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European Journal of Soil Biology 47 (2011) 77e87

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European Journal of Soil Biology

journal homepage: http : / /www.elsevier .com/locate/ejsobi

Review

A review of molecular methods to study the microbiota of soiland the mycosphere

J.D. van Elsas*, F.G.H. BoersmaDepartment of Microbial Ecology, CEES, University of Groningen, Kerklaan 30, 9750 RA Haren, Netherlands

a r t i c l e i n f o

Article history:Received 28 July 2010Received in revised form26 November 2010Accepted 30 November 2010Available online 15 December 2010Handling editor: Bryan Griffiths

Keywords:Molecular methodsSoil microbiotaMycosphere

* Corresponding author.E-mail address: j.d.van.elsas@rug.nl (J.D. van Elsas

1164-5563/$ e see front matter � 2010 Elsevier Massdoi:10.1016/j.ejsobi.2010.11.010

a b s t r a c t

The availability of novel and advanced molecular methods based on soil nucleic acids has revolutionizedour studies of the microbiota of soil. In particular, our understanding of the daunting diversity of soilmicrobes has grown to maturity, opening up a new box of challenging research questions aboutmicrobial functioning and interactions. We here review recent developments in, as well as the state-of-the-art of, the molecular methods applied to soil, and discuss a few salient cases in which they haveenhanced our understanding of the soil microbiota and its functioning. In particular, we place a focus onthe interface between soil fungal hyphae and the corresponding non-fungal-affected soil, i.e., themycosphere. This selective environment may reduce the diversity of its inhabitants, allowing animproved picture of their ecology and functioning via molecular techniques. We present arguments forthe contention that, to investigate testable hypotheses, a polyphasic approach is needed, in which workon the basis of molecular approaches such as metagenomics and metatranscriptomics is coupled to thatbased on culturable organisms. Thus, advances in our understanding of local functioning and adaptationof bacterial mycosphere inhabitants will be fostered by combined metagenomics/metatranscriptomicsand cultivation-based approaches.

� 2010 Elsevier Masson SAS. All rights reserved.

1. Introduction

The analysis of microbial populations in natural habitats such assoil is one of the cornerstones of current research on the func-tioning of natural ecosystems. In traditional soil microbiologicalapproaches, data on soil microorganisms have been obtained byanalyzing material derived from microbial growth, i.e., cells inliquid cultures or colonies obtained by plating. Methods derivedfrom microbiology, cellular biochemistry, molecular biology (DNA-or RNA-based) and physiology have traditionally been used withsuch material. However, such methods have often met with stronglimitations, the reason being that only a small fraction of themicrobiota in soil can be accessed on the basis of cultivation. Thisphenomenon has been coined the Great Plate Count Anomaly [1].Researchers thus soon realized that the only sensible way tounderstand the complex soil microbial community was by devel-oping direct molecular assessments, for which pre-extraction ofcellular macromolecules like DNA and/or RNAwas a prerequisite. Inthe light of the astounding development of analytical methods inmolecular biology ever since the 1980-ies, exciting opportunities

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for analyses were offered if DNA and/or ribosomal or messengerRNA could be efficiently extracted from soil and subsequentlyanalyzed [2,3]. The molecularly-based methods specifically enableto produce “snapshots” of the molecular make-up of wholecomplex soil microbial communities, as well as of specific micro-organisms and genes therein. Although the term had not beencoined at that time, this early stage of soil molecular microbiologymay be rightly called the era of early metagenomics or “Proto-metagenomics”. The Molecular Microbial Ecology Manual (editionsI and II) bears testimony of the ultrafast developments in this areaover the past one to one-and-a-half decade [4,5].

A now almost traditional way of performing a molecularassessment of soil microbial communities following cultivationconsists of colony hybridization, using suitable probes as proxies forthe identification of the colonies e grown on isolation plates e thatare examined. Early analyses of colony material have been based onthis method [6], which allowed the investigators to pinpoint thepresence of particular genes in their cultured organisms. Themethod was later followed by polymerase chain reaction (PCR)-based assessments of colony material (colony PCR) directly fromisolation plates. Such cultivation-based molecular analyses allowedthe description of the population dynamics of specific culturablebacteria in soil settings. However, they were inherently limited intheir scope due to the general unculturability of a majority of soil

J.D. van Elsas, F.G.H. Boersma / European Journal of Soil Biology 47 (2011) 77e8778

bacteria. On the other hand, the examination of organisms that areable to give a growth response is still highly crucial in many studies,and hence such analyses should be encouraged. In contrast, manycurrent assessments of soil microbial communities are based on theisolation of microbial DNA or RNA directly from soil samples [7e9].Following the isolation and purification of soil DNA/RNA, an array ofanalytical techniques is available to provide answers to the scien-tific question that is being posed. Such approaches should go hand-in-hand with the aforementioned cultivation-based approaches ina polyphasic approach, as it often pays off to have bacterial isolateshandy next to direct molecular data.

This review will examine the molecular methods that arecurrently applied to soil and mycosphere systems. We will firstprovide an outline of the peculiarities of the mycosphere asa particular microhabitat in the soil, after which we will examinecurrent procedures for the extraction and processing of microbialnucleic acids from soil. Then, relevant analytical procedures areexamined with respect to their power to detect, fingerprint,sequence and quantify (targeted parts of) the microbiota. Inparticular, advanced methods for the analysis of the diversity andcommunity structures of soil-, plant- and mycosphere-associatedbacterial communities are the focus [10,11]. Finally, we address theins and outs of the application of molecular methods tothe mycosphere, as a specific microhabitat compartment of soil.Table 1 gives an outline of the methods and their intricacies.

