ORIGINAL ARTICLE

Impact of petroleum hydrocarbon contaminationon the indigenous soil microbial community

Simrita Cheema & Meeta Lavania & Banwari Lal

Received: 12 July 2013 /Accepted: 9 March 2014# Springer-Verlag Berlin Heidelberg and the University of Milan 2014

Abstract Changes in the microbial community structure inagricultural soils and soils contaminated with hydrocarbonswere evaluated using the culture-independent method of 16SrRNA gene sequence analysis. The bacterial composition wasmore diverse in the agricultural soil (AS) samples in terms ofnumber of species and Shannon diversity index [6.6 vs. 1.94for the hydrocarbon-contaminated soil (HCS)]. Twelveknown bacterial groups were identified in the AS:Proteobacteria (41 % of bacter ia l community) ,Actinobacteria (34 %), Acidobacteria (5 %), Firmicutes(4 %), Chlorof lexi (4 %), Bacteroidetes (3 %),Gemmatimonadetes, Planctomycetes, Verrucomicrobia,Armatimonadetes, Cyanobacteria, TM7 and Archaea (the lat-ter 7 each accounting for 1–2%) . In comparison, the clonallibrary from the HCS samples included members from onlyfive groups: Proteobacteria (85 %) and Bacteriodetes,Actinobacteria, Chloroflexi and Verrucomicrobia (the latterfour collectively accounting for 15 %). The familyEctothiorhodospiraceae was the most dominant family withinthe Proteobacteria isolated from the HCS. These microbes areknown to synthesize a number of biotechnologically usefulproducts, such as polyhydroxyalkanoates and ectoines, andtheir dominance in the sampled area suggests the possibility ofdiscovering better adapted novel genes of commercial

importance, especially since the site had high alkaline andsaline characteristics. Soils (arid, alpine and polar) which arenutrient and moisture limited are typically often dominated byActinobacteria that are well adapted to low-resource environ-ments and do not show major changes in community structureas a result of hydrocarbon contamination.

Keywords Diversity . High alkalinity .

Ectothiorhodospiraceae . Polyhydroxyalkanoates . Ectoines

Introduction

Microbes are an essential part of all life forms on Earth. Theycan live in extreme environments and possess adaptive capa-bilities that enable them to adjust to changes in living condi-tions. Many microorganisms have been used in industrial-scale processes for the production of antibiotics, preparationof food and beverages, leather industry, production ofbiofuels, such as ethanol, among others in which they carryout various chemical biotranformations. Microbial communi-ties have for billions of generations contributed towardstransforming the world around them. Their applications aretoo widespread to describe in detail, and they represent by farthe richest repertoire of molecular and chemical diversity innature (Kapur and Jain 2004).

The diversity of microorganisms has been explored acrossa wide range of environments, such as water, soils, the humanbody (Achtman and Wagner 2008), hydrocarbon-contaminated soils (Liang et al. 2011), the Arctic and deepsea vents (Stoeck et al. 2007). Among the various habitats, soilis considered to house the maximum number of microbes, andit has been estimated that 1 g of sediment may contain 1010

bacteria, which is the highest for any environment (Torsviket al. 1996). However, the cultivation efficiency of soil mi-crobes is only 0.3 % (Torsvik et al. 1996) due to limitations in

S. CheemaCentre for Bioresources and Biotechnology, TERI University, PlotNo.10, Institutional Area, Vasant Kunj, New Delhi 110070, India

S. Cheema :M. Lavania :B. LalMicrobial Biotechnology Division, TERI, India Habitat Centre,Lodhi Road, New Delhi 110003, India

B. Lal (*)Environmental and Industrial Biotechnology, TERI University,Darbari Seth Block, India Habitat Center, Lodhi Road, NewDelhi 110003, Indiae-mail: banwaril@teri.res.in

Ann MicrobiolDOI 10.1007/s13213-014-0868-1

traditional cultivation methods. This implies that most soilbacteria are difficult to isolate on laboratory media due tounknown culture conditions, insufficient growth nutrientsand the lack of cells in cultivable state. This drawback hasbeen largely overcome by culture-independent approaches(Handelsman 2004) which are currently being exploited at avery fast pace and have allowed researchers and scientists togain a better understanding of the number of microbialcommunities.

