Argentina (Rivas et al. 2004). These results are in agreement with our results and

547 confirmed that the existence of Devosia genus with Acacia roots.

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548 The specific Rhizobium primers used were best suited for amplifying endophytic bacteria

549 in root nodule samples. The only exception was a few samples that failed to amplify. Because

550 not all sequences produced a closest match with a described well-known species, it is difficult

551 to discuss the presence of endophytic bacteria. Thus, only the composition of the communities

552 at the genus level for the taxonomic rank could be characterized. Overall, the microbial

553 population associated with the root system of nursery-grown Acacia seedlings was rich and

554 more diverse compared to that in rhizosphere and native desert soils. Because of the lack of

555 sufficient similarities with the sequences from NCBI, further studies are required to

556 characterize the bacterial population present in the natural desert soil at the species level. 557 Conclusions Draft 558 In the present study, we found that Bacteroidetes and Firmicutes are the most abundant

559 phyla followed by Acidobacteria and Betaproteobacteria in both desert and commercial mix

560 soils. Our investigation also revealed a considerable diversity in endophytic bacterial

561 community among different nodule samples obtained from the field and nursery. We found

562 the bacterial composition and diversity were distinct between rhizospheric and non-

563 rhizospheric soils. This study provides first time acuity on bacterial communities associated

564 with the roots of only surviving native A. gerrardii a tree species. We showed that the

565 bacterial communities are different with rhizosphere and non-rhizospheric bulk soil

566 conditions, and rhizospheric effects are evident. To our knowledge, our study for the first time

567 raveled that despite Kuwait’s harsh climate; the studied Lonely Tree roots harbor a diverse

568 endophytic bacterial community. Our investigation has provided a baseline insight about

569 ecological characteristics of A. gerrardii and for further functional characterization of

570 rhizospheric and endophytic bacterial communities. Re-vegetation of the Kuwait desert could

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571 need a greater level of plant diversity that could lead to a higher level of heterogeneity in

572 structure and exude patterns, capable of supporting a higher degree of bacterial diversity.

573 Clearly, further detail information is still required, but probably there is possibility to improve

574 better seedling production and survival rates of A. gerrardii seedlings by increasing

575 population of certain microorganisms in rhizosphere zone. Our study is a first comprehensive

576 work using molecular approach and progresses our current knowledge about the bacterial

577 microbiome related with this nationally important unique tree as the tree species is considered

578 endangered in Kuwait.

579 Acknowledgements 580 The authors acknowledge the KuwaitDraft Institute for Scientific Research (KISR) for providing 581 encouragement throughout the experiments. We also thank Dr. Damase Khasa and his

582 research team at Université Laval, Québec, Canada for the technical assistance, data analysis,

583 and valuable comments and reviewing an earlier version of this manuscript. This research did

584 not receive any specific grant from funding agencies in the public, commercial, or not-for-

585 profit sectors.

586 Conflicts of Interest

587 The authors reported no potential conflict of interest.

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843 844 Draft 845 Figure captions

846 Fig. 1. Phylogenetic tree showing molecular phylogenetic analysis obtained by maximum

847 likelihood of prominent DGGE bands of 16S rDNA sequences of bacterial soil amplification.

848 On the right it is showing major taxonomic groups identified, namely Acidobacteria,

849 Bacterioidetes, Firmicutes, Proteobacteria, and Actinobacteria. The phylum Bacterioidetes

850 were the dominant group in all soil samples.

851 Fig. 2. Phylogenetic tree showing maximum likelihood analysis of Rhizobiales bacteria

852 including Rhizobium, Agrobacterium and Shinella genera. Bootstrap percentage values

853 (>50%) are generated from 1000 replicates from maximum likelihood and posterior

854 probabilities from Bayesian analysis are shown as [Maximum likelihood bootstrap

855 values/Bayesian posterior probabilities]. Bold sequences are from this study.

856 Fig. 3. Phylogenetic tree showing maximum likelihood analysis of Bradyrhizobium,

857 Mesorhizobium and Ensifer (formerly Sinorhizobium) species. Bootstrap percentage values

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858 (>50%) are generated from 1000 replicates from maximum likelihood and posterior

859 probabilities from Bayesian analysis are shown as [Maximum likelihood bootstrap

860 values/Bayesian posterior probabilities]. Bold sequences are from this study.

