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Applied Soil Ecology 68 (2013) 1– 9

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Applied Soil Ecology

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Short communication

Soil microbiomes vary in their ability to confer droughttolerance to Arabidopsis

Gaston Zollaa, Dayakar V. Badria, Matthew G. Bakkera,Daniel K. Manterb, Jorge M. Vivancoa,∗

a Center for Rhizosphere Biology, Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO 80523, USAb United States Department of Agriculture-Agricultural Research Service, Soil-Plant-Nutrient Research Unit, Fort Collins, CO 80526, USA

a r t i c l e i n f o

Article history:Received 22 October 2012Received in revised form 22 February 2013Accepted 14 March 2013

Keywords:DroughtSympatricSoil microbiomeArabidopsisPyrosequencing

a b s t r a c t

Drought is a major constraint on agricultural production. Crop genetic improvement for drought tolerancehas received much attention and there is ample information about the ability of specific soil microbes toinfluence drought tolerance in plants. However, in nature, plants interact simultaneously with an array ofbeneficial, benign and pathogenic microbes. There is a need to understand the cumulative effect of thesemultiple interactions on a plant’s ability to overcome abiotic stresses such as drought. The objective of thisresearch was to investigate the potential of whole soil microbiomes to help Arabidopsis thaliana plants dealwith drought stress under in vivo conditions. A sympatric microbiome (i.e., having a history of exposure toArabidopsis at a natural site) significantly increased plant biomass under drought conditions, but causedearlier death rates as a consequence of drought; whereas, the two non-sympatric soils did not influenceArabidopsis biomass. Consistent with this, we observed reduced expression levels for several Arabidopsisdrought response marker genes (ATDI21, DREB1A, DREB2A, and NCED3) in the sympatric Arabidopsis soiltreatment. Pyrosequencing analysis of the three soil microbiomes used in this study identified 84 bacterialOTUs (3% genetic distance) from 41 genera (Burkholderia, Phormidium, Bacillus, Aminobacter, Acidiphilumand among others) that were significantly higher in the sympatric Arabidopsis soil, as compared to the twonon-sympatric soils. In conclusion, we have identified a robust set of Arabidopsis-associated microbesthat when present in the soil can modify the plant’s ability to sense abiotic stress and increase its biomassproduction.

© 2013 Published by Elsevier B.V.

1. Introduction

Drought is a major constraint on plant growth and agriculturalproductivity around the world (Balestrini and Vartanian, 1983;Yamaguchi-Shinozaki and Shinozaki, 2006), particularly for sub-sistence farmers with little or no access to water for irrigation(Ceccarelli and Grando, 1996). Currently, 75% of global water con-sumption is used for agriculture (Molden, 2007). For instance, theproduction of 1 kg of grain requires an average of 900 l of waterfor wheat (Triticum spp.), 1400 l for maize (Zea mays), and 1900 lfor rice (Oryza sativa) (Pimentel et al., 1997). To aid in the devel-opment of drought-resistant crops and production systems, it isimportant that we understand the mechanisms of drought toler-ance in plants. There are several distinct steps in the drought stress

∗ Corresponding author at: Colorado State University, Center for Rhizosphere Biol-ogy, 1173 Campus Delivery, Fort Collins, CO 80523-1173, USA.

E-mail addresses: dayakar@lamar.colostate.edu (D.V. Badri),j.vivanco@colostate.edu (J.M. Vivanco).

response, such as sensing of stress, systemic signaling pathways,and genetic regulation, including epigenetic controls and activ-ities of small RNAs (Shinozaki and Yamaguchi-Shinozaki, 2007;Mittler and Blumwald, 2010). Beyond these plant-centric responsesto drought stress, there is also a strong possibility of interactiveeffects involving associated microorganisms.

Soil microbes contribute to a wide range of functions thatare important to plant productivity, such as nutrient cycling,mineralization of soil organic matter, inducing disease resistanceand responding to abiotic stresses such as drought and salinity. Forexample, Timmusk and Wagner (1999) showed that Paenibacilluspolymyxa enhanced drought tolerance in Arabidopsis thalianain a gnotobiotic system by modulating the expression of thedrought stress responsive gene ERD15 (Kiyosue et al., 1994).Moreover, Achromobacter piechaudi ARV8 isolated from Arava,a region in southern Israel, was found to increase fresh anddry weight of tomato seedlings in arid and salty environmentsby modulating ethylene levels through the degradation of itsprecursor 1-aminocyclopropane-1-carboxylic-acid (ACC) via thebacterial enzyme ACC deaminase (Mayak et al., 2004a,b). The

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ACC hydrolysis products, ammonia and �-ketobutyrate, becomeavailable to the bacterium as a source of nitrogen and carbon (Kleeet al., 1991). Marulanda et al. (2009) reported that Pseudomonasputida, Pseudomonas sp. and Bacillus megaterium were able tostimulate growth of Trifolium repens under dry conditions. Strainsof both Pseudomonas and Bacillus have shown ACC deaminaseactivity (Ghosh et al., 2003; Glick et al., 2007). However, othermechanisms of impacting plant drought tolerance are also pos-sible. For instance, Murzello (2009) reported that volatile organiccompounds (VOCs) from B. subtilis GBO3 increased expressionof the PEAMT gene in plants. The PEAMT gene is involved inthe accumulation of osmolytes and osmoprotectants such ascholine and glycine betaine, which are known to enhance droughttolerance.