Soil microbial communities residing at sites contaminatedwith hydrocarbons are one of the most complex and diverseassemblages. Their roles and activities in these soils are thefocus of much interest (Liang et al. 2011). It is expected thatsuch information will result in the identification of manymicroorganisms which may represent a potential resourcefor various biotechnological products, bioenergy productionand novel biotransformations (Kalia et al. 2003). In addition,such studies will help to determine bacterial communities witha high tolerance for hydrocarbon contamination. Their phys-iological response and stronger biodegradation efficiency canultimately be exploited for developing economic bioremedia-tion technologies.

In the study reported here, we investigated a site contam-inated with hydrocarbons using a culture-independent ap-proach in order to gain insight into the microbial communitycomposition. Microbial diversity from a neighbouring uncon-taminated agricultural soil (AS) was also analysed to betterunderstand the effects of environmental conditions and soilcharacteristics on microbial diversity. Our results suggest thatthe phylogenetic diversity and distribution in thehydrocarbon-contaminated soil (HCS) was quite distinct anddifferent from that in the unpolluted AS. They also indicatesthat microorganisms differ with habitats, are less diverse incontaminated sites and are dominated by populations that arewell adapted to survive under these conditions.

Materials and methods

Sampling site

The heavy oil belt of Gujarat, India is 30 km long, with asurface area of about 45 km2. The majority shareholder is theOil & Natural Gas Corporation Ltd., and several exploratoryoil wells with an extensive pipeline network are located atvarious sites in this oil belt. The village of Kalol, located27 km east of Ahmadabad city (73°15′N/ 72°28′60E) alsofalls within this belt. It is characterized by a mean annualrainfall of 742 mm and maximum and minimum temperaturesranging between 45 °C and 4 °C, respectively. The farmersgrow mainly Pennisetum glaucum (L), Ricinus communis andBrassica juncea in an inter-cropping cycle. For the past 14years, the crops have been under organic management with

inputs of composted cow manure; there has also been notillage and no removal of crop residues during this same timeperiod. An oil spill occurred in April 2008 which resulted inone of the agricultural fields being contaminated with hydro-carbons. In our study, soil collected from this site was consid-ered as the HCS. Within the same area, we also collected soilsamples from uncontaminated AS.

In both the cases (HCS and AS), about 10-g samples of thesurface soil were collected at depths ranging from 0 to 10 afterthe top 3 cm of the soil surface was removed, in the rainyseason of July 2008. Ten samples collected from each sitewere randomly mixed, and subsamples were used for micro-bial community analysis. Soil samples were kept in polyeth-ylene whirl bags on ice and transported to the laboratory. Thesamples were stored at −80 °C until further analysis. Allefforts were made to avoid surface contamination.

Physiochemical analyses of the soil sample

Physiochemical analysis of the soil samples was performed asdescribed by Marinari et al. (2006). Total organic carbon(TOC) was determined by the dichromate oxidation method(Nelson and Sommers 1982). Soil total lead (Pb), copper,cobalt (Co), arsenic, cadmium, selenium and chromium (Cr)were analysed by digesting 0.1 g soil with HCLO4–HNO3–HF (Nautiyal et al. 2010). The digested solution was washedinto a flask, and deionized water was added to a fixed volume.The digested solutions were analysed with atomic absorptionspectroscopy (model-AA 300; Perkin Elmer, Waltham, MA)for heavy metals. Soil pH and electric conductivity weremeasured in 1:10 w/v aqueous solution using a pH meter(Thermo Fisher Scientific, Waltham, MA).