861 Fig. 4. Phylogenetic tree showing maximum likelihood analysis of other Alphaproteobacteria.

862 Bootstrap percentage values (>50%) are generated from 1000 replicates from maximum

863 likelihood and posterior probabilities from Bayesian analysis are shown as [Maximum

864 likelihood bootstrap values/Bayesian posterior probabilities]. Bold sequences are from this

865 study.

866 Fig. 5. Correspondence analysis of the different bacterial communities in root nodules of 867 Acacia sp. in diverse conditions. NoduleDraft samples are positioned along the first two DA axes, 868 where Eigenvalues are 0.9110 for CA1 and 0.5899 for CA2.

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Draft

https://mc06.manuscriptcentral.com/cjm-pubs 89 AB682649 Niastella populi strain NBRCCanadian 107671 Journal of Microbiology Page 42 of 55 76 4-7-3 AB682352 Flavihumibacter petaseus NBRC 106054 90 JX100322 Uncultured bacterium clone HLUCs269 98 4-7-4 EU370955 Sphingobacteriaceae Gsoil809 4-7-5 85 68 EU194882 Flavisolibacter sp A35 67 4-8-5 JF488342 Bacteroidetes SCGCAAA166-I10 68 67 4-2-3 JX624252 Salinimicrobium sp CAU1287 100 4-1-1 JN899241 Nafulsella turpanensis ZLM-10 99 4-2-4 JN417561 Uncultured soil bacterium clone 12-49 FM209309 Uncultured bacterium clone 1241 72 NR 042235 Adhaeribacter aquaticus MBRG1-5 Bacteroidetes 4-5-3 52 KC925257 Uncultured bacterium clone 16SJ1 4-11-2 NR 108511 Chryseolinea serpens RYG 4-13-2 JF986940 Uncultured Bacteroidetes clone Upland40-6238 4-13-1 56 AJ871243 Flexibacter flexilis clone 153-1 KC432491 Uncultured bacterium clone SEAD1DD121 4-1-3 4-2-6 90 EF626900 Uncultured bacterium clone RC2-178Draft 4-10-2 AB360413 Bacterium RS19G JN417572 Uncultured soil bacterium clone 24-28 75 4-15-4 219913865 Uncultured Sphingobacteriales clone CM38F8 100 4-12-5 AY364020 Methylobacterium sp iEII3 52 AGU87781 Afipia genosp10 Alphaproteobacteria AF469072 Devosia neptuniae J1 D86513 Rhodopila globiformis 93 HQ697428 Uncultured bacterium clone B46 89 AY795686 Betaproteobacterium Schreyahn AOB-SSU-Aster2 Proteobacteria 54 4-5-4 Betaproteobacteria AJ420323 Acidovorax delafieldii SM 50263 59 97 DQ490308 Oxalobacteraceae bacterium KVD-unk-24 50 AB021388 Janthinobacterium lividum ATCC33665 NR041368 Lysobacter panaciterrae Gsoil068 Gammaproteobacteria 75 KF057196 Xanthomonas campestris campestris TUr1 96 HQ995659 Acidobacteriaceae bacterium 277 100 3-7-4 51 HM748714 Bacterium Ellin7504 Acidobacteria 100 GQ264366 Uncultured bacterium clone WW2-41 76 4-9-1 AB245397 Actinomycetales bacterium Gsoil 1632 80 NR040880 Tetrasphaera duodecadis IAM14868 Actinobacteria 99 EF063479 Streptomyces fradiae 7273 98 KC893662 Bacillus sp G5(2013) 4-7-7B 3-2-6 62 AB696842 BacillusSP UNPA236 3-1-6 99 Firmicutes 3-1-7 KF219799 Planomicrobiumhttps://mc06.manuscriptcentral.com/cjm-pubs koreense KBM-2-20 88 3-4-1 KC921179 Bacillus senegalensis WY167 FR877762 Bacillus niacini BD12OL1-B46 Page 43 of 55 KF704746 Shinella zoogloeoidesCanadian strain SM22 Journal of Microbiology 12C-6 OTU-9A NR044066 Shinella kummerowiae strain CCBAU25048 KF318040 Shinella granuli strain PGR3 97/1.00 KC252688 Shinella fusca strain N016 77/1.00 1A-8 OTU-44 76/- AB285481 Shinella yambaruensis strain MS4 80/1.00 AM403191 Rhizobiales bacterium D5-25 88/- 12C-5 OTU-9B 99/1.00 HM194609 Shinella sp. AGR1(2010) 12A-1-12 OTU-25A Y17047 Allorhizobium undicola -/0.72 99/0.98 AY509210 Rhizobium etli strain S1 19B-3 OTU-4 U86343 Rhizobium gallicum JX524433 Rhizobium galegae 99/1.00 JX407092 Rhizobium huautlense strain DL01 84/0.98 3C-9 OTU-1B 71/1.00 JQ660038 Rhizobium alkalisoli strain S1-181 96/0.97 AY626396 Agrobacterium vitis strain ICMP5960 97/1.00 DQ337571 Rhizobium sp CHNTR26 72/0.99 2B-2 OTU-6 Rhizobium/Agrobacterium/Shinella 97/1.00 GU201840 Rhizobium sp Qtx-14 Rhizobiaceae 20A-12 OTU-8 11A-8 OTU-12F Draft EU817493 Rhizobium sp XJ-L72 86/0.97 78/- NR113608 Agrobacterium rubi strain NBRC13261 75/0.74 20A-1 OTU-12D 95/1.00 AJ389902 Agrobacterium tumefaciens strain NCPPB1641 JQ771467 Rhizobium sp G58 90/1.00 12C-1 OTU-12C 99/1.00 KJ184900 Agrobacterium sp CZBSA1 NR074266 Agrobacterium fabrum strain C58 AM157353 Rhizobium radiobacter strain GCIZ 10C-16 OTU-24 98/0.59 72/0.99 NR026059 Rhizobium giardinii strain H152 KC117530 Rhizobium sp RS3-4-B U29386 Rhizobium leguminosarum bv viciae 80/- 87/0.99 KF787795 Rhizobium vallis strain J15 21B-1 OTU-7B 99/0.99 AY206687 Rhizobium rhizogenes strain 163C 63/- NR029195 Rhizobium hainanense strain I66 82/1.00 JN129372 Rhizobium tropici strain CNPSO655 84/0.99 19C-1 OTU-7C X67222 Sinorhizobium meliloti strain LMG6133 84/1.00 D14516 Sinorhizobium fredii type strain ATCC35423 Ensifer/Sinorhizobium 70/0.83 AM181753 Sinorhizobium saheli LMG11864 56/- JX891459 Mesorhizobium ciceri strain CB8 Mesorhizobium AY509218 Mesorhizobium loti strain S139 AF469072 Devosia neptuniae strain J1 Devosia Hyphomicrobiaceae D11342 Azorhizobium caulinodans type strain ORS571 Azorhizobium Xanthobacteriaceae 100/1.00 AB070571 Bradyrhizobium japonicum strain USDA135 Bradyrhizobium Bradyrhizobiaceae HQ233240https://mc06.manuscriptcentral.com/cjm-pubs Bradyrhizobium elkanii strain USDA76