There is ample information about the ability of specific soilmicrobes to influence drought tolerance in plants. However, innature, plants interact simultaneously with an array of beneficial,benign and pathogenic microbes. There is a need to understandthe cumulative effect of these multiple interactions on a plant’sability to overcome abiotic stresses such as drought. In particu-lar, sympatric associations between plants and soil microbes mayoccur, such that there is greater interaction between a microbialcommunity and a ‘familiar’ host plant than with an ‘unfamiliar’host plant. Here, we studied the interaction between Arabidopi-sis thaliana and three distinct soil microbiomes (derived fromArabidopsis, corn and pine soils) under drought stress condi-tions. Our results suggest that the sympatric microbiome enhancesplant biomass under drought stress by reducing the perception ofthe stress signaling response. We further characterized the threesoil microbiomes by 454 sequencing in an effort to find correla-tions between drought tolerance, microbial descriptors and therecently reported core microbiome of Arabidopsis (Lundberg et al.,2012).

2. Materials and methods

2.1. Soil collection and characterization

Three field soils were used in our studies, each having a differ-ent dominant overstory plant species. The pine and corn soils werecollected as part of a larger study to investigate sampling effects onmicrobial community assessments (Manter et al., 2010a). Briefly,soils (0–5 cm) were collected within the crown (less than 240 cmfrom the base of the plant) of three different plants at each site. Pinesoil was collected at Young’s Gulch, CO (N40◦40′20′’, W105◦20′50′’)where ponderosa pine is the major overstory species and precipi-tation was recorded as 5.5 cm. Corn (Zea mays) soil was collectedfrom the Colorado State University Agricultural Research, Develop-ment and Extension Center (ARDEC), Fort Collins, CO (N40◦39′07′’,W104◦59′58′’), where strip-tilled, continuous corn has been grownsince 2009 and precipitation was recorded as 4.7 cm. The Ara-bidopsis soil (0–5 cm) was collected from the center of Arabidopsisplant patches growing naturally at the Michigan Extension Station,Benton Harbor, MI (N42◦05′34′′, W86◦21′19′′) and the precipita-tion was recorded as 8.8 cm. At this last site, Arabidopsis hasgrown naturally along with several natural grasses in the fallowsoil for several years. All three soils were collected in July, 2011and were stored at 4 ◦C until use. Prior to analysis, all soils fromeach site were pooled and thoroughly homogenized by hand. Soilswere analyzed for pH, electrical conductivity (EC), organic matter,ammonium, nitrate, phosphorus, potassium, zinc, iron, copper, drymatter, total nitrogen, carbon to nitrogen ratio (C:N) (Thompsonet al., 2002), sodium absorption ratio (USDA, 1996) and hydrome-ter density (Klute, 1986) at the Soil Testing Laboratory of ColoradoState University.

2.2. Drought stress experiments

2.2.1. Plant material and growth conditionsSeeds of Arabidopsis thaliana Col-0 were surface-disinfested in

Clorox® bleach for 1 min, rinsed five times with sterile water andthen stratified at 4 ◦C for 4 days to break dormancy. Seeds wereplated on MS agar plates (MS salt, pH 5.7, 1% sucrose, and 1%agar) and placed vertically in a growth room at 25 ◦C, with a 16/8 hlight/dark photoperiod.

2.2.2. Inoculum preparationTwo experiments (full and partial drought) were conducted in

a control soil using filter-sterilized and non-filtered soil slurriesderived from the Arabidopsis, corn, and pine soils described belowto separate the abiotic and biotic factors. We adopted this methodbecause autoclaving the soil is a harsh manner to kill microbesthat alters the soil chemistry by releasing the cellular contents ofsoil organisms and modifies the soil structure. In this experiment,microbes were removed by sterile-filtering, and the resultant phys-ical removal of the microbes did not release their chemical contents.However, we acknowledge that filtering may remove some ofthe chemical contents due to adhesion to the filter membrane;however, an attempt to minimize this was achieved by preparinginocula in Hoagland’s solution. In other words, the filtered treat-ment could remove the microbial community and an unknownchemical component(s); whereas, the autoclaved treatment couldremove the microbial community but may add an unknown chemi-cal component and/or change the structure of the soil. For each soil,100 g of soil was suspended in 1 L of a 1× Hoagland’s solution (Phy-totechnology Laboratories, USA) by shaking for 1 h. After settlingfor 30 min, the supernatant was centrifuged (2000 rpm, 5 min) topellet soil particles. The resulting supernatant containing both soilmicrobes and chemical solutes was used as non-filtered inoculum.For controls, the supernatant was further centrifuged (12,000 rpm,15 min) and filtered (0.45 �m nylon filter, Millipore).