Extraction of total petroleum hydrocarbon from contaminatedsoil

Total petroleum hydrocarbon (TPH) was extracted in an equalratio of hexane and dichloromethane (1:1, each 100 ml) from10 g of HCS and AS using the Soxhlet method (Soxtherm;Gerardt GmbH, Königswinter, Germany). Extracts were driedat room temperature by evaporating the solvents under agentle nitrogen stream in the fume hood. After evaporationthe amount of residual TPH recovered was determined gravi-metrically (Mishra et al. 2001).

Analysis of TPH fractions by gas chromatography

Following gravimetric quantification, the residual TPH wasfractionated into alkane, aromatic, asphaltene and nitrogen–sulphur–oxygen fractions in a silica gel column (Mishra et al.2001). The TPH sample (200 mg) was dissolved in a mixtureof hexane, loaded onto a silica gel column and eluted withsolvents of different polarity. The alkane and aromatic

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fractions were eluted with 100 ml of hexane and dichloro-methane, respectively. Aliphatic and aromatic fractions wereanalysed by gas chromatography (GC-FID; 6890 series N;Agilent Technologies, Santa Clara, CA) using a flame ioniza-tion detector (FID) fitted with a DB5 column (length 30 m,inner diameter 0.25 mm- film thickness 0.25 μm). The oper-ating conditions of the GC system were: an oven temperatureprogrammed to increase from 55 °C for 1 min to 290 °C at5 °C/min over a period of 20 min; total run time of 68 min;injector port temperature of 250 °C; detector temperature of300 °C. Helium was used as the carrier gas at a flow rate of2 ml/min with a split ratio of 1/50. Individual compoundspresent in the alkane and aromatic fractions were determinedby comparing retention times with those of authentic stan-dards (Sigma Chemicals, St. Louis, MO) as described earlier(Lal and Khanna 1996).

Total community DNA extraction

Total microbial community DNA was extracted from soilsamples, following the removal of stones and plant roots,using the PowerMax® Soil DNA Isolation kit (Mo BioLaboratories, Solana Beach, CA) according to the manufac-turer’s protocol. The DNAwas quantified using the NanoDropLite Spectrophotometer (Thermo Fisher Scientific).

16S rRNA gene library construction

The community DNA extracted from the HCS was amplifiedfor the 16S rRNA gene using the universal bacterial primers27 F (5′-AGA GTT TGATCC TGG CTC AG-3′) and 1492R[5′-ACG G(CT)T ACC TTG TTA CGA CTT-3′). A PCRreaction mixture (50 μL) was prepared using the extractedcommunity DNA (50 ng/μL) and PCR reagents [1× PCRbuffer, 2.5 mM MgCl2, 0.5 μM of each primer, 0.2 mMdNTPs (Fermentas, Vilnius, Lithuania), 1.25 U Taq HotStart (Promega, Madison, WI)]. The PCR cycling conditionsconsisted of an initial denaturation step at 94 °C for 2 minfollowed by 30 cycles of denaturation at 94 °C for 30 s,annealing at 56 °C for 30 s and elongation at 72 °C for1 min , with a final extension of 2 min at 72 °C. The amplified16S rDNA product (about 1,500 bp) was confirmed by load-ing about 5 μL of the PCR product onto a 1 % agarose gel.The PCR product was purified with using Microcon 100 PCRcentrifugal filter device (Millipore, Billerica, MA) and wasligated into pGEM-T Easy vector (Promega) as per the man-ufacturer’s protocol. The ligated 16S rRNA was transformedinto Escherichia coli JM109 high-efficiency competent cellswhich were plated on LB plates supplemented with ampicillin(100 μg/mL), IPTG (100 mM) and X-Gal (34 μg/mL) andincubated overnight. About 150 clones were picked, arrayedinto 96-well plates and stored at −80 °C as glycerol stocks.