0,01 Canadian Journal of Microbiology Page 44 of 55 71/- NR108508RhizobiumsubbaraonisstrainJC85 55/- 10B-11OTU-11 AY024335Sinorhizobiummorelense NR113893EnsiferadhaerensstrainNBRC100388

91/0.67KF437393EnsiferspJNVUCM16 74/0.6510C-3OTU-33

D14516SinorhizobiumfrediitypestrainATCC35423 Ensifer/Sinorhizobium NR025251SinorhizobiumamericanumstrainCFNEI156 AM181753SinorhizobiumsaheliLMG11864 75/- 52/0.95 NR113891SinorhizobiumterangaestrainNBRC100385 92/0.80X67222SinorhizobiummelilotistrainLMG6133 98/1.00 EF201801SinorhizobiummedicaeisolateRPA20 NR037001SinorhizobiumarborisstrainTTR38 AJ389902AgrobacteriumtumefaciensstrainNCPPB1641 62/0.98 97/1.00 Rhizobiaceae U86343Rhizobiumgallicum 89/1.00 Rhizobium/Agrobacterium 92/0.99 AY206687Rhizobiumrhizogenesstrain163C U29386Rhizobiumleguminosarumbvviciae NR026426MesorhizobiumplurifariumstrainLMG11892 95/1.00 AY509218MesorhizobiumlotistrainS139 NR024879MesorhizobiumamorphaestrainACCC19665 73/- 63/0.81NR044118MesorhizobiumcaraganaestrainCCBAU11299Draft Mesorhizobium NR044052MesorhizobiumgobiensestrainCCBAU83330 57/1.00 10B-9OTU-23