2.2.3. Full drought experimentThis experiment consisted of six treatments in a factorial design:

three different soil microbiomes (derived from Arabidopsis, corn,or pine soil) × two forms of amendment (filtered vs. non-filtered, asdescribed above). Nine replicate pots were planted for each treat-ment, with one plant per pot. All plants were placed on the sameshelf in a single growth chamber and were grouped by treatment.Seven day old Arabidopsis seedlings were transferred into pots con-taining a mix of sterile sand and vermiculite (1:1). The substratewas sterilized with five cycles of autoclaving (40 min, 121 ◦C) andcooling to room temperature. Filtered and non-filtered soil slurrieswere applied to appropriate treatments twice, when plants were10 and 14 days old. When plants reached the 6-leaf stage (21 daysold), watering was ceased in order to impose drought stress. Plantswere monitored for 18 days after the cessation of watering. Relativewater content was measured by following the method described inYoo et al. (2010) on the pots at 3, 5, 8, 10, and 12 days after thecessation of watering. Briefly, relative water content was calcu-lated by weighing the pots and employing the following equation:relative water content = (final fresh weight - dry weight)/(initialfresh weight - initial dry weight) × 100. Mortality was determinedby visual assessment and re-watering for three days as describedabove. Aboveground tissues were harvested at the end of the stressperiod and accumulated biomass was determined after drying at70 ◦C for three days.

2.2.4. Partial drought experimentThis experiment consisted of seven treatments, including a con-

trol treatment and a factorial design using three different soilmicrobiomes (derived from Arabidopsis, corn, or pine soil) × two

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forms of amendment (filtered vs. non-filtered, as described above).Nine replicate pots were planted for each treatment, with oneplant per pot. All plants were placed on the same shelf in a sin-gle growth chamber, and were grouped by treatment. Six of thereplicates were used for measurement of aboveground dry biomass,and the remaining 3 replicates were used for gene expression anal-yses (described below). Plants in the control treatment receivedonly the nutrient solution (1X Hoagland’s) used to generate thesoil inoculums. In this experiment, less extreme drought condi-tions were imposed; soil moisture was maintained at constant lowlevels rather than being allowed to continuously decline, follow-ing the method of Luna et al. (2005). Water content was measuredby weighing the pots individually. Pots were maintained at 40% offull-watering conditions by replenishing the water lost once perday. Partial drought conditions were maintained for 13 days beforeaboveground tissues were harvested.

2.3. Gene expression analysis

Expression levels for several marker genes associated withdrought response in Arabidopsis (ATDI21, DREB1A, DREB2A, andNCED3) (Gosti et al., 1995; Liu et al., 1998; Iuchi et al., 2001; Sakumaet al., 2006) were measured with semi-quantitative RT-PCR. Planttissues were collected from the partial drought experiment, asdescribed above, and were stored at −80 ◦C until processing. TotalRNA was isolated with TRI REAGENT (Molecular Research Cen-ter, Inc.) according to the manufacturer’s instructions. Total RNA(2.5 �g) was treated with DNAse I (Fermentas) to eliminate thegenomic DNA contamination. cDNA was synthesized with oligo dT(Invitrogen) using SuperScript® III First-Strand Synthesis System(Invitrogen) according to the manufacturer’s instructions. Semi-quantitative RT-PCR was carried out with gene-specific primers(Table S1). UBQ10 was used as a control to ensure equal loadingsof cDNA for each sample. The quantification of fold induction wasdetermined by measuring the band intensities using ImageJ Soft-ware after normalization with control ubiquitin. The PCR analysiswas carried out three times with three independent biological repli-cates. A paired T-test was performed to determine differences inmean signal values between the treatments.

2.4. Data analyses

Differences in soil water contents were analyzed by repeatedmeasures ANOVA with soil microbiome (e.g., filtered and non-filtered) as fixed effects using PROC MIXED in SAS Vers. 9.3 (SASInstitute, Cary, NC, USA). Due to the presence of a significant inter-action, the effect of the soil microbiome was tested using an analysisof simple effects (SLICE statement), which provides a means of par-titioning significant interactions to simple effects (Winer, 1971).Differences in Arabidopsis biomass were analyzed by a two-wayANOVA with soil microbiome (e.g., filtered and non-filtered) asfixed effects using PROC MIXED in SAS Vers 9.3, and the effect ofthe soil microbiome was tested using an analysis of simple effects.Differences in the date of mortality were analyzed by time-to-event(survival) analysis using the non-parametric Wilcoxon test in PROCLIFETEST in SAS Vers 9.3. All reported values are the median and 95%confidence interval for the day of mortality.

2.4.1. Pyrosequencing analysesDNA extraction of 0.5 g samples of pine, corn and Arabidop-

sis soil was performed using the MoBio UltraClean-htp 96-wellSoil DNA Isolation Kit (Carlsbad, CA, USA) following the manu-facturer’s instructions, plus an additional purification step withAMPure beads (Agencourt) to further remove humic acids and otherPCR inhibitors. All DNA extractions were quantified spectropho-tometrically and diluted to a final concentration of 10 ng �l−1.