Sequencing

The template used for the sequencing of inserts was processedby heat lysis of the overnight-grown clones at 96 °C for10 min in a thermocycler (Eppendorf, Hamburg). About 96clones were randomly picked, and the 16S rDNA insert wasamplified with the primer set M13F (5′GTAAAACGACGGCCA G-3′) and M13R (5′-AGG AAA CAG CTATGA C-3′).The PCR mix consisted of 1× PCR buffer, 2.5 mM MgCl2,0.1 μM of each primer (M13F/M13R), 0.2 mM dNTPs(Fermentas) and 1.25 U Taq Hot Start (Promega). The PCRcycling conditions consisted of an initial denaturation step at94 °C for 3 min followed by 30 cycles of denaturation at 94 °Cfor 30 s, annealing at 60 °C for 30 s and elongation at 72 °C for90 s, followed by a final extension step of 3 min at 72 °C. The96 PCR reactions were purified using the QiagenMinElute 96UF PCR Purification kit (Qiagen, Venlo, the Netherlands).The amplified insert after purification was cycle sequencedusing the BigDye® Terminator v3.1 Cycle Sequencing kit(Applied Biosystems, Foster City, CA). The forward andreverse sequencing reactions were done in separate reactionsusing the M13F and M13R primers, respectively. A 10-μLreaction mixture was prepared consisting of 1 μL purifiedPCR product, 2 μL BigDye Ready Reaction Mix, 1 μL ofBigDye sequencing buffer and 1 μL of M13F / M13R(25 μM) primers. De-ionized water (5 μL) was added to afinal volume of 10 μL. The cycling conditions for the ampli-fication reaction included an initial denaturation step at 96 °Cfor 1 min followed by 25 cycles of denaturation at 96 °C for20 s, annealing at 56 °C for 20 s and elongation at 60 °C for4 min with a final extension step at 60 °C for 1 min. Thesequencing PCR reactions were purified using the Qiagen-DyeEx 96 kit. The elutes were dried using the DNASpeedVac-DNA 110 vacuum system for 30 min at mediumspeed (Thermo Fisher, Waltham, MA). The sequenced prod-uct was re-suspended in 20μLHi-Di Formamide (PE AppliedBiosystems, Foster City, CA) and transferred to sequencingvials for sequence analysis (ABI prism 310 genetic analyser;PE Applied Biosystems). The sequenced DNA was resolvedon ABI PRISMTM 310 genetic analyser (PE AppliedBiosystems). The DNA samples were sequenced with the longcapillaries (5–61 cm×50 μm). Electrophoresis was performedin 1× electrophoresis buffer with EDTA and performance-optimized polymer (POP6). The various parameters that wereset for the electrophoresis in the genetic analyser were tem-perature (50 °C), current (4 μA), voltage (12 kV) and argonion laser power (9.8 mW).

Phylogenetic analysis

The 16S rRNA sequences were checked for purity with theCheck–Chimera program (http://rdp.cme.msu.edu/).Sequences in certain cases were manually edited by using

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the BioEdit software version 7.0.5.3. Sequences weresubjected to a BLAST search with the NCBI database andClassifier tool of the Ribosomal database project II. Multiplesequence alignments were performed using CLUSTAL W,ver. 1.8 (Thompson et al. 1994). A phylogenetic tree wasconstructed with the evolutionary distances using theneighbour-joining method (Saitou and Nei 1987). Tree topol-ogies were evaluated by performing bootstrap analysis of1,000 data sets with the PHYLIP version 3.61 packages(Felsenstein 1989). The tree was generated with theTREEVIEW program (Page 1996).

Nucleotide sequence accession numbers

The 16S rRNA sequences of representative isolates from thisstudy were submitted to the NCBI Genbank Database withaccession numbers JN217142 through to JN217218 (HCS)and KC820818 through to KC820893 (AS).

Statistical analysis

Sample diversity richness based on 16S rRNA sequences wascalculated using the Shannon–Weaver index with the help ofMothur (Schloss et al. 2009), which is a comprehensivesoftware package for analysing community sequence data.The rarefaction curve was also calculated in Mothur by plot-ting the number of operational taxonomic units (OTUs) ob-served against the number of sequences sampled (Schlosset al. 2009).