50/0.95 KC759691MesorhizobiumspBP2 95/1.0 0 55/- JX891459MesorhizobiumciceristrainCB8 99/1.00NR102452MesorhizobiumaustralicumstrainWSM2073 JQ014376SinorhizobiumspLC541 Sinorhizobium 61/- 12B-3OTU-34 AF469072DevosianeptuniaestrainJ1 Devosia Hyphomicrobiaceae Azorhizobium Xanthobacteriaceae D11342AzorhizobiumcaulinodanstypestrainORS571 100/1.00 DQ520809BradyrhizobiaceaebacteriumNR111 53/- 21B-7OTU-16 100/0.95HM107183AlphaproteobacteriumCCBAU45397

92/0.99 20B-7OTU-15 99/0.96 HQ233240BradyrhizobiumelkaniistrainUSDA76 NR043037BradyrhizobiumpachyrhizistrainPAC48 Bradyrhizobium Bradyrhizobiaceae 100/1.00 NR041827BradyrhizobiumdenitrificansstrainIFAM1005 96/1.00 NR112671BradyrhizobiumiriomotensestrainEK05 AY577427Bradyrhizobiumcanariense 78/- NR028768BradyrhizobiumyuanmingensestrainB071 61/- AB070571BradyrhizobiumjaponicumstrainUSDA135 57/0.99 NR112095Bradyrhizobiumliaoningensestrain2281 https://mc06.manuscriptcentral.com/cjm-pubs 0.02 Page 45 of 55 Canadian Journal of Microbiology

59/0.97 AF469072DevosianeptuniaestrainJ1 KC464823DevosiaspR41 Hyphomicrobiaceae 93/0.963C-2OTU-14A Group1 97/1.00 NR113618DevosiariboflavinastrainNBRC13584 99/1.001B-10OTU-14C NR104723Vasilyevaeaenhydrastrain9b Unclassified 12B-13OTU-28 Rhizobiales 99/1.00 D11342AzorhizobiumcaulinodanstypestrainORS571 Xanthobacteriaceae NR041839AzorhizobiumdoebereineraestrainBR5401 87/0.96 97/1.00 EF191408MicrovirgalupinistrainLut6 HM362433MicrovirgazambiensisWSM3693 Methylobacteriaceae NR112614MethylobacteriumnodulansstrainLMG21967 76/1.00 99/1.00 M65248AfipiafelisATCC53690strainB-91-007352 HQ233240BradyrhizobiumelkaniistrainUSDA76 Bradyrhizobiaceae 89/0.98 AB070571BradyrhizobiumjaponicumstrainUSDA135 NR024920NitrobacteralkalicusstrainAN1 92/0.99 KC921198HyphomicrobiaceaebacteriumWX185 99/1.0 19A-6OTU-13B NR074189HyphomicrobiumdenitrificansstrainATCC51888 0 62/- Hyphomicrobiaceae AY934488HyphomicrobiumspWG6 Group2 21B-9OTU-13A FM886904PedomicrobiumaustralicumOTSz-M-268 Alpha-proteobacteria/Rhizobiales 92/0.99 1C-5OTU-43 99/1.00 JF184047Unculturedbacteriumclonencd2136b01c1 Unclassified 12A-1-14OTU-32 Rhizobiales 93/- AY206687Rhizobiumrhizogenesstrain163C 65/- U29386Rhizobiumleguminosarumbvviciae 63/0.96 U86343Rhizobiumgallicum 63/0.96 Y17047Allorhizobiumundicola 67/- AJ389902AgrobacteriumtumefaciensstrainNCPPB1641 NR044066ShinellakummerowiaestrainCCBAU25048 68/0.75 JX891459MesorhizobiumciceristrainCB8Draft 96/- AY786080Phyllobacteriumtrifolii Rhizobiaceae 70/- AY509218MesorhizobiumlotistrainS139 60/- D14516SinorhizobiumfrediitypestrainATCC35423 66/1.00AM181753SinorhizobiumsaheliLMG11864 X67222SinorhizobiummelilotistrainLMG6133 92/0.9385677386BartonellaelizabethaestrainQ-3 10A-3OTU-5 Bartonellaceae KF956670OchrobactrumspS21103 75/- AY776289OchrobactrumcytisistrainESC1 99/1.0019C-13OTU-26 Brucellaceae NR042911OchrobactrumlupinistrainLUP21 1A-9OTU-40 99/1.00 AY771798SphingomonasspAlpha4-5 20B-1OTU-18 87/1.00 99/1.00JX239758SphingopyxisspUBF-P4 Sphingomonadaceae 97/1.00 19B-1OTU-20 KC410867NovosphingobiumspDC-9 95/1.0012C-8OTU-21 HF930765BlastomonasspP2AR16 JQ963327ErythrobacteraceaebacteriumK-2-3 Alpha- 12A-1-10OTU-27 proteobacteria/Sphingonomadales KC012862BacteriumBW3PhG20 Erythrobacteriaceae 1C-10OTU-41 99/1.00 GQ476825AltererythrobacterspR83-1 FJ889319UnculturedErythrobacteraceaebacteriumclonePlot18-2F10 20A-3OTU-19 99/1.00FJ455532DongiamobilisstrainLM22 80/- 20B-10OTU-17 99/1.00KJ524113Inquilinussp72bal 1A-1OTU-42 Rhodospirillaceae 99/1.00 HM636056AzospirillumcanadensestrainLMG23617clone1 Alpha- NR114058AzospirillumlipoferumstrainNBRC102290 proteobacteria/Rhodospirillales 99/1.00 GQ476822SkermanellaspR224-3 12B-14OTU-29 NR116305AzotobacterchroococcumstrainLMG8756 Pseudomonadaceae Gamma- 99/1.00 NR074774NitrosomonaseuropaeaATCC19718 Nitrosomonadaceae Beta-proteobacteria/Pseudomonadales 96/1.00 NR026462BurkholderiacaribensisstrainMWAP64Burkholderiaceae proteobacteria/Nitrosomonadales https://mc06.manuscriptcentral.com/cjm-pubsNR074823CupriavidustaiwanensisstrainLMG19424 Beta- proteobacteria/Burkholderiales 0.02 Canadian Journal of Microbiology Page 46 of 55