2. Soil versus the mycosphere e issues of microhabitatsampling

Bulk soil, although heterogeneous in nature, is often readilysampled, and accepted sampling procedures based on statisticalconsiderations are in place. However, common sample sizes formolecular assessments, which are often less than 1 g, still seem tolimit the scope of the investigator to the (micro)habitat that isactually accessed. In contrast, the mycosphere poses a numbers ofdifferent problems to sampling. The mycosphere can be defined asthe interface between soil fungal mycelium and the (bulk) soilenvironment [12]. It encompasses the soil zone around thehyphae of a range of soil fungi, e.g., soil ectomycorrhizae, arbuscularmycorrhizae and/or saprotrophic fungi [13]. Next to themycosphere, which is per definition extraradical, the mycorrhizo-sphere e which includes influences from plant roots e can berecognized [11,14,15]. In the specific case of mushroom-formingecotomycorrhizal fungi, the mycosphere has been defined as thenarrow zone of soil around the bundled hyphae (hereafter calledthe “bundle”) at the base of the mushroom [11,16]. The mycosphereserves as a habitat for diverse bacteria that, specifically orstochastically, inhabit this interface. The interface is influenced bycompounds that become available from the fungal mycelium viadirect secretion of organic acids like oxalic acid or trehalose [15] orcompounds like glycerol [17] or via dying fungal cells. The myco-sphere does not a priori pose major problems for DNA/RNAextractions using common procedures. However, a main challengein studying this interface environment by molecular and/or culti-vation means lies in the ability of the sampling procedure to dissectout the relevant portion of the soil that is impacted by fungalhyphae. As the hyphae, either underneath fungal fruiting bodies ordirectly in the soil hyphal network, are often small and fragile,sampling them in a representative manner and including theproper amount of surrounding mycosphere soil, is actually quitedifficult. Thus, sampling of the mycosphere has not turned intoa routine practice yet, and it is therefore not well-defined. Thisstands in sharp contrast to sampling of the rhizosphere, which hasbeen standardized across laboratories. The difficulty is also reflec-ted in the definition of the mycosphere, which may read as “the soil

compartment which is under the influence of the hyphae of thefungus studied”. This definition does not clearly define the exactdimensions of the soil compartment to be sampled. Thus, tosensibly address the microbial communities of the mycosphere ina comparative fashion, it is extremely important to consider andapply standardized sampling procedures of the mycosphere.A sensible approach developed in our laboratory [16] sampled themushroom foot part, shaking the loose soil from the foot, thusobtaining a shallow layer of soil surrounding the mushroom foot(Fig. 1). The bacteria inhabiting this area in soil were assumed tobest represent the mycosphere microbiota. Thus, molecular anal-yses applied specifically to such samples in comparison to those ofthe bulk soil will shed light on the specific molecular features(phylogenetically and/or functionally) of mycosphere inhabitants.

3. Molecular analyses of the soil and mycospheremicrobiota e soil nucleic acids as the basis

3.1. Nucleic acid extraction, with emphasis on soil DNA

The vast majority of current molecular analyses from soil ispreceded by direct soil nucleic acid extractions [5]. Methods thatallow access to soil nucleic acids originate from the eighties, andthe reader is referred to some of the relevant pioneering studies[2,7,9,18]. Such methods commonly yielded both DNA and RNAreleased from soil microbial communities. Since their inception,there have been fast developments in these methods, culminatingin the fact that current nucleic acid extraction protocols are almostall (commercial) kit-based [8]. However, for specific purposes,several non-kit based protocols are still in use [8]. Another key issueis that most (but not all) analyses have commonly targeted soil DNAinstead of RNA, the reason being the greater stability of DNA uponextraction. However, RNA-based protocols are in use in ribosomalmarker-based studies (in the light of the greater number of ribo-somes than chromosomes per cell), and they are obviously indis-pensable in studies on the transcriptome, focussing on messengerRNA (for instance, [19]). The commercial extraction kits for DNA,several of them finetuned to soil DNA, all guarantee robustnesswith respect to the quantity and quality of the DNA that is obtained.However, a fact of soil scientific life is that for each “new” soil, theperformance of a particular extraction kit needs to be tested andvalidated [5,8]. Furthermore, it is imminent that, per scientificstudy, the same standardized extraction protocol is used, as eachprotocol will introduce its own biases with respect to quality andquantity of the extracted DNA [8,20,21].

Key issues in soil nucleic acid extraction are the efficiencies ofthe release of microbial cells from soil particles and the subsequentlysis of the former. Ideally, all cells in the sample are released andsubsequently lysed in one go, however this has been suggested tobe nearly impossible due to inherent problems of incompletedesorption of cells from soil particles, their ready readsorption and,finally, incomplete and biased cell lyses. In the light of the diversityof the soil microbiota and the impossibility to have a “magic agent”that captures and lyses all cells in a given sample, the key initialdesorption and lysis steps are inevitably prone to biases. It followsthat, in any study on the soil microbiota, a particular “window” atthe true extant diversity in the soil habitat is obtained. This windowis limited and biased per definition. Therefore, rigorous standardi-zation is required in comparative work in soil, to keep the putativebiases similar across samples or treatments. In this respect, it isimportant to recognize the difference between, on the one hand,the physical (e.g., bead beating based) and, on the other hand, theenzymatic (soft) cell lysis methods [2,7,9]. Bead beating may result,following break-up of the cells, in enhanced shearing of the DNA ofthose cells with the most fragile envelopes (those that first yield

Table 1An overview of methods suitable for assessments of bacteria in soil and the mycosphere. Special emphasis is placed on both the promise and the potential caveats of these methods.

Method Reproducibility Interpretation of results Advantages Disadvantages Major pitfalls Remarks

Cultivation(plating)

Medium Limited information on in situactive populations due to GreatPlate Count Anomaly

Allows to further analyze coloniesincluding metabolic characteristicsor whole genome sequence

Low resolution, lacksrepresentation.Morphotypes hardto distinguish.

Only culturablemicroorganismsfound (only 1%of community).

Cultivation-based analyseskey support formolecularly-based observations

Soil nucleic acid extraction High Snapshot of extant microbiota inthe form of information-carryingmolecules

Easy access to genes of extant soilmicrobial community

Prone to incompleteand biased sampling

Chemical integrity andpurity of soil DNA maylimit analyses

Nucleic acids as the basis of allmolecular work: biases needto be reduced

PCR/qPCR High Proxies of organisms or genesamplified and/or quantified

Routine techniques of high sensitivity;allow detection and/or quantification

Several PCR biases andartifacts, includinginhibition

Only species >0.1e1%abundance are visible

Key method for moleculardetection from soil

Fingerprintings (DGGE, TGGE,T-RFLP, SSCP, RISA, LH-PCR)

-phylogenetical-functional

High Snapshot views of (dominant)microbial diversity andcommunity make-up,different sensitivity levels

Easy comparisons between samples,possibility of obtaining differentfingerprints from same sample

Only top-1000 of targetcommunity is accessed.