Results and discussion

In the last three decades metagenomics as a tool for investi-gating microbial communities has gained momentum since itprovides access to the large gene pool of unculturable bacteriaand thereby to microorganisms which are missed due to theinherent limitations of conventional culturing methods(Handelsman 2004). To date, a number of bacterial commu-nities have been examined using this approach and hydrocar-bon contaminated sites have also been studied (Liang et al.2011). In our study bacterial diversity was investigated in twodifferent soil environments, a HCS and a neighbouring AS, bydetermining the phylotype richness and the distribution andsimilarity among the 16S rDNA clones investigated.

Characteristics of the sampling sites

Soils from the Kalol site (Gujarat) were loamy with a surfacetemperature of 28 °C. The pH of the HCS was alkaline (pH8.5) with a high salt content (6.4 %), and that of the AS wasalso alkaline (pH 7.8) with a low salt content (1.3 %). Theoccurrence of heavy metal contamination was also

determined. In the AS, all metals were below the detectionlimits; in the HCS, Pb (1,477 mg/kg), Co (997 mg/kg) and Cr(3,869 mg/kg) were present at significant levels (Table 1). TheAS and HCS also differed TOC (Table 1), with the AS havinga higher TOC (4.32 %) than the HCS (0.8 %). This differencewas likely due to no organic manure being applied to the HCSsince the oil spill in 2008 which made the field unfeasible foragricultural purposes. The AS showed negligible (residual60 mg) TPH per kilogram soil and was not characterized byany hydrocarbon signatures indicative of an uncontaminatedhealthy soil. In comparison, the crude oil concentration of theHCS was approximately 5,100 mg TPH/kg soil. The HCSincluded hydrocarbons belonging to all saturated alkanes(C14–C36) and aromatics (anthracene, fluoranthene, pyrene,benzo[a] anthracene, chrysene, benzo[b] fluoranthene,benzo[k] fluoranthene, dibenzo[a,h] anthraene), as shown inFig. 1.

Diversity analysis

Shannon’s diversity index varied remarkably across the twoenvironments, being 6.6 for the AS, which indicates an ex-tremely diverse and dynamic community structure (Köberlet al. 2011; Steven et al. 2013), and 1.94 for the HCS. Highconcentrations of TPH have been shown to have contrastingeffects on microbial diversity (Sutton et al. 2013). In our studythere was clearly a decrease in diversity in the HCS, mostlikely caused by the high selection pressures imposed by thehigh level of TPH contamination (5,100 mg/kg of soil). Allgroups of Proteobacteria respond positively to the influx ofhydrocarbon contaminants, and members of the classGammaproteobacteria are commonly predominant when sup-plemental nutrients (C:N:P) are provided. The concomitantpresence of heavymetals, such as Cr, Pb and Co, has also been

Table 1 Physico-chemical properties of soil sampled from the site con-taminated with hydrocarbons and an agricultural site at Kalol,Ahmedabad

Properties Hydrocarbon-contaminated soil

Agricultural soil

Texture Dark-brown,granular, loamy

Copper-brown,granular, loamy

pH 8.5 7.8

Total organic carbon 0.8 % 4.32 %

Heavy metals (mg/kg)

Pb 1477 ND (<5)

Co 997 ND (<5)

As ND (<10) ND (<10)

Cd ND (<5) ND (<5)

Cr 3869 ND (<5)

Se ND (<5) ND (<5)

ND, Not detected

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observed to decrease microbial diversity due to their deleteri-ous effects on susceptible microorganisms (Sheik et al. 2012).The combined effect of heavy metal and hydrocarbon con-tamination likely caused a reduction in microbial diversity inthe HCS, which is also highlighted by the rarefaction curves(Fig. 2). A comparison between the rarefaction curves fromboth sites shows that, at the phylum level, the number ofOTUs observed decreased and reached a plateau at 20 %distance for the HCS, suggesting that most of the diversity atthe phylum level had been detected. In contrast, for the AS,the number of phylotypes seemed to be increasing, indicatingthe possibility that many more unique phylotypes or speciescould be found.