Amplification of the bacterial 16S rRNA genes was performedas described by Manter et al. (2010b). Pyrosequencing was per-formed under contract with Duke University’s IGSP SequencingCore Facility using a 454 Life Sciences GS FLX System with standardchemistry. All sequence read editing and processing was per-formed with Mothur Ver. 1.24 (Schloss et al., 2009) using thedefault settings unless otherwise noted. Briefly, sequence readswere (i) trimmed (bdiff = 0, pdiff = 0, qaverage = 25, maxambig = 0,maxhomop = 10); (ii) aligned to the bacterial-subset SILVA align-ment available at the Mothur website (http://www.mothur.org);(iii) filtered to remove vertical gaps; (iv) screened for chimeras withuchime; (v) classified using the Green Genes Database containing84,414 bacterial and archaeal sequences (http://www.mothur.org)and the naïve Baysian classifier (Wang et al., 2007) embeddedin Mothur, all sequences identified as chloroplast were removed;(vi) sequences were screened (optimize = minlength-end, crite-ria = 95) and filtered (vertical = T, trump=.) so that all sequencescovered the same genetic space; and (vii) all sequences were pre-clustered (diff = 2) to remove potential pyrosequencing noise andclustered (calc = onegap, coutends = F, method = nearest) into oper-ational taxonomic units (OTUs) (Huse et al., 2010). All measures ofalpha diversity were calculated using the index calculators embed-ded in Mothur.

In order to remove the effect of sample size on communitycomposition efforts, sub-samples of 2119 reads were randomlyselected from each soil sample. A subset of OTUs associated withthe Arabidopsis soil was selected as follows. First, the Arabidop-sis community was compared to the microbial communities foreach of the other two soils using the procedure of Audic andClaverie (1997). Those OTUs whose relative abundance was signifi-cantly higher (p < 0.05) in the Arabidopsis soil for both comparisonswere considered to be associated with the Arabidopsis soil. TheArabidopsis-associated OTUs were further compared to the Ara-bidopsis core microbiome recently reported in (Lundberg et al.,2012). For this comparison, taxonomic assignments (as outlinedabove) for each OTU were determined using only the representa-tive sequence of each OTU (as this is the reported data in Table ST3,Lundberg et al., 2012). After assignment, the number of OTUs (bothstudies), and cumulative relative abundance (present study only)for each of the 41 Arabidopsis-associated genera was calculated. Inaddition, because the two studies sequenced different regions ofthe 16S gene a direct comparison of the representative sequencescannot be used to identify common OTUs. Therefore, both datasets(present study and Lundberg et al., 2012) were individually alignedto the SILVA reference database (as outlined above), and any OTUsthat aligned (≥97%) to the same SILVA reference sequence wereconsidered a match between the two microbiomes for the samebacterial OTU.

3. Results

3.1. Plant performance under drought

Under full drought conditions and for both treatments (filteredand non-filtered slurries), statistically significant differences(p < 0.05) in substrate water content, plant biomass productionand mortality rate were not observed at the 12th day after the ces-sation of watering (Fig. 1A–C). However, the greatest increase wasobserved in biomass production for the plants treated with Ara-bidopsis non-filtered soil slurry (p = 0.11). All treatments showed asignificant reduction of soil water content over the period of timeunder full drought stress (Fig. S1). Although vermiculite is oftenused to increase soil water holding-capacity, the increased aera-tion may lead to increased water stress due to the more limitedcontact between root tips and the water-holding vermiculite

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Fig. 1. Arabidopsis drought stress response under different soil slurry conditions. (A)Relative water content of the soil, measured 12 days after the cessation of watering.The values represent the mean ± SE (n = 9). (B) Shoot dry weight, measured 18 daysafter the cessation of watering. Data represent the mean ± SE (n = 9). Dotted linerepresents the control, which received the slurry solution with no soil. (C) The dayof mortality was assessed daily after imposing the drought stress. Data represent themedian ± 95% CI (n = 9). Numbers above the bars are the p-values testing the effectof the soil slurries (vs. filtered controls), using the slice parameter in SAS 9.3.

particles (Verslues et al., 1998). Therefore, we suspected that thepotential beneficial microbial impact on plant growth may havebeen limited by a more severe drought stress in the full-droughtexperiment.

Under moderate drought conditions (substrate moisture main-tained at 40% of fully hydrated conditions), differences in plantbiomass production attributable to soil microbes became visibleand this effect was significant only for the Arabidopsis non-filteredsoil slurry, and not for both slurries obtained from the pine orcorn soils (Fig. 2). Under these conditions, no plant mortality wasobserved for any of the treatment combinations tested (data notshown).

Since a significant plant biomass enhancing effect was observedwith the Arabidopsis non-filtered soil slurry, which contains bothbiotic and edaphic factors, we compared the physico-chemicalproperties of the three soils. We observed that the Arabidopsis andpine soils had more NH4–N, NO3–N, total phosphorus and totalpotassium compared with the corn soil (Table 1). However, wedid not observe an increase in biomass of the plants treated withany of the three filtered soil slurries. These results suggest that the

increase in plant biomass in the Arabidopsis non-filtered slurry wasdue to a microbiome effect aside from the edaphic factors.