Several pitfalls due tonature of separationtechniques. DGGEdiscussed in text

DGGE has turned into a routinefingerprinting method. Care tobe taken with the interpretationsdue to biases

Clone libraries Medium Accounts of dominant sequencetypes in the community

Easy census of target genesin community; allows diversityestimates

Laborious preparationof sample

Pitfalls due tocloning bias

Nice but limited overview oftarget gene/organism diversity

Stable isotopeprobing and BrdU

High Direct information on incorporationof label into communitymembers: highlightsactive bacteria

Gives information on the activecommunity. Relation betweenstructure and functioncan be elucidated

Problems of opportunistsblurring the data

Relies on activity ofmicroorganisms,which can be very low

Widely appreciated method todescribe in situ activities

Microarrays Medium Parallel information on diversity,at phylogenetic or functional levels

Currently very high throughput, directinformation on sequences. Sensitive

Only chipped genesare found

Problems due tocross-hybridizationswith low-homologysequences

Allows high-throughput analysesacross habitats

High-throughput sequencing:-metagenome-metatranscriptome

Medium Large amounts of information on totaland active members of the communityat sequence level

All-in-once analysis in high-throughput.High potential for comparative studies

Methods are error-prone! Wrong interpretationsdue to artifacts/errors

Method of choice in manystudies. Again, caution withinterpretation of data needed

Reproducibility: divided in three classes: high (average SD below 10%), medium (average SD 10e25%) and high (average SD > 25%).

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Fig. 1. An overview of methods that are recommended to study the diversity and function of bacterial inhabitants of the mycosphere. The combination of cultivation-independentwith cultivation-dependent methods is predicted to enable great advances in our understanding of the system.

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free DNA). On the other hand, enzymatic lysis may not affect thosebacteria that are resistant to too soft lysis, and these will thusescape detection. In both cases, substantial biases are introduced inthe analyses. The type of desorption and lysis thus determines ourultimate view of the microbial community in the sample [8,22]. Itseems mandatory that attempts are made to optimize cell lysis inaccordance with the soil type and the bacterial taxon that is tar-geted. Furthermore, it should be recognized that, in different soils,DNA/RNA extraction methods will most likely work differently. Forinstance, the nucleic acids that are liberated may bind differently tosoil particles (clay and organic matter) in soils of different textureor mineral composition. Comparison of the microbiota in differentsoil types may thus be hampered by this variable DNA extractionefficiency. On the positive side, a reassuring degree of commonalitywas found between bacterial communities in soils of similartexture [23], which supported the contention that, across soils, ina grossly similar extraction background, similar types of potentialbiases will be encountered.

Soil nucleic acid extraction (often consisting of processing a soilsample, in several steps, up to the so-called crude lysate) iscommonly followed by one or more purification steps, as the crudeextract often still contains a substantial amount of compounds likehumic or fulvic acids, which hamper subsequent analyticalmethods that require PCR or labelling for hybridization. Therequired purification steps may incur losses of material, whichshould be minimized [24]. Ideally, purification steps are harmo-nized across samples, as comparisons based on data fromDNA extracts that underwent different purification protocolsmay be scientifically unwarranted in the light of possible biasesbetween these.

In most laboratories, the nucleic acid extraction protocols ofchoice are currently based on just a few commercial kits, e.g., thoseproduced under the names “Ultraclean” or “Powersoil” soil DNAextraction kits (MoBio, USA) and/or the Fast DNA Spin kit for soil(Bio101, USA). Combined with so-called Wizard (Promega, USA)resin-based DNA purification steps, commercial extraction kits, inparticular Powersoil, have been found to reproducibly yield PCR-amplifiable DNA from a variety of soils [8]. This has included sandy,clayey as well as organic-matter-rich soils. Representative DNA ofadequate purity and reasonably high molecular weight hasconsistently been obtained, which was suitable for subsequent PCRamplification analysis. However, a note of caution should be givenhere, as the aforementioned biases with respect to incompletenessof sampling of the extant nucleic acid diversity have not been(completely) solved. This implies that investigators applying directsoil nucleic acid extraction methods accept the view that theirdepiction of the soil microbial community is, by nature, incompleteand biased. On the other hand, a critical and comparative use ofsoil-extracted nucleic acids does provide the investigator witha very powerful data source, allowing him/her to directly picture, ina snapshot approach, themicrobial communities that abound in thesoil system of study, e.g., the mycosphere.

3.2. Molecular analyses of the soil microbiota e pioneeringstudies using hybridization

Early pioneering approaches set out to directly analyze micro-bial community nucleic acids (mainly DNA) extracted from soil, thepurpose being to obtain an overall view of the soil microbialcommunity diversity and make-up. Thus, soil DNA samples can be

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characterized in terms of their reannealing [18] and/or hybridiza-tion behavior [25]. The first criterion, i.e., the rate of reannealing ofmolten soil DNA, has been taken as characteristic for the level ofcomplexity (diversity) of the microbial communities under study,the premise being that the more complex themicrobial communityis, the lower the rate of reannealing of completely molten soil DNAwill be [18]. The second criterion (hybridization) has enabledinvestigators to assess the levels of commonality between soilecosystems, or even the prevalence of particular genes of interest inthe community [26]. However, a major problem often encounteredwith hybridization analyses performed directly on environmentalDNA extracts is their general lack of sensitivity, which limits theseanalyses to populations of cells or genes that occur in relativelyhigh numbers in the environmental samples [27]. Hence, furtherprocessing steps that offer increased analytical power (with respectto the analysis of microbial community make-up) are required,being PCR performed on environmental nucleic acids the obviouschoice.

3.3. PCR underlies many nucleic acid based analyticalapproaches

3.3.1. PCR as the basis for highly-sensitive analytical approachesto the soil microbiota

Amajor step forward in the study of the soil microbiota via DNA(and/or RNA) has been the development of direct PCR amplificationof target genes [28e30]. Such target genes include a phylogeneti-cally-tuned marker such as the 16S ribosomal RNA (rRNA) gene orthe rpoB gene, or functional gene markers like amoA (encodingammonia monooxygenase, a key enzyme in the oxidation ofammonia) or nifH (encoding nitrogenase reductase, a key enzymein nitrogen fixation). Using PCR followed by cloning/sequencing orfingerprinting approaches, information on the extant sequences ofthe gene of choice can thus be obtained from soil nucleic acids. Ina seminal paper in which PCR amplification of 16S rRNA genes wasused following by cloning and sequencing, Liesack and Stack-ebrandt [31] were the first to describe a totally novel bacterialphylum, denoted the Planctomycetales, from soil. Ribosomal RNAgene-based PCR analyses of soil and other environmental DNAshave, in many later studies, been primordial in the discovery ofa large number of novel bacterial radiations, and this process is stillongoing [32]. Some of the novel phyla, e.g., TM7, are withoutcultured representatives to date, although microcultivation tech-niques have been partially successful [33,34]. In a similar fashion,PCR amplification of functional genes has allowed a depiction of thediversities of such genes.