Draft

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1 Table 1. Concentration of total N, P, K, organic matter, Ca, and Mg present in soil and irrigation water.

Organic Organic Ece N P K Ca Mg Sample ID pH matter carbon

(mS/cm) (%) (mg/kg) (%) (mg/kg)

LT-RS 7.33±0.3 3.44±1.2 0.07±0.02 1.16±1.1 90.26±76.6 0.95±0.78 0.55±0.4 274.23±110.9 49.15±26.9

LT-CS 7.67±0.1 1.75±0.6 0.03±0.01 0.37±0.4 8.85±3.4 0.45±0.09 0.26±0.0 111.87±56.4 10.99±4 N-CS 7.13±0.1 1.29±0.1 0.14±0.01 2.36±0.9Draft250±10.0 8.62±9.4 5±0.5 1540±212.3 133±14.2 N-SARS 7.4±0.1 1.75±0.3 0.14 ±0.02 123.54±33.6 32.39±8.3 8.38±1.42 4.86±0.8 196.1±53.9 22.52±8.6

N-LTRS 7.37±0.2 2.32±0.8 0.15±0.05 177.37±66.2 49.2± 22.4 7.98±0.32 4.63±0.1 351.95±185.9 36.57±26.6

pH (mS/cm) mg/l

Irrigation

water for N- 7.3±0.0 0.37±0.3 4.68±1.91 0.32±0.2 2±0.0 NA NA 46.67±5.3 0.86±0.3 SARS & N-

LTRS

2 LT-RS: Lonely tree composite rhizospheric soil; LT-CS: Lonely tree control bulk soil; N-CS: Nursery control soil; N-LTRS: Nursery Lonely tree rhizospheric 3 soil; ECe: Electrical conductivity of saturated soil extract; N: Nitrogen; P: Phosphorus; K: Potassium;Ca: Calcium; Mg: Magnesium 4

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5 Table 2. Phylogenetic identification and distribution of bacteria excised and sequenced from DGGE bands.