To explore whether soil microbes impacted plant drought stressresponse, we examined the expression of genes (ATDI21, DREB1ADREB2A and NCED3) considered as markers for drought stressresponse (Gosti et al., 1995; Liu et al., 1998; Iuchi et al., 2001;Sakuma et al., 2006). Plants execute complex signaling pathways,with the possibility of cross-talk, to respond abiotic stresses such asdrought, salinity and cold (Hirayama and Shinozaki, 2010). Due tothe complexity of the signaling pathway, we selected these genesspecifically to determine the early response of stress and whetherthe response was abscisic acid (ABA) dependent or independent.Expression of each of these marker genes was significantly lowerin the presence of microbes (from Arabidopsis, pine or corn soils)compared to a control which received only the nutrient solutionused to prepare the soil slurries (Fig. 3). Among soil sources, theArabidopsis soil slurry significantly reduced expression levels ofATDI21, DREB1A and DREB2A to a greater extent than soil slurriesderived from pine and corn soils (Fig. 3). These data further sup-port the hypothesis that soil microbes reduce plant drought stressresponse, and that this effect may be more pronounced for sym-patric plant-microbiome combinations (Arabidopsis paired with anArabidopsis soil microbiome vs. microbiomes from pine or cornsoil). NCED3 is a gene involved in ABA-dependent stress response(Iuchi et al., 2001). This gene was expressed at detectable levelsonly in plants from the control treatment (Fig. 3), suggesting thatall three soil microbiomes repressed expression of this gene and/orsignaling pathway.

3.2. Soil microbial community structure

We analyzed the microbial community structure of Arabidop-sis, pine and corn soils by pyrosequencing to determine whetherspecific microbial groups could be linked with changes in plantperformance under drought stress. A total of 24 different bacte-rial phyla were detected across the three soil microbiomes (Fig. 4).Phyla Actinobacteria and Proteobacteria accounted for more than50% of the community in each soil. Largely due to the remainingphyla, the Arabidopsis community exhibited higher Shannon’sDiversity and Evenness indices (1.92 and 0.693), as compared toeither the pine (1.66 and 0.545) or corn (1.74 and 0.582) soils. TheOTUs associated with the Arabidopsis soil originated from nine dif-ferent phyla (Table 2) and included: 6 belonging to Rhizobiales(3.45%), 8 belonging to Bacillus (3.40%), 6 belonging to Acidobac-teriaceae (3.30%), 3 belonging to Solirubrobacterales (3.26%), 7belonging to Actinomycetales (3.11%), and 6 belonging to Kte-donobacteria (2.50%).

Further, we compared the microbial community structure ofthe Arabidopsis soil (present study) with the core microbiome ofArabidopsis (Lundberg et al., 2012) to better determine the speci-ficity of the Arabidopsis sympatric soil OTUs identified in thisstudy. Pyrosequencing analysis of the three soil microbiomes usedin this study identified 84 bacterial OTUs (3% genetic distance)from 41 genera that were significantly higher in the sympatricArabidopsis soil, as compared to the two non-sympatric soils(Table 2). Furthermore, 33 of these genera are part of the coreArabidopsis microbiome (Lundberg et al., 2012), suggesting thatthey routinely associate with Arabidopsis plants and are not uniqueto our Arabidopsis soil. Among those, 14 OTUs are similar withthe OTUs enriched in the rhizosphere fraction of the core Ara-bidopsis microbiome which includes species of Micromonospora,Streptomyces, Bacillus, Hyphomicrobium, Rhizobium, Burkholderiaand Azohydromonas (Table 2). These 14 OTUs are also highly abun-dant in the Arabidopsis soil microbiome compared with the pineand corn soil microbiomes.

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Fig. 2. Response of the Arabidopsis plants under partial drought (40% of full-moisture conditions). Data show mean shoot fresh weight ± SE (n = 9). Photographs show arepresentative Arabidopsis plant for each soil slurry treatment. Numbers above the bars are the p-values testing the effect of the soil slurries (vs. filtered controls), using theslice parameter in SAS 9.3. Dark and gray bars represent filtered and non-filtered treatments respectively in a given soil.

4. Discussion

In this study we explored the influence of soil microbes ondrought stress response in Arabidopsis thaliana using a series ofexperiments. In studies of this kind, it is very difficult to iso-late and remove soil microbial communities without releasingunknown chemical contents or changing soil properties. There-fore, we devised a filtration procedure that removes most of thesoil microbial components. This method might also remove tracequantities of chemical compounds due to filter adhesion, but mostchemicals (i.e. minerals, metals, ions, secondary metabolites, andother unknown small components) should pass through the filter.In our studies, a significant increase in Arabidopsis biomass wasonly observed for the Arabidopsis non-filtered soil slurry and thiseffect was enhanced under partial drought.

Pyrosequencing data showed a higher abundance of poten-tial Plant Growth Promoting Rhizobacteria (PGPRs) correspondingthe genera Bacillus, Rhizobium and Burkholderia in Arabidopsis soilcompared with pine and corn soils. However, further studies arewarranted to identify the specific component(s) contributing tothis biomass increase under partial drought conditions. PGPRs havebeen shown to significantly increase the growth of plants under dif-ferent experimental conditions, through a variety of mechanisms

such as antagonism, nutrient solubilization, disease suppressive-ness and release of growth hormones (Vessey, 2003; Lugtenbergand Kamilova, 2009; Babalola, 2010). Therefore, the induction ofplant growth in our partial drought experiment could be due toeffects of PGPRs in the soil.