PCR can be based on soil DNA or RNA, the latter following priorreverse transcription (yielding cDNA). The method is based on thecyclic enzymatic extension of a particular gene region (usingtemperature-driven cycles of denaturing and annealing), with twoprimers that anneal at the opposite ends of the template. Thisresults in the generation of numerous copies of the region spannedby the two primers. Given the high denaturing temperature (often94 �C), the DNA polymerase used in PCR has to be resistant to hightemperature. A range of thermally-stable DNA polymerases arecurrently in use, all with their specificities in respect of reactionfidelity, proofreading activity and thermal stability. Special atten-tion to the fidelity and consistency of amplification offered by suchenzymes is required, as PCR error levels differ. PCR based on soilnucleic acids has turned into a basic step in soil molecular analyses,like the sequencing of inserts in so-called clone libraries and/ormolecular fingerprinting techniques such as DGGE or T-RFLP.A recent study illustrating this, revealed, on the basis of 16S rRNAgene-based PCR applied to DNA from the mycosphere versus cor-responding bulk soil, that selected bacterial (sphingomonad)

communities were quite different in these two contrasting envi-ronments [35]. Although many studies use prior soil nucleic acidbased PCR, themethodhas a number of potential biases,which needstrong consideration. First, PCR on the basis of so-called universalbacterial primers that target (part of) a common gene like the rRNAgene will not amplify all extant bacterial diversity simply becauseprimers used may miss a considerable part of the community [36].Second, following PCR, the perceived diversity is prone to so-calleddifferential amplification, which means that particular targetsamplify at higher rate than other ones. Third, the same PCR mayyield hybrid molecules called chimeras, which result from so-called“jumping PCR”. Such chimeras need to be removed e using forinstance, the web-based programme CHECK_CHIMERA e from theamplicons prior to further analyses, which is possible oncesequences are known. Finally, as indicated, only targets that aredominant in the sample will be amplified, and hence PCR is biasedagainst the so-called “rare biosphere”. This latter problem canactually be circumvented by using group-specific primers, whichallowamplification of DNA from low-abundance organisms. For thispurpose, primer sets e often consisting of nested or semi-nestedsystems e that target bacteria at the group level (e.g., the a, b, g-proteobacteria or bacilli) have been developed. Alternatively,primer sets targeting specific taxa like the pseudomonads, meth-ylobacteria and sphingomonads have been concocted and success-fully applied [37e41]. These group-specific approaches have oftenprovided greater insights in the ecology (dynamics) of the targetgroups, as they reduce the complexity of the target community.

Given the fact that the 16S rRNA genes may occur in multiplecopies per genome, alternative single-copy markers, like rpoS[42,43], gyrB [44] and recA [43] have been sought. So far, the use ofthese genes appears as a promising approach, as the poly-morphisms within them may well reflect evolutionary history andalso contemporary diversity across the members of a targetedcommunity [45]. However, the limited amount of sequenceinformation of these genes in the database stands in sharpcontrast to the enormous number of 16S rRNA gene sequencesthat are present. This limitation for the alternative markershampers sequence analysis and primer design. Naturally,researchers will provide increasingly more sequence data to thedatabases, enhancing sequence resolution. Conversely, it has beenshown that, in particular for the pseudomonads, the resolvingpower of the 16S rRNA gene is rather low. That is, pseudomonadsharboring very similar 16S rRNA genes may have quite differentecological roles and hence differ strongly in particular accessorygenes elsewhere on the genome. Recent work of Costa et al. [46],which was based on the use of the global regulator gacA as themarker to separate the pseudomonads, revealed that this markergene gave a significantly higher resolution than the 16SrRNA gene.

3.3.2. Quantitative PCR (qPCR)PCR of soil DNA can be used in a quantitative manner using a so-

called Taqman or “real-time” approach [47]. The principle of thismethod lies in the generation of a fluorescent and detectable signalby exonuclease activity of the polymerase. Signal is produced ateach cycle of the PCR reaction. Sensitive instruments have beendeveloped that allow the real-time detection of the signalproduced. When it passes a certain threshold level, the signal istransformed into predicted target gene numbers on the basis ofa pre-established calibration line with standard target DNA. qPCR iscurrently widely applied to soil-extracted DNA, allowing thequantification of numbers of target genes such as 16S rRNA genes(to quantify soil bacteria) or of functional genes like amoA or nifH.Although successfully used in many soil studies (e.g., [30]), qPCR isplagued by the very same biases as PCR based on soil DNA extracts;

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it provides an inherently biased picture of target gene abundanceand obviously does not detect any gene of the same function withaberrant sequence. However, qPCR may be well employed at themicrohabitat/mycosphere level to assess to what extent localconditions affect gene and gene expression levels. Thus, it may bepossible to more precisely map microbial diversity and function tosoil/mycosphere space.