Bacterial community structure

Among the two libraries, a total of 350 transformants wereobtained of which 192 clones were analysed further. A total of

77 (HCS) and 76 (AS) 16S rDNA clones were successfullysequenced and ultimately deposited in the GenBank databaseunder accession numbers JN217142–JN217218 andKC820818–KC82089, respectively. Sequences were subject-ed to BLAST searches as well as to the Ribosomal DatabaseProject II Classifier tool for determining the phylogeneticaffiliations of each of the clones. The microbial communityof the HCS site was characterized mainly by a single phy-lum—Proteobacteria (88 %). This phylum was also predom-inate in the AS sample, where 41 % of OTUs belonged toProteobacteria (Fig. 3a). However, within this phylum differ-ent trends were observed for the two soils. The AS siteincludedDelta Proteobacteria (3 %), which was not observedin the HCS. Almost all sequences (85 %) in the HCS wereaffiliated to Gamma Proteobacteria (Fig. 3b) whereas in theAS, Alpha Proteobacteria formed the dominant group (33 %).

The prevalence ofGamma Proteobacteria at such contam-inated sites (HCS) has also been observed in previous studies

Fig. 1 Gas chromatographs ofhydrocarbon components presentin contaminated soil. a Saturatedalkanes (C14–C36). Numberindicates chain length. bAromatic hydrocarbons

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(e.g. Stoffels et al. 1998). These bacteria have the capabilitiesof utilizing such contaminants for growth and therefore sur-vive easily. Heavy metals are usually present at sites contam-inated with hydrocarbons, and only those microbes whichhave the ability to tolerate both can survive. Specific adaptivemechanisms enable hydrocarbon-tolerant bacteria to surviveand grow in the presence of these toxic hydrocarbons, andthese generally involve either modification of the membraneand/or cell surface properties, changes in the overall energystatus and activation and/or induction of active transport sys-tems for extruding hydrocarbons (Lăzăroaie 2009). However,heavy metal contamination has been observed to lower mi-crobial biomass and activity, which in turn affects the decom-position of soil organic matter and its accumulation in soil (Shiet al. 2002) and explains why such sites typically show lessdiverse and more selected microbial communities.

Our comparison of microbial diversity in our samples re-vealed that the family Ectothiorhodospiraceae made up thelargest group of the HCS library. Ectothiorhodospiraceae arehalophilic and haloalkaliphilic, purple sulfur, phototrophicbacteria belonging to Gamma Proteobacteria which prefer togrow anaerobically under light conditions using reduced sul-phur compounds as electron donors (Tourova et al. 2007).

Fig. 2 Rarefaction curves of thebacterial 16S rRNA clonal libraryof the agricultural soil (AS; a) andhydrocarbon-contaminated soil(HCS; b) at the species (3 %difference, filled diamond), genus(5 % difference, open square),family/class (10 % difference, X)and phylum (20 % difference,shaded triangle) levels. OTUsOperational taxonomic units

Fig. 3 Distribution of cloned 16S rRNA sequences at the phylum levelfrom the AS (a) and the HCS (b)