While the Arabidopsis-adapted microbiome enhanced Ara-bidopsis biomass production, it also led to earlier mortality underdrought stress. It is possible that larger plants may inherentlyface resource scarcity more quickly than smaller plants. That is tosay, growth promotion by microbes may increase susceptibility todrought stress simply by increasing plant size prior to drought con-ditions. However, in light of our gene expression data, we suggestthat it is more likely that the soil microbiome alters the ability ofthe plant to sense and respond to drought. It has been reportedthat genes related to auxin response were induced in plants uponcolonization by PGPRs, and that these genes play a role in vari-ous developmental processes such as lateral root development andhypocotyl elongation (Wang et al., 2005). Thus, prior knowledgesuggests that soil microbes can influence plant growth in ways thatcould impact sensitivity to drought. However, we are not aware ofany reports showing effects of whole microbiomes on the regula-tion of plant genes related to the sensing of abiotic stresses. We arenot excluding the possibility that these effects are attributable to

Table 1Chemical and physical properties of soils used in this study.

Arabidopsis Pine Corn

Organic matter (%) 6.1 8.9 2.1pH 7.0 5.4 6.3EC (mmohs/cm) 0.6 0.1 0.1Sodium absorption ratio (SAR) 0.9 0.4 0.2NH4-N (mg/kg) 13.7 10.5 6.7NO3-N (mg/kg) 9.4 6.0 3.7NH4-N: NO3-N ratio 1.5 1.8 1.8Total P (mg/kg) 562 505 280Total K (mg/kg) 3373 4699 239Textural class Sandy clay loam Sandy loam Loamy sand

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Fig. 3. Expression analyses, by semi-quantitative RT-PCR, of specific marker genes modulated under partial drought stress. The results are representative of three independentsamples.

specific members present in the microbial consortium, but addi-tional work is needed in this regard.

Signal transduction pathways and their regulation are criticalpoints in understanding plant response to drought stress, includ-ing how such responses may be impacted by other factors suchas soil microbes. Because we observed both enhanced growth and

Fig. 4. The relative abundance of the major bacterial phylogenetic groups in Ara-bidopsis (At), pine and corn soils, as revealed by pyrosequencing.

earlier mortality under drought conditions for plants treated withthe Arabidopsis soil slurry, we hypothesized that the Arabidopsissoil microbiome may have impaired a mechanism(s) of sensing orresponding to drought stress. Our gene expression analysis sup-ports this possibility.

Abscisic acid (ABA) has been proposed as a mediator betweenenvironmental stress (i.e. drought) and plant responses (Trewavasand Jones, 1991; Davies et al., 2002). We examined the gene expres-sion of NCED3, which is induced only upon drought stress (Iuchiet al., 2001) and is a key regulatory gene involved in the biosyn-thesis of ABA. Under moderate drought conditions, expression ofthis gene was only evident in the control, which received onlythe soil suspension solution (1X Hoagland’s) with no microbes.This suggests that adding soil microbes somehow prevents theinduction of the ABA-dependent drought stress response path-way. We also measured the expression of DREB1A and DREB2A(Dehydration Responsive Element Binding) genes which code fortranscription factors that improve stress tolerance by interactingwith a DRE/CRT cis-element present in the promoter region of var-ious abiotic stress-responsive genes (Lata and Prasad, 2011). Wealso analyzed the expression of ATDI21, a marker gene inducedupon drought stress (Gosti et al., 1995). Plants treated with all threesoil microbial communities reduced the accumulation of transcript

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Table 2Bacterial operational taxonomic units (OTUs) associated with the Arabidopsis soil.

