Corinne Biderre-Petit

Didier J Éz Équel

Eric Dugat-Bony

Filipa Lopes

Jan Kuever

Guillaume Borrel

Eirc Viollier

Gerard Fonty

Pierre Peyret
email: pipeyret@univ-bpclermont.fr

Identi¢cation of microbial communities involved in the methane cycle of a freshwater meromictic lake

Lake Pavin is a meromictic crater lake located in the French Massif Central area. In this ecosystem, most methane (CH 4 ) produced in high quantity in the anoxic bottom layers, and especially in sediments, is consumed in the water column, with only a small fraction of annual production reaching the atmosphere. This study assessed the diversity of methanogenic and methanotrophic populations along the water column and in sediments using PCR and reverse transcription-PCR-based approaches targeting functional genes, i.e. pmoA (a-subunit of the particulate methane monooxygenase) for methanotrophy and mcrA (a-subunit of the methylcoenzyme M reductase) for methanogenesis as well as the phylogenetic 16S rRNA genes. Although methanogenesis rates were much higher in sediments, our results confirm that CH 4 production also occurs in the water column where methanogens were almost exclusively composed of hydrogenotrophic methanogens, whereas both hydrogenotrophs and acetotrophs were almost equivalent in the sediments. Sequence analysis of markers, pmoA and the 16S rRNA gene, suggested that Methylobacter may be an important group actively involved in CH 4 oxidation in the water column. Two main phylotypes were characterized, one of which could consume CH 4 under conditions where the oxygen amount is undetectable.

Introduction

Methane (CH 4 ) is an important radiative trace gas responsible for about 20% of the anthropogenic additional greenhouse effect. Global CH 4 emissions from natural wetlands range from 100 to 237 Tg year À1 , corresponding to approximately 75% of all natural emissions. Lakes alone are believed to contribute 6-16% of these natural emissions [START_REF] Bastviken | Methane. Encyclopedia of Inland Waters[END_REF]. CH 4 production is a strictly anaerobic process restricted to environments with very low concentrations of alternative electron acceptors [manganese and iron oxides, oxygen (O 2 ), nitrate and sulfate] and high concentrations of common electron donors, particularly H 2 and acetate [START_REF] Capone | Comparison of microbial dynamics in marine and freshwater sediments: contrasts in anaerobic carbon catabolism[END_REF]. The two main pathways of production are acetotrophic (acetate dependent) and hydrogenotrophic (H 2 dependent) methanogenesis. In the former case, acetate is cleaved into CH 4 and carbon dioxide (CO 2 ).

During hydrogenotrophic methanogenesis, H 2 reacts with CO 2 to produce CH 4 and H 2 O [START_REF] Bastviken | Methane. Encyclopedia of Inland Waters[END_REF]. However, currently, there is little evidence of any significant rates of methanogenesis in anoxic water columns, supposedly due to the lower substrate concentrations than that in sediment [START_REF] Bastviken | Methane. Encyclopedia of Inland Waters[END_REF]. Stable syntrophic consortia could be more difficult to establish in water columns than sediments due to the greater transport processes involved. Water chemistry in meromictic lakes is another important factor in determining whether methanogenesis occurs in the water column and in the sediment [START_REF] Winfrey | Microbial methanogenesis and acetate metabolism in a meromictic lake[END_REF].

Once produced in aquatic environments, CH 4 is consumed in both aerobic and anaerobic compartments. Thus, although from 45% to 100% of CH 4 produced in the water column of lakes or derived from benthic flux is oxidized [START_REF] Bastviken | Methane. Encyclopedia of Inland Waters[END_REF], even today, little is known about the structure of methanotrophs in pelagic freshwater ecosystems. Aerobic oxidation by CH 4 -oxidizing bacteria in surface sediments [START_REF] Sweerts | Oxygen-consuming processes at the profundal and littoral sediment-water interface of a small meso-eutrophic lake (Lake Vechten, The Netherlands)[END_REF] and in the water column [START_REF] Utsumi | Dynamics of dissolved methane and methane oxidation in dimictic Lake Nojiri during winter[END_REF] is the main pathway controlling CH 4 escape into the atmosphere, making it a key process for the mitigation of CH 4 emissions from aquatic environments [START_REF] Bastviken | Methane. Encyclopedia of Inland Waters[END_REF]. In freshwaters, CH 4 oxidation is most active in the vicinity of the oxic-anoxic interface, where both CH 4 and O 2 are available.