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They are usually found in soils with high alkalinity and salin-ity. Singh et al. (2010) earlier described the occurrence of thesehaloalkalophilic bacteria in saline habitats of Gujarat and thebiotechnological applications of their enzymes (such as prote-ases), which are active at alkaline pH and high salt concentra-tions. Some of the members of this family are also known foraccumulating two useful products: polyhydroxyalkanoates(PHAs) and ectoines (Galinski and Herzog 1990; Zhanget al. 2004). Consequently, the HCS could represent a reservoirof a group of useful bacteria that can be exploited for theproduction of these valuable products. The survivability ofthese organisms in such an environment may be due to bettermetabolic adaptabilities which have evolved over time. It isparticularly noteworthy that these genes are involved in theprocessing of PHAs and ectoines as it suggests the probabilitythat these genes may possess properties that are unique andwhich have evolved for a better expression of enzymes thantheir counterparts belonging to other environments. The genusMethylonatrum formed the second largest subgroup withinGamma Proteobacteria. These bacteria also thrive inalkaliphic and hypersaline ecosystems, and its members havebeen previously detected from sediments of hypersaline chlo-ride–sulfate lakes in Altai, Russia (Sorokin et al. 2007). Thesebacteria can degrade the greenhouse gas methane and otherorganic pollutants (Sorokin et al. 2007).

T HCS and AS shared some similarities in terms of thepresence of Bacteroidetes (8 vs. 3 %, respectively),Actinobacteria (1 vs. 34 %), Chloroflexi (1 vs. 4 %),Verrucomicrobia (1 % each) and TM7 (1 vs. 2 %) but alsoshowed significant differences. The major decline in the dom-inance of Actinobacteria in AS and the shift to Proteobacteriadominance in HCS has also been observed in other studies(Sheik et al. 2012). This shift is likely due to Proteobacteriapossessing metal-tolerant genes and, therefore, they can easilysurvive in contaminated soils. High concentrations of metalsharm cells by displacing the enzyme metal ions, competingwith structurally related non-metals in cell reactions andblocking functional groups in the cell bio-molecules (Hetzeret al. 2006). Microbial survival in soils polluted with heavymetals depends on the intrinsic biochemical properties andphysiological and/or genetic adaptation mechanisms, includ-ing morphological, of the specific microbial species, as well asenvironmental modifications of metal speciation (Abou-Shanab et al. 2007). The few Actinobacteria observed in theHCS may be either those species which carry such resistancegenes and have been earlier reported to be involved in metalcycling (Kothe et al. 2010) or their presence was possiblyaffected by higher than normal soil moisture (Goodfellow andWilliams 1983).

Verrucomicrobia is a major phylogenetic group but is rep-resented by very few cultured isolates (Hedlund et al. 1997)These bacteria account for 1–10 % of the bacterial 16S rRNAin soils (Buckley and Schmidt 2003) and therefore were also

represented by just one clone each in our study. More speciescould have been found with greater sampling sizes, as indi-cated by the rarefaction curve. The optimum medium, inor-ganic salt content, temperature and growth factors present inthe AS promoted the sustainability of such a rich microbialcommunity. The widespread and ubiquitous distribution ofphyla may indicate their important role in plant–soilinteractions.

The AS soil was also characterized by additional phyloge-netic groups, although these were low in numbers—Archaea(2 %), Gemmatimonadetes (1 %), Acidobacteria (5 %),Firmicutes (4 %), Planctomycetes (1 %), Armatimonadetes(1 %) and Cyanobacteria (1 %). Acidobacteria, although anextremely prevalent bacteria in soil, was underrepresented atboth sites. In case of the HCS, their absence can be attributedto the higher alkalinity of the soil (Jones et al. 2009). At least15 taxonomic orders were present with a diversity index of6.67. Reports of such a high diversity index from agriculturalsoils with high nutritional levels are not known. The combineddata for the AS library represents a phylogenetically broadspectrum of microorganisms. Members of AlphaProteobacteria were the most dominant group, and membersof this group are frequently found in soils where they areknown to form symbiotic relationships with plants(Herschkovitz et al. 2005). Crop rotation involving Papaverglaucum (L), Ricinus communis and Brassica juncea is prac-ticed at the AS site, and these plants form associations withnitrogen-fixing bacteria such as Azotobacter chroococcum.Therefore, this type of farming system with the inclusion ofthese plants in the rotation amplifies the presence of the rootnodule bacteria, and with their degradation there is excess ofnitrogen availability in soil which stimulates microbialactivity.