3.4. Commonly used molecular analytical approaches

3.4.1. Molecular fingerprinting techniquesFollowing PCR of either the 16S rRNA gene or any phylogenetic

or functional gene of choice, analysis of the amplified targetsequences is needed to yield the data on themicrobial communitiesthat are sought. These further analysis can proceed via e.g.,restriction fragment length polymorphism analysis (PCR-RFLP),which yields relatively simple community fingerprints that can beused for comparative purposes. Direct hybridization of the ampli-cons to a specific probe using a dot blot or Southern blot approach isanother option, yielding information about the presence of regionsof homology to the probe. Alternatively, cloning into a library fol-lowed by sequencing of selected library clones can be used,providing information about the diversity and nature of thesequences that are targeted. Over the last decade, PCR-basedmolecular fingerprinting techniques have superseeded most otherpost-PCR analytical methods that allow insight into soil microbialdiversity and community make-up. The advantage of thesemethods is that they allow a direct comparative overview of thecomposition and diversity of the (dominant) soil microbiota tar-geted. A range of molecular fingerprinting methods based on PCR-generated amplicons, such as denaturing gradient gel electropho-resis (DGGE) [48], temperature gradient gel electrophoresis (TGGE)[40,48], terminal restriction fragment length polymorphism(T-RFLP) [49], single-strand conformational polymorphism (SSCP)[50], ribosomal internal spacer analysis (RISA) [51] and lengthheterogeneity-PCR (LH-PCR) [52] have emerged. All of thesemethods enable the direct fingerprinting of soil microbialcommunities at different levels of resolution, and among them,DGGE of PCR amplicons has been most widely accepted. In the lightof the PCR biases as discussed above, the methods are clearlylimited to the dominant members (the so-called top-1000) of themicrobial community that is targeted. Hence, without applying anykind of deliberate “pre-bias”, the method will not access organismsof the rare biosphere of soil. Another observation, and a matter ofcaution, is that all the soil DNA-based applications will detect bothviable and non-viable (or even dead) populations of cells. Thesetwo groups are hardly distinguishable without performing addi-tional assessments, such as analyzing cell viability in a direct viablecount assay [53].

To assist or finetune the direct nucleic acid based molecularfingerprinting methods, incorporation of label (e.g., 13C in substratethat can be consumed) prior to soil sampling (e.g., bromodeox-yuridine [BrdU] or stable isotope prelabelling of cells, see below)provides an emerging very promising complementary approach.The methods allows the pinpointing, in a microbial community, ofthose organisms that are actively involved in a particular ecosystemtask, e.g. the incorporation of BrdU under certain conditions [54] orthe transformation of the compound carrying the label [55]. Giventhe fact that DGGE is the most frequently used technique in manysoil research laboratories, this method will be described in moredepth in the following section.

3.4.2. PCR-DGGEIn PCR-based DGGE, as well as TGGE, similar-sized amplicons

generated by PCR are separated on the basis of differences in their

nucleotide sequences. This is achieved on polyacrylamide gels withdenaturing or temperature gradients, respectively for DGGE andTGGE. The techniques were originally developed for mutationdetection [56], but they have been extensively used for soilmicrobial community analyses since the 90-ies [5,48]. PCR-DGGEhas been optimized for use with soil DNA in the last decade andnow constitutes a routine and reliable method to produce rapiddepictions of (dominant) soil microbial communities. Dependingon the primers used, PCR-DGGE can depict the microbial diversityand community make-up at the level of the 16S rRNA gene(phylogenetically-based fingerprinting) or any other marker gene(such as rpoB, gyrA or recA), or, alternatively, at the level of a func-tional gene (such as amoA). Furthermore, the suitability withrespect to the quick comparison of large numbers of samples fromdifferent treatments has made the technique common propertyacross a range of laboratories. The ability to excise, reamplify andsequence particular bands in the patterns even allows for theidentification of the microbial types or genes that underly thesebands, although the sizes of the underlying ampliconsmay limit theinformation that is obtained [14,21]. In spite of its current routineuse and wide acceptance, PCR-DGGE still faces problems whichmay hamper the analyses. For one, different sequences may displaysimilar migratory behavior in the gel, thus giving rise to coincidingbands [57]. Secondly, the presence of multiple melting domainswithin the same molecule may cause bands to appear fuzzy on gel[58]. Thirdly, and specifically important for the 16S rRNA basedapproaches, some organisms contain several (up to 15) ribosomaloperons, between which microheterogeneity may exist. If thismicroheterogeneity yields differences in melting, then multiplebands arise on gel which are provenient from the same organism.Finally, the formation of heteroduplexes may cause an over-estimation of the number of bands present, although thisphenomenon is often detectable on gel [59]. Due to these issues aswell as the still qualitative nature of the PCR which is used as thebasis for the generation of molecules of different sequence, quan-tification of the bands as a tool to predict the absolute abundance ofparticular bacterial types in the community is often of questionablevalue. Hereunder, we examine to what extent phylogenetically-based bacterial PCR-DGGE allows us to make inferences about soilmicrobial community make-up.

3.4.3. Bacterial phylogenetic DGGEThe 16S rRNA gene is nowadays routinely used in PCR-DGGE as

well as TGGE as the proxy for bacterial phylogenetic relatedness. Infact, the first DGGE and TGGE analyses that were ever performed, inthe 90-ies, were based on the use of bacterial 16S rRNA genes.Application of the method to diverse soil communities has yieldedimportant scientific insights that were impossible to achieve beforethe onset of the approach. Thus, on the basis of this method, Dui-neveld et al. [60] could clearly dissect the bacterial communities inthe rhizosphere of Chrysanthemum, pinpointing Variovorax spp.,next to Acetobacter spp., as key rhizosphere inhabitants. Concerningthe area of the assessment of the impact of genetically-modified(GM) plants, Gyamfi et al. [61] showed, on the basis of the method,ephemeral minor changes in the bacterial diversity between GMand non-GM canola. In contrast, Angelo-Picard et al. [62] did notfind any difference in the eubacterial communities between GMand non-GM tobacco. Given the successes with such analyses, itseems likely that 16S rRNA-based PCR-DGGE will remain onemethod of choice in future studies on the impact of GM plants onthe soil microbiota. However, as indicated before, it has inherentlimitations with respect to its resolving power, as typically only upto 100 bands can be distinguished in a gel lane. Only the mostabundant members of a microbial community are thus detectable,with a threshold of roughly 0.1% of the total (the “top-1000”).

J.D. van Elsas, F.G.H. Boersma / European Journal of Soil Biology 47 (2011) 77e87 83

Therefore, the approach does not detect microorganisms of the rarebiosphere in soil and also will not easily detect subtle changes ina microbial community. This lack of resolving power has partiallybeen solved by targeting specific groups within the community, asoutlined in the foregoing. Another limitation of phylogenetically-based PCR-DGGE profiling is that it does not a priori allow us toassess soil functioning. On the other hand, in particular cases suchas the bacterial ammonia oxidizers, the phylogenetic profiles werefound to correlate well with functional diversity. Hence, group-specific PCR-DGGE analyses proved to be very useful to inferpotential function and functional redundancy. Such considerationsare important as they provide ways to infer whether additionalmethods that address functioning are necessary. These methodsmay range from the detection and quantification of messenger RNAand/or of functional genes to the assessment of the rate offunctioning.