Taxonomya OTUsb Relative abundance (%)c Arabidopsis cored

Arabid. Corn Pine All EC R

Acidobacteria; Acidobacteria; Acidobacteriales; Acidobacteriaceae; unclassified 5 3.11 1.42 0.52 12 0 0Acidobacteria; Solibacteres; Solibacterales; Solibacteraceae; Candidatus Solibacter 4 0.9 0 0 8 0 0Acidobacteria; unclassified; unclassified; unclassified; unclassified 2 0.52 0 0 2 0 0Actinobacteria; Actinobacteria; Actinomycetales; Geodermatophilaceae; Geodermatophilus 2 0.85 0.19 0.14 0 0 0Actinobacteria; Actinobacteria; Actinomycetales; Micromonosporaceae; Actinoplanes 1 0.19 0 0 4 3 1Actinobacteria; Actinobacteria; Actinomycetales; Micromonosporaceae; Micromonospora 1 0.42 0 0 0 0 0Actinobacteria; Actinobacteria; Actinomycetales; Mycobacteriaceae; Mycobacterium 3 1.98 0.47 0.24 3 2 3Actinobacteria; Actinobacteria; Actinomycetales; Pseudonocardiaceae; unclassified 1 0.28 0 0 0 0 0Actinobacteria; Actinobacteria; Actinomycetales; Streptomycetaceae; Streptomyces 1 0.19 0 0 35 30 4Actinobacteria; Actinobacteria; Actinomycetales; unclassified; unclassified 6 2.83 0 0.09 15 6 2Actinobacteria; Actinobacteria; MC47; unclassified; unclassified 5 2.55 0.05 0.61 16 0 0Actinobacteria; Actinobacteria; Solirubrobacterales; Patulibacteraceae; unclassified 1 0.61 0.28 0.05 2 1 0Actinobacteria; Actinobacteria; Solirubrobacterales; unclassified; unclassified 2 2.64 0.66 0.19 2 2 0Bacteroidetes; Sphingobacteria; Sphingobacteriales; Flexibacteraceae; Cytophaga 1 0.19 0 0 7 1 0Bacteroidetes; Sphingobacteria; Sphingobacteriales; Sphingobacteriaceae; unclassified 1 0.28 0 0 3 0 1Chloroflexi; Ktedonobacteria; unclassified; unclassified; unclassified 6 2.5 0 0 1 0 0Cyanobacteria; Oscillatoriophycideae; Oscillatoriales; Phormidiaceae; Phormidium 1 1.32 0 0 1 1 0Cyanobacteria; Synechococcophycideae; Pseudanabaenales; Pseudanabaenaceae; Leptolyngbya 1 2.27 0 0 1 1 0Firmicutes; Bacilli; Bacillales; Bacillaceae; Bacillus 8 3.4 0 0.05 14 10 4Firmicutes; Bacilli; Bacillales; Planococcaceae; Sporosarcina 2 0.66 0 0 0 0 0Firmicutes; Bacilli; Bacillales; unclassified; unclassified 2 0.42 0 0 0 0 0Gemmatimonadetes; Gemmatimonadetes; Gemmatimonadales; Gemmatimonadaceae; unclassified 2 0.38 0 0 17 0 0Proteobacteria; Alphaproteobacteria; Rhizobiales; Bradyrhizobiaceae; Balneimonas 1 0.19 0 0 1 0 0Proteobacteria; Alphaproteobacteria; Rhizobiales; Hyphomicrobiaceae; Hyphomicrobium 1 0.24 0 0 1 0 1Proteobacteria; Alphaproteobacteria; Rhizobiales; Hyphomicrobiaceae; Rhodoplanes 1 0.24 0 0 11 0 0Proteobacteria; Alphaproteobacteria; Rhizobiales; Phyllobacteriaceae; Aminobacter 1 3.16 0.76 0.47 0 0 0Proteobacteria; Alphaproteobacteria; Rhizobiales; Rhizobiaceae; Rhizobium 1 0.24 0 0 3 0 2Proteobacteria; Alphaproteobacteria; Rhizobiales; unclassified; unclassified 1 0.28 0 0 11 0 1Proteobacteria; Alphaproteobacteria; Rhodospirillales; Acetobacteraceae; Acidiphilium 2 0.42 0 0 0 0 0Proteobacteria; Alphaproteobacteria; Rhodospirillales; Acetobacteraceae; unclassified 4 1.37 0 0 0 0 0Proteobacteria; Alphaproteobacteria; Sphingomonadales; Sphingomonadaceae; unclassified 1 1.13 0.57 0.42 10 0 2Proteobacteria; Betaproteobacteria; Burkholderiales; Alcaligenaceae; Azohydromonas 1 0.28 0 0.05 10 0 4Proteobacteria; Betaproteobacteria; Burkholderiales; Burkholderiaceae; Burkholderia 1 0.85 0.05 0.09 7 0 2Proteobacteria; Betaproteobacteria; Burkholderiales; Oxalobacteraceae; Herbaspirillum 2 0.38 0 0 1 0 1Proteobacteria; Betaproteobacteria; Burkholderiales; Oxalobacteraceae; Massilia 1 0.71 0.19 0.05 6 0 2Proteobacteria; Deltaproteobacteria; Myxococcales; Cystobacteraceae; unclassified 1 0.71 0 0 1 0 0Proteobacteria; Deltaproteobacteria; Myxococcales; Haliangiaceae; unclassified 2 0.38 0 0 2 0 0Proteobacteria; Deltaproteobacteria; Myxococcales; Myxococcaceae; Myxococcus 1 0.42 0 0 0 0 0Proteobacteria; Gammaproteobacteria; Xanthomonadales; Xanthomonadaceae; unclassified 1 0.24 0 0 7 0 0TM7; TM7-1; unclassified; unclassified; unclassified 1 0.61 0 0.05 3 0 0unclassified; unclassified; unclassified; unclassified; unclassified 2 0.85 0 0 42 0 0Total 84 41.19 4.64 3.02 259 57 30

a Taxonomic assignments are based on the representative sequence from each OTU.b Number of OTUs (3%) assigned to the specified taxonomic group.c Relative abundances are the sum for all OTUs assigned to the taxonomic group.d Number of OTUs from the Arabidopsis core microbiome assigned to the specified taxonomic group. Assignments were made using all representative sequence, or only

the the endophyte-enriched (EC), or rhizosphere-enriched (R) sequences as reported in Table S3 (Lundberg et al., 2012).

levels of DREB1A, DREB2A and ATDI21 compared with the con-trol. However, the Arabidopsis soil microbes showed the strongestreduction in transcript expression levels.

In aggregate, these gene expression results suggest that thepresence of soil microbes tends to dampen drought stress response.Previous studies have demonstrated a reduction in the expressionlevels of plant stress response genes upon inoculation with partic-ular bacterial strains (Hontzeas et al., 2004; Stearns et al., 2012).In this work we have taken a different approach by investigat-ing impacts of whole microbial communities, leading to resultswhich suggest that sympatric associations between plants and soilmicrobes may amplify these microbial effects on the expression ofplant stress response genes.