Sample DGGE Putative Most closely related bacterial % % Genus Isolation source Label bands Classification sequence (accession number) identity abundance Uncultured soil bacterium 4-1-1 Soil 99 (EF688382) Uncultured bacterium 4-1-3 Apple orchard 97 (KC331476) Uncultured bacterium 4-2-3 Bacteroidetes Apple orchard 87 62.5 (KC331461)Draft Nafulsella turpanensis 4-2-4 Arid soil 88 LTRS (JN899241) Uncultured bacterium 4-2-6 Wetland 85 (KC432491) 3-1-6 Bacillus sp. (AB696842 ) Rice paddy soil 94 Planomicrobium koreense Ugan River/Populus 3-1-7 98 Firmicutes (KF219799) euphratica 37.5 Uncultured Firmicutes 3-2-6 Upland cropland soils 90 bacterium (JF990241) 6

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7 Table 2 cont.

Sample DGGE Putative Most closely related bacterial % % Genus Isolation source Label bands Classification sequence (accession number) identity abundance Host root tissues and 3-4-1 Firmicutes Bacillus niacini (FR877762) 98 33.3 associated Soil Uncultured bacterium 4-5-3 Bacteroidetes Sand soil 94 33.3 LT-CS (FM209309) Uncultured bacterium Drinking water 4-5-4 Betaproteobacteria 87 33.3 (HQ697428) treatment Uncultured Sphingobacteria Forest at the GASP 4-7-3 96 bacterium (EF665817) KBS-LTER Site UnculturedDraft bacterium 4-7-4 Forest soil 96 (JX100322) Bacteroidetes Oryza sativa cv. Dong- 57.1 4-7-5 Flavisolibacter sp. (EU194882) 93 jin Sphingobacteriaceae bacterium Soil from ginseng field 4-8-5 98 N-CS Gsoil (EU370955) in Pocheon Acidobacteriaceae bacterium 3-7-4 Soil 98 (HQ995659) Acidobacteria 28.6 Uncultured bacterium Simulated low level 4-9-1 95 (GQ264366) waste site

4-7-7B Firmicutes Bacillus sp. (KC893662) Enzymatic apple juice 92 14.3

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9 Table 2 cont.

Sample DGGE Putative Most closely related bacterial % % Genus Isolation source Label bands Classification sequence (accession number) identity aundance Uncultured bacterium 4-10-2 Soil 98 (EF626900) Uncultured soil bacterium 4-11-2 Soil 90 (JN417561) Uncultured Sphingobacteriales 4-12-5 Draft Contaminated soil 96 bacterium (AM936482) N-LTRS Bacteroidetes 100 Uncultured Bacteroidetes 4-13-1 Upland cropland soils 93 bacterium (JF986940) Uncultured bacterium 4-13-2 Sediments 92 (KC925257) Uncultured soil bacterium 4-15-4 Soil 100 (JN417572) 10 LT-RS: Lonely tree composite rhizospheric soil; LT-CS: Lonely tree control bulk soil; N-CS: Nursery control soil; N-LTRS: Nursery Lonely tree rhizospheric 11 soil. The numbers following the codes indicate the different replicates. 12

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14 Table 3. BLAST result for representing clone sequences from nodule communities for each OTU- Relative frequency of each OTU

15 when sequence similarity threshold is 97%-Diversity indices for each sample type.

OTU Clones Similarity LT-ND N-LTND N-SAND Accession Identity no. representative (%) 1-2-3 10-11-12 19-20-21

1 3C-9 JX407092 Rhizobium huautlense (DL01) 98 30* 0 8*

4 19B-3 AY509210 Rhizobium etli (S1) 99 0 0 6* 5 10A-3 AB246807 Bartonella elizabethaeDraft (Q-3) 99 0 13* 1 6 3C-8 DQ337571 Rhizobium sp. (CHNTR26) 96 15* 0 0

7 21B-1 KF787795 Rhizobium vallis (J15) 98 8* 4 14*

8 20A-12 GU252152 Shinella sp. (CC-CCM15-9) 99 0 0 2

9 12C-6 KF261556 Rhizobium sp. (C12-2013) 99 0 9* 8*

11 10B-11 NR108508 Rhizobium subbaraonis (JC85) 98 0 9* 3

12 12C-1 KJ184900 Agrobacterium sp. (CZBSA1) 99 0 21* 28*

13 21B-9 AY934488 Hyphomicrobium sp. (WG6) 97 4 0 7

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18 Table 3 Cont.