3.4.4. Functional gene-based DGGE to assess functional diversityAs the functional redundancy among the bacteria in soil is often

high, community shifts observed via PCR-DGGE gels based on 16SrRNA genes do not a priori provide information on soil functioning,quality and health. In this respect, reduced soil microbial diversitymight not necessarily correlate with poor soil functioning. Giventhe limitations of phylogenetic assessments, in the last decade anincreasing focus has been placed on the analysis of protein-encoding genes involved in key ecosystem processes. On the onehand, attention was given to functions in which the genes areharbored by only one or few bacterial species, i.e., which are mono-or oligophyletic. Disturbances influencing such groups, e.g., bacte-rial ammonia oxidizers, supposedly have a larger influence on soilfunctioning than those affecting highly-redundant groups [63]. Onthe other hand, functional genes occurring in a wide range ofbacteria, such as in denitrification, were addressed. Gene databaseshave expanded enormously over the last decade, making robustand specific primer design for the detection of a range of functionalgenes feasible (see further). However, the web-based informationthat can be found per functional gene still does not come close tothe wealth of information on 16S rRNA gene sequences. Varioustarget genes have been used as proxies to track changes in soilfunctional gene diversity, including the gene encoding ammoniamonooxygenase, amoA, those encoding methane monooxygenasespmoA and mmoX [30], nitrate reductase narG, nitrite reductasesnirK and nirS, and nifH encoding the dinitrogenase reductases ofnitrogen-fixing bacteria [45]. Interestingly, the nifH gene hasrecently been used to study the impact of GM (Bt) white spruce onsoil nitrogen-fixing communities [64]. The authors did not finda significant effect of the transgenic plant on the nitrogen-fixingcommunities. As another example, the presence of the phlD geneencoding the production of the antagonistic compound diacetylphloroglucinol (DAPG) by pseudomonads has been successfullytracked in soil using PCR-DGGE [65].

Although the analysis of target genes encoding enzymesinvolved in key or sensitive soil processes provides better insight in(potential) soil function than that of the 16S rRNA gene, the linkbetween soil microbial diversity and function is still far fromunderstood. One of the greatest challenges for the forthcomingyears will be to understand how microbial diversity affects thefunctioning of the soil system and to address the issue of stability offunction in the face of stress imposed on the soil.

3.5. Clone librariesAs mentioned in the foregoing, analyses of clone libraries

provides direct access to information (richness, evenness andnature) on the targeted gene sequences present in the extantmicrobiota. In clone library analyses, PCR-generated amplicons

(with preselected primers that target a selected phylogeneticproxy like the 16S rRNA gene, or a functional gene) are ligated intoa suitable vector plasmid. Subsequently, the resulting constructsare introduced into Escherichia coli by transformation. Aftergrowth of single colonies that received vectors with insert, clonedamplicons can be isolated by plasmid extraction, sequenced andthe sequences analyzed by comparison to databases. In thisanalysis, chimeras are routinely discarded, as discussed before. Thesensitivity of clone library analyses, with respect to understandingthe community diversity and phylogenetic make-up, is higherthan that of the aforementioned fingerprinting techniques. This ismainly so because the sequences are analyzed separately, andhence single sequences from abundant or less abundant species(given a large enough sample size) are well detectable. Addition-ally, a major advantage of 16S rRNA gene based clone libraries isthe ability to directly obtain and analyze novel sequences, whichincreases our knowledge of soil microbial community make-up.Rarefaction analysis has shown that, in order to achieve satisfac-tory coverage of the extant bacterial diversity in soil ecosystems,an unrealistically high number of sequences is often required(roughly over 1500 or 2000 [66]). However, practical consider-ations (as reflected in the question “what degree of novelty ispresented with clone library analysis even if coverage is stilllow?”) have led the scientific community to also accept dataobtained with smaller-sized libraries. Moreover, the data con-tained in these can be cross-compared between different soils ortreatments using advanced statistical tools such as LIBSHUFF [67]or UniFrac [68].

Clone library analysis is a somewhat laborious method, which,with current ultra-high-throughput sequence facilities, allows foran in-depth analysis of microorganisms or functional genes presentin a soil microbial community. However, the current high-throughput facilities also facilitate the direct generation ofsequence diversity data on the basis of soil DNA, thus bypassing thecloning step (see section High throughput sequencing). Clonelibraries have high resolution but e as large samples are needed todetect the less abundant (rare) bacterial types e do not allow fora quick overview of the diversity per sample or the differencebetween samples, as is the case with fingerprinting techniques.Therefore, there is a need to combine the two methods. It is,however, important to recognize the cloning bias that is inherent tothe technique, i.e., DNA fragments are ligated into a vector plasmidwith possibly differential efficiencies. This may affect the inter-pretation of the true microbial diversity in the system. Directpyrosequencing or microarray analysis of soil DNA bypasses thispotential bias (see sections below).

3.6. DNA microarrays (chips)Over the last decade, the analysis of the diversity and activity of

the soil microbiota has been greatly spurred by the developmentof DNA microarrays and their use in hybridization assays of soilDNA. In this method, soil DNA is, often after pre (PCR-based)amplification, fluorescently labeled and brought into contact witha microarray. On the microarray, up to tens of thousands ofoligonucleotide probes, either consisting of fragments of 16S rRNAgenes (Phylochip; [69,70]) or of functional genes (Geochip; [71]),are positioned in a dense array. Genes in the soil DNA that arehomologous to the probes present on the chip will bind e viahybridization e at the positions of their homologous counterparts.After hybridization, the signals on the chip are digitally analyzed.This way, information on the phylogenetic diversity and commu-nity make-up (Phylochip) as well as on functional potential(Geochip) of the soil is obtained in high throughput. In a high-complexity sample such as soil, distinguishing potential sequencediversity and cross-hybridization may be problematic. To solve the