The second process controlling CH 4 release is anaerobic oxidation of methane, which is thought to involve CH 4oxidizing archaea in a consortium with sulfate-reducing bacteria [START_REF] Boetius | A marine microbial consortium apparently mediating anaerobic oxidation of methane[END_REF]. Although mainly observed in saline/alkaline anoxic continental habitats [START_REF] Joye | Oxidation of ammonia and methane in an alkaline, saline lake[END_REF], recent studies suggest that this pathway also occurs in freshwater environments through nonsulfate terminal electron acceptors [START_REF] Raghoebarsing | A microbial consortium couples anaerobic methane oxidation to denitrification[END_REF].

Lake Pavin in the French Massif Central is a permanently stratified crater lake with layers of water that do not intermix. Hence, this meromictic lake has three water layers, an anoxic deep water layer (monimolimnion) separated from the oxygenated upper layer (mixolimnion) by an intermediate layer (mesolimnion) with strong chemical gradients. The sharp increase in the concentration of dissolved compounds within the mesolimnion leads to an increase in the density of the bottom water layers and consequently strengthens the stability of the physical stratification, despite a temperature increase of about 1 1C [START_REF] Michard | Vitesse des réactions de dissolution et précipitation au voisinage de l'interface oxydo-réducteur dans un lac méromictique: le lac Pavin (Puy de Do ˆme, France)[END_REF]. The isolation of the monimolimnion (by the mesolimnion) results in a significant CH 4 accumulation (over 4 mM at 90 m depth). This situation causes a strong CH 4 concentration gradient within the mesolimnion, but only a small amount (a 10 5 decrease in concentration from the bottom to the top of the lake) of this CH 4 actually reaches the atmosphere, as it is almost fully consumed in the water column.

The identification of organisms involved in methanotrophy and methanogenesis within Lake Pavin is a key step for a complete understanding of the CH 4 and carbon cycles in this ecosystem. In this study, the diversity and the vertical distribution of methanogens and methanotrophs were assessed along the entire water column and sediments of this lake using two functional gene markers [i.e. the a-subunit of the particulate methane monooxygenase (pmoA) for methanotrophy, the a-subunit of the methyl-coenzyme M reductase (mcrA) that catalyzes the last step in methanogenesis]. Additional studies with 16S rRNA gene analyses were also performed at two critical points in the water column. Our results provide insights into the substrate or niche adaptations of these communities.

Materials and methods

Sampling site

Lake Pavin (45129.74N, 2153.28E) is a maar located at 1197 a.s.l. in the more recent volcanic area of the French Massif Central. It is divided into two permanent stratified layers (Fig. 1) (see [START_REF] Michard | Vitesse des réactions de dissolution et précipitation au voisinage de l'interface oxydo-réducteur dans un lac méromictique: le lac Pavin (Puy de Do ˆme, France)[END_REF]. The surface stratum, or mixolimnion, includes three different layers according to variations in depth, temperature, pH and dissolved O 2 (the epilimnion, up to 5-15 m depth, the metalimnion, from the bottom of epilimnion up to 20 m depth and the hypolimnion from approximately 20 to 61 m depth). Seasonal dissolved O 2 depletion occurs at the base of the hypolimnion with a value close to zero between around 58 and 61 m depth. The mixolimnion is separated from the monimolimnion by the mesolimnion ($60-70 m depth), which is characterized by a strong increase in specific conductivity. Finally, the monimolimnion, from $70 m depth to sediments, is not affected by spring or fall turnover. This layer is characterized by a steady state of the major physical and chemical parameters.