Clones Similarity LT-ND N-LTND N-SAND Identity OTU no. representative Accession (%) 1-2-3 10-11-12 19-20-21

14 3C-2 KC464823 Devosia sp. (R41) 98 31* 0 0

15 20B-7 HM107183 Alpha proteobacterium (CCBAU 45397) 99 0 5 2

16 21B-7 DQ520809 Bradyrhizobiaceae bacterium (NR111 ) 99 0 0 3 17 20B-10 FJ455532 Dongia mobilis (LM22)Draft 99 0 0 2 18 20B-1 AY771798 Sphingomonas sp. (Alpha4-5 ) 98 1 1 13*

Uncultured Erythrobacteraceae (Plot18- 19 20A-3 FJ889319 99 0 0 2 2F10)

20 19B-1 JX239758 Sphingopyxis sp. (UBF-P4) 99 4 4 1

21 12C-8 KC410867 Novosphingobium sp. (DC-9) 97 0 5* 0

23 10B-9 KC759691 Mesorhizobium sp. (BP2 ) 98 0 1 0

24 10C-16 KC117530 Rhizobium sp. (RS3-4 B) 99 0 15* 0

25 11A-4 JX292365 Rhizobium sp. (L32C549B00) 98 0 6 0

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20 Table 3 Cont.

SimilarityLT-ND N-LTND N-SAND Identity OTU no.Clones representative Accession (%) 1-2-3 10-11-12 19-20-21

26 19C-13 KF956670 Ochrobactrum sp. (S21103) 99 0 0 2

27 12A-1-10 JQ963327 Erythrobacteraceae bacterium (K-2-3) 98 0 1 0

28 12B-13 NR_104723Vasilyevaea enhydra (9b) 94 0 1 0 29 12B-14 GQ476822 SkermanellaDraft sp. (R224-3) 99 0 1 0 32 12A-1-14 JF184047 Uncultured bacterium (ncd2136b01c1) 98 0 1 0

33 10C-3 KF437393 Ensifer sp. (JNVU CM16) 99 1 1 0

34 12B-3 JQ014376 Sinorhizobium sp. (LC541) 95 0 1 0

39 1A-9 HF930765 Blastomonas sp. (P2AR16) 93 1 0 0

41 1C-10 GQ476825 Altererythrobacter sp. (R83-1) 96 1 0 0

42 1A-1 KJ524113 Inquilinus sp. (73bal) 99 1 0 0

43 1C-5 FM886904 Pedomicrobium australicum (OTSz_M_268 ) 98 1 0 0

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23 Table 3 Cont.

Similarity LT-ND N-LTND N-SAND OTU no. Clones representativeAccession Identity (%) 1-2-3 10-11-12 19-20-21 44 1A-8 KC252688 Shinella fusca (N016 ) 100 1 0 0 24 *: Dominant OUT (OTU is considered dominant if Pi > 1/S, where Pi represents the probability of sampling OTU i and S is the OTU richness); LT-ND: Lonely 25 Tree Root Nodule (A. gerrardii); N-LTND: Nursery grown Lonely Tree (local A. gerrardii) root nodule; N-SAND: Nursery grown Saudi Arabia (non-local) A. 26 gerrardii. 27 28 29 Draft 30

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Table 4. Estimated OUT richness, diversity index and sample coverage of the clone

libraries obtained from root nodule communities of Acacia gerrardii

LT-ND N-LTND N-SAND Description 1-2-3 10-11-12 19-20-21

Nb of libraries 7 7 6

Nb of clones (N) 61 65 62

Shannon-Wiener Diversity Index 1.799 2.42 2.323

OTU Richness (S) 13 18 16

Simpson Diversity Index

D: 0.223 0.115 0.135

1-D: Draft0.777 0.885 0.865

1/D: 4.477 8.728 7.421

Evenness (Pielou) 0.701 0.837 0.838

Rarefaction (60 individuals) 10.2 14.8 14.2

** Coverage 0.885 0.877 0.968

**Coverage: C is defined by the equation: C = 1 - (n1/N), n1 is the number of clones that occurred only once (frequency = 1), and N is the total number of clones examined of species richness; LT-ND: Lonely Tree Root Nodule (A. gerrardii); N-LTND: Nursery grown Lonely Tree (local A. gerrardii) root nodule; N-SAND: Nursery grown Saudi Arabia (non-local) A. gerrardii.

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