J.D. van Elsas, F.G.H. Boersma / European Journal of Soil Biology 47 (2011) 77e8784

issue for the phylochip, a minimum of eleven or more shortoligonucleotides have been designed, allowing to distinguishperfect match (PM) from mismatch (MM) [70]. Cross-hybridizationbecomes a key issue in particular when highly abundant 16S rRNAgene fragments share sequence similarity to nontarget probesresulting in weak false positive signals. The perfect match (PM)-mismatch (MM) pair approach substantially improves the fidelityof hybridization. The phyloarray approach was suitable to identifyOTUs which contributed to the differences in the soils underdifferent land use. DeSantis et al. [69] detected a higher degree ofdiversity by this approach than that observed by 16S rRNA genebased PCR followed by cloning and sequencing. Moreover, theapproach was useful to overcome the problem of dominance, i.e.,the overshadowing of members of the rare soil biosphere by thedominant ones. The phyloarrays that are presently available canthus complement the 16S rRNA gene based cloning andsequencing as well as community fingerprinting by PCR-DGGE or -T-RFLP. In addition, geochips may contain over 24,000 probescovering more than 10,000 genes distributed among more than150 functional groups involved in nitrogen, carbon, sulphur andphosphorus cycling [71]. They have been employed for soil studies[71] in which initial hybridizations showed to be rather insensi-tive. Hence, to increase sensitivity, preamplification (e.g., by rollingcircle amplification) has been included. The geochip has beensuccessfully applied to study N- and C-cycle genes in antarcticsoils [72], indicating that the functional gene complement differedsignificantly across sampling locations and vegetation types. Giventhe novelty of the functional gene array, quantitative PCR andenzyme assays were used, which substantiated the microarrayhybridization results [72].

Microarray hybridization has enormous potential, including thepossibility to generate a so-called universal microarray describingsoil quality or health. However, it is critical here which probes willbe elected to make part of the chip, and the relationship betweenparticular genes and soil health is not at all clear. Furthermore,positive detectionwill depend on the probes that are present on thechip and thus on pre-existing knowledge about the underlyingorganisms or genes. Hence, totally unknown organisms or geneswill not be detected by using chips that are based on databasesequences. Researchers have acknowledged this problem and haveset out to prepare chips based directly on soil DNA, thus encom-passing material from the whole sampled community (Vogel, pers.comm). This has potentially solved one problem, namely the lack ofrepresentation for the extant community, but it has opened anotherbox of problems, i.e., those related to the undefined nature of manyof the new probes on the chip.

Probe development, hybridization quality and data evaluationare the crucial steps for an appropriate use of DNA microarrays tostudy the soil microbiota. Bottlenecks in microarray work includeproblems of robustness and the fact that they cannot generateinformation on new sequence types. Thus, only the breadth offunctions/genes that are already known can be assessed [72]. Inspite of such remaining challenges, the all-at-once glance at(potential) soil functioning offered by DNA microarrays isvery attractive. The data obtained can be placed in the context of(local) soil/mycosphere conditions to obtain gene level e habitatcorrelations.

3.7. High throughput sequencing- pyrosequencingand Solexa-based sequencing

Just a few years ago, several highly powerful novel sequencingtechniques, denoted next-generation (NG) sequencing methods,were developed [73]. Prominent among them were the so-called454-based/pyrosequencing [74] and Illumina/Solexa’s GenomeAnalyzer sequencing. These high-throughput technologies seemed

very suitable for massive parallel sequencing of metagenomes andmetatranscriptomes [75]. For instance, soon after its emergence,454-based pyrosequencing was applied to soil DNA [66,76,77] and/or RNA [19]. This method consists of multiparellel sequencing bysynthesis, in which the pyrophosphate that is released is detectedin an enzymatic cascade ending in luciferase and detection of theemitted light. Pyrosequencing, as well as Illumina sequencingbypass three bottlenecks in classical sequencing, namely librarypreparation, template preparation and the actual capillarysequencing [73]. Its multiparallellity allows the production ofhundreds of thousands to millions of 450-bp reads in just a singlerun. The Solexa platform even offers an orders of magnitude higherthroughput of reads, however at lower read lengths (currently35 bp on average).

The sensitivities of the two NG sequencing platforms are mainlydetermined by the efficiency and unbiased nature of thesequencing, which directly uses soil DNA. Hence, the soil DNAextraction method strongly determines the representation andeventual bias of the data. The 454 platform, yielding longer reads, isof direct use for the generation of, e.g., partial 16S rRNA based reads,whereas the Solexa platform, due to its extreme throughput, mayserve the purpose of “gap-filling” in 454-generated sequence data.Limitations may arise by the human capability to analyze theimmense amount of data obtained and of databases to deal witherrors (noise) and to filter out the genes of interest [78].

In practical terms, evolutionarily-distant genes with similarfunction from previously unknown sources may remain uncon-sidered as databases may fail to identify such sequences. On theother hand, given current analytical power, direct pyrosequencingof soil DNA allows to dissect a system from the top to the bottom,i.e., starting with the most abundant species going down into therare biosphere [77,79]. A major advantage of pyrosequencing isthat, given its ultra-high throughput and lack of biases, many newsequences will be discovered, thereby giving novel insight into soilmicrobial diversity [80]. There are, however, some drawbacks. Thereads that are produced are often relatively small (maximally450 bp), thus yielding only partial 16S rRNA sequence reads. Themethod is more error-prone than previous (Sanger-based)sequencing and thus special error (“noise”) detection programs arerequired [78]. Lastly, the overwhelming amount of sequence dataobtained will require special bioinformatics software for easysorting (binning) and analysis. It will possibly make arbitrarychoices insuperable, hampering the analyses [80]. Furthermore, atthis point in time, analyses on the basis of pyrosequencing are a bitlimited by the high costs of the equipment and procedure, but thissituation is rapidly changing.

In spite of financial and other limitations, the NG sequencingtechniques discussed so far have already been extensively used inthe analyses of soil microbial diversity and community structure aswell as gene expression (metatranscriptomics) across diverse soils[19,66,76,77]. In these cases, mostly bulk soils have been analyzed.For instance, the soil microbial community structures were shownto shift in relation to soil pH as the main driver, in particular whendirect pyrosequencing was used [66,76]. In addition, a range ofnovel sequences was obtained on the basis of mRNA (metatran-scriptome analysis), although mRNA was never dominant in theextracts [19]. It is foreseeable that, with improved sensitivity [81],soil metatranscriptome-based analyses will actually superseed themicroarray-based analyses, as they (1) directly approach geneexpression at the RNA level and (2) are independent of priorassumptions about the types of genes present. Thus, in terms of theapproaches used, we are currently witnessing a rapid shift from thealready well-accepted molecular fingerprinting and microarray-based techniques to methods based on direct pyrosequencing ofenvironmental metagenomic DNA or RNA [19,66,76,77].