Optimal plant responses to drought likely differ depending onboth the severity and duration of water limitation. For instance, ifdroughts are short-lived, plants may realize an advantage if sym-patric microbes dampen stress response systems such that theplant continues active growth. However, under extended drought,this interaction may reduce plant survival because of a failure toadjust strongly enough to survive over longer periods of water lim-itation. Thus, it is difficult to predict whether plant-microbiome

sympatric associations for modified drought stress response wouldbe advantageous. Sympatric associations between plants and soilmicrobes have recently been studied in the context of how plantsmodulate soil microbiomes (Broz et al., 2007; Broeckling et al.,2008; Badri and Vivanco, 2009; Sugiyama et al., 2010), but effectsof the sympatric microbiome on the plant have not been as wellexplored. Interestingly, a recent report gives an additional layerof complexity by considering that habitats prone to drought tendto support endosymbionts of rice plants that confer abiotic stressrelief (Redman et al., 2011). Similarly, wild barley plants in a verylocal population showed differences in the ability of the rhizo-sphere bacterial community to utilize ACC that correlated with thesusceptibility of the plants to drought stress as a result of microcli-mate (north vs. south facing slope) (Timmusk et al., 2011).

Next generation sequencing has opened up new frontiers insoil microbial ecology, allowing for the first time the possibility ofeffectively sampling the diversity of microbes, at sufficient depthand without the biases inherent in cultivation-based techniques.We characterized, by pyrosequencing, the microbial communi-ties present in the three soils used here. Because the Arabidopsissoil had the most pronounced effects, suggesting the possibility of

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sympatric associations between host plant and soil microbiome,we focused our analysis on identifying microbial taxa that wereenriched in the Arabidopsis soil relative to the other soils. A total of84 OTUs were significantly more abundant in the Arabidopsis soil.Although we did not directly test the ability of these microbial taxato influence drought stress response in Arabidopsis, these analysesprovide a starting point for future investigations.

Our results were consistent with other findings from studiesof plant–microbe interactions and of microbial natural history.Members of the phyla Actinobacteria and Proteobacteria have beenpreviously reported to help plants overcome abiotic stress (Mayaket al., 2004a,b; Cheng et al., 2007; Saravanakumar and Samiyappan,2007). Furthermore, bacteria isolated from the Atacama Desert,an extremely water-limited environment, were mainly species ofthe Actinobacteria and Firmicutes, with only a small number ofProteobacteria (Navarro-Gonzalez et al., 2003; Lester et al., 2007).Moreover many Cyanobacteria can grow under extreme conditionssuch as low water potential (Potts and Friedmann, 1981; Reed et al.,1986), although we are unaware of any studies documenting theirability to interact with plants or to influence plant drought responseor tolerance. It is important to note, however, that while particularfamilies or genera have been repeatedly highlighted for containingplant growth promoting strains, the traits that lead to plant growthpromotion are not necessarily shared among all members of thesetaxa. Thus the sequence-based summary of bacterial communitycomposition reported here should be followed up with additionalwork to test whether the observed beneficial effects can be assignedto any particular taxa.

At the same time, the robustness of our Arabidopsis-associatedmicrobiome identified in this study is supported by the significantoverlap with the recently reported and more extensive Arabidop-sis core microbiome (Lundberg et al., 2012). For instance, 14OTUs are similar with the OTUs enriched in the rhizosphere frac-tion of the core Arabidopsis microbiome (Lundberg et al., 2012)which includes species of Micromonospora, Streptomyces, Bacil-lus, Hyphomicrobium, Rhizobium, Burkholderia and Azohydromonas(Table 2). These 14 OTUs are also highly abundant in the Ara-bidopsis soil microbiome (this study) compared with the pine andcorn soil microbiomes. This comparative analysis suggests that thepotential microbes identified in the Arabidopsis soil microbiome(present study) are the result of sympatric association with the hostplant over an extended period of time. Moreover, the presence ofthese microbes at higher abundance in the Arabidopsis core micro-biome suggests that there is a close-linkage with the host plantbut not necessarily with the soil type; as the Lundberg et al. (2012)study used non-sympatric soil to grow the Arabidopsis plants undergreenhouse conditions for one generation.

As we have pointed out previously, there are difficulties associ-ated with studies involving whole microbial communities. Whilestudies of pairwise plant-microbe combinations are crucial formechanistic studies, the present work represents an important stepin our understanding of the depth and degree of soil microbial com-munity as a whole interacting with plants and influencing plantperformance and stress tolerance.

5. Conclusions

In summary, we have demonstrated that the Arabidopsis sym-patric soil microbiome appears to help plants by increasing biomasssignificantly under moderate drought stress, by dampening ofstress sensing. However, this effect was not significant under fulldrought conditions. It is possible that the Arabidopsis soil micro-biome could enhance the plant’s growth under drought stress toaccelerate development toward flowering before drought kills theplant. From an agricultural management perspective the use of

sympatric soil microbiomes could help plants deal with short-term drought stress such as by increasing the interval betweenirrigation events. However, further mechanistic studies are war-ranted to examine the interrelationship of sympatric associatedmicrobes with the host.

Acknowledgements

This research was supported by a grant from the National Sci-ence Foundation to JMV (MCB-0950857) and by a CooperativeAgreement with the USDA-ARS.

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