Analytical method

Conductivity, temperature and dissolved oxygen (DO) concentration were determined using a Seabird SBE 19 Seacat profiler (Sea-Bird Electronics Inc., Washington, DC) in July 2007 and May 2009. This CTD-O 2 probe was calibrated for DO with Winkler titrations in triplicate samples from 2 and 40 m depths (where the O 2 gradients are very weak). Profiles were acquired at a speed of descent as low as 5 cm s À1 in the O 2 gradient zone to allow the O 2 sensor to equilibrate.

Water samples for CH 4 concentration determination were collected in July 2007 using a custom-built automatic 1-L syringe sampler, which was built on a 1-L syringe Model S-1000 Hamilton basis, along a vertical profile near the center of the lake. The sampler was deployed from a stable platform, and the use of an electronic depth gauge allowed a 0.2 m depth precision and direct filtration from 1-L syringe just after retrieving on board without air contact (Luer connections and use of syringe filtration units). Water from the oxic mixolimnion (from the surface down to 55 m) was collected into 115-mL serum bottles filled to overflow and then sealed and poisoned with 1 mL of 0.5 g L À1 HgCl 2 until analysis. A 30-mL nitrogen headspace was then created before analysis, as described by [START_REF] Abril | Methane dynamics in a shallow nontidal estuary (Randers Fjord, Denmark)[END_REF]. In the CH 4 -rich zone (from 55 to 90 m depth), a different sampling method was used in order to minimize CH 4 loss due to depressurization: 30 mL of water from the sampling syringe was rapidly transferred with a needle through the butyl cap into preweighed and N 2 -preflushed sealed glass bottles. Thus, most of the depressurization occurred in the bottle, minimizing CH 4 loss. CH 4 concentrations were quantified using a gas chromatograph (Chrompack 438 gas chromatograph, Packard Instruments, Downers Grove, IL) equipped with a 2 m  2 mm Haysep column and a flame ionization detector.

Sample collection

Water column samples were collected using an 8-L horizontal Van Dorn bottle along a vertical profile at nine depths (20, 50, 60, 63, 65, 70, 75, 80, 85 and 90 m) in July 2007 and three depths (65, 70 and 90 m) in June 2009 (Fig. 1). Immediately on collection, the water samples were transferred into sterile bottles and stored on ice until processing. The water samples (0.3-1 L) were filtered directly in the laboratory under vacuum, and collected onto a 47-mm TSTP Millipore filter (0.2-mm pore size). Filters were stored dry at À 80 1C until nucleic acid extractions.

Supplementary water column samples (also 0.3-1 L) were collected using a 4-mm-bore PVC tube connected to a peristaltic pump and filtrated on-site through a 47-mm TSTP Millipore filter (0.2 mm) held in a Swinnex-47 (Millipore, Billerica, MA) filter holder connected to the tube, at 62 m depth in December 2007 and at four depths (50, 55, 60 and 63 m) in June 2009 (Fig. 1). This second sampling method was used, when possible, to reduce mRNA transcription modifications or their destruction, which could be induced by transport. Thus, filters were immediately placed into 2-mL sterile tubes (Eppendorf, Hamburg, Germany) and stored on dry ice until they were transferred at À 80 1C to the laboratory for further nucleic acid extraction. Unfortunately, this sampling was not applied for depths below 63 m due to excessively high degassing in the anoxic zone.

Sediment samples were collected at 40 m depth (within the oxic zone) and at 92 m (within the anoxic zone) in June 2007 and only at 92 m in June 2009 using a gravitational Uwitec corer with a diameter of 90 mm and a length of 60 cm (Fig. 1). About 100 g of each sediment sample from the upper sediment horizon (first 20 cm) was separately placed in sterile containers and stored on dry ice until being transferred to the lab at À 80 1C for further processing.