J.D. van Elsas, F.G.H. Boersma / European Journal of Soil Biology 47 (2011) 77e87 85

4. Molecular methods applied to soil microhabitats e themycosphere

4.1. Use of molecular techniques to unravel bacterialefungalinteractions in soil e the mycosphere

Taking into account the aforementioned intricacies of themycosphere habitat, Warmink and van Elsas [16] recently proposedthat an excellent compartment representative of the mycosphere isprovided by the foot of fungal fruiting bodies (mushrooms), wherebundles, consisting of dense networks of hyphae, is present. Thesebundles were hypothesized to concentrate the potential effect onmycosphere-associated bacteria and thus to serve as a hot spot forbacterial activity in soil. By severing off the mushroom foot part,and shaking the loose soil from the foot, a shallow layer of soilsurrounding the mushroom foot was obtained (Fig. 1). The bacteriainhabiting this area in soil were assumed to provide the best accessto the mycosphere microbiota. Using this sampling strategy, War-mink and co-workers [16,35,82] successfully isolated 2e5 mg ofDNA per g of mycosphere soil, which, by a back-of-the-envelopecalculation, may be considered as fairly representative for theestimated microbial community size in this compartment.Following the successful extraction of DNA from the mycosphere,the further processing and analytical steps required to describe thelocal microbiota were found to be similar to those executed withDNA from bulk soil (see section on Soil nucleic acid extractionabove; Fig. 1).

On the basis of nucleic acids extracted from the mycosphere andcorresponding bulk soil, both bacterial phylogenetic PCR-DGGE andclone library analysis were then successfully performed [16,35,82].These studies revealed a clear “mycosphere effect” exerted by thevaried fungi on the local bacterial communities. A major findingwas that the apparent diversity of the bacterial community in themycosphere generally decreased. In other words, the communityrevealed reduced complexity. It was hypothesized that nutrient-rich spots at the mycosphere might locally have incited bacterialgrowth leading to locally selective processes. The reducedcomplexity might be favourable for the dissection of the system bythe aforementioned high-throughput metagenomics- or meta-transcriptomics-based sequencing approaches.

Furthermore, particular bacterial types were also obtained inculture, allowing to study their responses to fungal hyphae in thesoil. Soil pH, next to the presence of glycerol, was shown to impactthe local populations of Variovorax paradoxus HB44 [17,83]. Thus,this polyphasic approach, consisting of direct molecular methodsand cultivation-based analyses, allowed an in-depth analysis ofbacterial population dynamics in soil. The power of the finger-printing and clone library based methods that were used in dis-secting the bacterial communities in mycosphere microhabitatswas thus indicated [16,35,82].

5. Concluding remarks and outlook

In this review, we provide an overview of currently almosttraditional molecular methods, such as PCR-based fingerprintingand clone library analyses, to access the soil microbiota, as well asrecent advances in the development of novel methods (microarraysand high-throughput metagenomic sequencing) and their appli-cation to soil samples. We posit that the large array of currentlyavailable molecular methods will even gain in analytical power ifcarefully applied to the proper soil microhabitats, such as themycosphere, where focussed research questions are being posed. Insome examples of recent work in our laboratory, the application offingerprinting as well as cloning methods to the mycosphere ofselected soil fungi was examined [16,35,82]. From the data

obtained, a selective effect of the mycospheres of several fungi onthe microbial communities -associated with these was found,indicating the possible existence, among soil bacteria, of universalversus specific fungiphiles [82]. Parallels of these data might bedrawn with the well-known rhizosphere effect, i.e., the clearselective effect that plant roots exert on the microbial communitiesin the surrounding soil, and the specificity of the responses given byparticular soil bacteria. In another mycosphere study [35], directanalysis of Sphingomonadaceae communities in the mycosphere oftwo fungal types and the comparison of these with bulk soilcommunities was a primary aim. Hence, it was important to fine-tune and apply a sphingomonad-specific PCR amplification systemcoupled to clone library analysis and DGGE fingerprinting toanalyze whether communities of the targeted sphingomonadswere selected in the mycosphere. Moreover, it was thought to beimminent to analyze to what extent different members of thiscommunity become selected or deselected in the mycosphere. Onthe basis of the respective soil and mycosphere DNAs, we thusobtained an in-depth analysis of the respective sphingomonadcommunities and revealed strong mycosphere effects on these. Thedata also revealed hitherto undetected bacterial groups. Theseexamples are not exhaustive and could be complemented withexamples from other labs. However, they illustrate thate as a resultof the application of molecular tools e strong progress has beenachieved in our understanding of the bacterial communities at themicrohabitat/mycosphere level. The ability to precisely sample anddissect samples of such soil microhabitats into the key componentsneeded for molecular analyses was a crucial and indispensableconditio-sine-qua-non in these analyses. Moreover, further poly-phasic studies performed in the mycosphere in microcosmsrevealed the selective effect of glycerol released by fungal hyphae infungus (Lyophillum sp. strain Karsten) -associated V. paradoxus likebacteria [17]. Also, this fungus was shown to de-acidify the acid soilused to pH values over 5.0, as a result of which the used V. para-doxus strain, as well as several other bacterial strains, had a morefavourable niche [83]. In this case, the mycosphere apparentlyconstituted a hospitable microhabitat for the bacterial partner.A more in-depth insight into the interactive processes that takeplace in this microhabitat should now be achievable using nucleicacid based metagenomics and metatranscriptomics analyses. Thelatter analysis would be especially relevant, as responses of thebacterial partners to soil fungi and vice versa in the microcosmmight be directly assessed from comparative analyses of the met-atranscriptomes obtained from systems with or without any one ofthe partners.

However, given the overall nature of these methods applied tomixed soil microbial communities and the analytical power offeredby having microorganisms in culture, for such studies it is stronglyadvocated to apply a polyphasic analytical approach to analyzingsoil and related systems, which should consist of:

(1) analysis of soil microorganisms in a direct fashion on the basisof their DNA or RNA, using molecular methods (see later),

(2) detection of their activities, if possible, in situ (e.g., messengerRNA-based),

(3) isolation of organisms and interrogating their ecophysiologicalbehavior in order to predict their in situ behaviour.

Acknowledgements

We thank Rashid Nazir for his assistance with providing mate-rial for this review. Three anonymous reviewers are acknowledgedfor their very helpful comments.

J.D. van Elsas, F.G.H. Boersma / European Journal of Soil Biology 47 (2011) 77e8786

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