Phylogenetic analysis

The phylogenetic analysis of the 16S rRNA sequences from theHCS site placed the members of the phyla GammaProteobacteria together (Fig. 4a), although there were somesequences which were placed within the GammaProteobacteria but as a clear distinct group (Fig. 4a). Theseconsisted of the sequences from phyla Alpha Proteobacteria,Verrucomicrobia, TM7 and Bacteroidetes. Most of the sequencesfrom Bacteroidetes, however, formed a separate group. OneOTU each belonging to Actinobacteria and Chloroflexi formeddistinct separate branches in the tree. TheGamma Proteobacteriamainly represented by Ectothiorhodospiraceae showed a highgenetic diversity as clearly reflected by the low bootstrapvalues (Fig. 4a). In addition to the Ectothiorhodospiraceae,the Gamma Proteobacteria included the subgroupMethylonatrum which were mostly closely associated witheach other, although some clones were also associated withinthe Ectothiorhodospiraceae cluster.

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The phylogenetic distribution of the cloned 16S rDNAsequences from the AS did not show a consistent branchingorder of the bacterial divisions which was representative of theHCS (Fig. 4b), although the topologies of two major divi-sions, Actinobacteria and Alpha Proteobacteria, were coher-ent. However, even within these divisions few sequences werephylogenetically interspersed into other groups. The mostnotable ones were a group of sequences belonging toActinobacteria (TERI-AS10, 13, 17, 19, 21, 20, 22, 24, 42,57, 69) which clustered separately and were not associatedwith the representative sequences obtained from the BLASTresults. The sequences are probably very unique and diverseand thus remained independent. The phylogeny ofAcidobacteria (TERI-AS55, 63, 66, 79), Firmicutes (TERI-AS16, 82, 84), Gamma Proteobacteria (TERI-AS2, 23, 52,80), Chloroflexi (TERI-AS44, 47, 56), Verrucomicrobia(TERI-AS59), Gemmatimonadetes (TERI-AS75),Planctomycetes (TERI-AS31) and TM7 (TERI-AS72) alsodid not agree, which reaffirms that sequences from this siteare highly mobile and varied. Sequences from DeltaProteobacteria (TER-AS36, 45), Bacteroidetes (TERI-AS77,78), Armatimonadetes (TERI-AS65), Cyanobacteria (TERI-AS68) and Archaea (TERI-AS73) were phylogenetically di-vided into distinct branches.

Even though this study is based on 16S rRNA gene se-quences and is limited in determining the functional profilesof only the isolated microbes, the results obtained can beuseful for constructing specific DNA primers and probes totarget bacterial groups of interest. Diversity profiles, especial-ly of agricultural soils, can help in improving soil quality forbetter productivity and management. It would also enable thedesign and development of better bioremediation strategieswhich would be targeted specifically towards these inherentmicroorganisms and therefore would be more effective. Thestudy of stressed sites can facilitate the identification of mi-crobial genera which have developed genes with superiorbiocatalytic properties which possibly would be of higherbiotechnological importance than existing ones. In the contextof the HCS site it would be especially beneficial for identify-ing novel PHAs and/or ectoines with a better adaptability toextreme conditions of alkalinity and salinity. The possibility ofdetecting those microorganisms which might have applica-tions in the field of pharmaceuticals, bioremediation or otherindustrial biosynthetic processes, and previously thought to benon-existent, not only speeds up the screening process but alsoprovides information on whether a sampling site is worthtargeting for further exploration or not. Fig. 4 (continued)

�Fig. 4 Phylogenetic tree based on 16S rRNA sequences of clonesobtained from the HCS (a) and AS (b). Bootstrap values (based on1,000 replication) are given on each node. Reference entries frompublic databases are given by accession numbers, and entries from thiswork are given as the clone number

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Acknowledgments The authors thank the Department of Biotechnolo-gy, Government of India for funding of this research and the Council ofScientific and Industrial Research, NewDelhi, for providing fellowship toSimrita Cheema.

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