Nucleic acid extractions

Genomic DNA (gDNA) was extracted from samples collected in 2007, and total RNA was extracted from samples collected in 2009. Water column filters were placed in 900 mL of lysis buffer as described by [START_REF] Vetriani | Fingerprinting microbial assemblages from the oxic/anoxic chemocline of the Black Sea[END_REF]. Freeze-thaw cycles were replaced by the beat-beating method, and nucleic acids were extracted using a standard phenolchloroform-isoamyl alcohol (50 : 49 : 1) method, followed by a second extraction with an equal volume of chloroform. Nucleic acids were then precipitated, washed in 70% ethanol and resuspended in nuclease-free water. For RNA samples, coextracted DNA was removed by digestion with 4 U of (RNase-free) DNase I (DNA-free, Ambion, Austin, TX) at 37 1C for 35 min following the manufacturer's instructions.

Frozen sediment aliquot (30 g) collected in June 2009 was mixed vigorously with 200 mL of buffer containing glucose, EDTA and Tris-HCl [START_REF] Vetriani | Fingerprinting microbial assemblages from the oxic/anoxic chemocline of the Black Sea[END_REF] and centrifuged briefly at 200 g before filtering the supernatant onto a 47mm TSTP Millipore filter (0.2 mm). The filter was then placed in 900 mL of lysis buffer. RNA was extracted as described above. DNA from frozen sediment aliquots (3 g) sampled in June 2007 was extracted using the protocol described by [START_REF] Zhou | DNA recovery from soils of diverse composition[END_REF].

Nucleic acid concentrations were measured using a NanoDrop ND-1000 spectrophotometer (NanoDrop). The integrity of the extracted RNA was checked by analyzing an aliquot on a Model 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA) using the RNA 6000 Nano kit (Agilent Technologies, Santa Clara, CA). DNA integrity was analyzed on an agarose gel. cDNA synthesis cDNA synthesis was performed starting with 100 ng RNA and using SuperScript III reverse transcriptase (Invitrogen Inc., Carlsbad, CA). To remove the secondary structure, the mixture containing RNA diluted with DEPCtreated water in a final volume of 12 and 0.5 mL of genespecific primer (25 mM) was heated for 10 min at 70 1C and immediately placed on ice. Four microliters of 5 Â buffer (supplied), 2 mL 0.1 M DTT, 0.5 mL dNTP mix (2.5 mM each), 0.5 mL (20 U) RNasIn 1 (Promega, Madison) and 0.5 mL SuperScript III reverse transcriptase (Invitrogen Inc.) were then added. The mixture was incubated for 2 h at 42 1C for cDNA synthesis. To check that the RNA extracts were uncontaminated by DNA, control reactions were prepared as described above, but without reverse transcriptase.

PCR and library construction

Table 1 summarizes the primers and cycling parameters used in this study. PCR amplifications were performed in tubes containing 25 mL (total volume) of a mixture using an iCycler thermal cycler (Bio-Rad, CA). Each PCR mix consisted of 1 Â PCR buffer (Promega), 0.2 mM of forward and reverse primers, 250 mM of each dNTP (Invitrogen Inc.), 2 U of GoTaq DNA polymerase (Promega) and template DNA (5-20 ng of gDNA or 4.5 mL of cDNA). For all amplifications, a 5-min denaturation step (95 1C) was included at the beginning of the PCR run. This step was followed by cycles at the annealing temperatures given in Table 1, anda 10-min extension step (72 1C) was included at the end of the reaction. Negative controls were included in all PCR reactions to check for background contamination.

The PCR products were assessed on 1% w/v agarose gels. Amplicons of the correct size were purified using QIAquick spin columns (Qiagen, Chatsworth, CA) and cloned using the TOPO TA cloning kit (Invitrogen Inc.). Plasmids were screened for the correct size insert by digestion with EcoRI. DNA sequencing was performed using the Sanger method [START_REF] Sanger | DNA sequencing with chain-terminating inhibitors[END_REF] on MWG DNA sequencing services (Ebersberg, Germany).

Sequence data and phylogenetic analysis

Sequences were processed and joined using the STADEN package program [START_REF] Staden | The Staden sequence analysis package[END_REF] and characterized using the BLASTN (16S rRNA genes) and BLASTX (functional genes) search tools (http://www.ncbi.nlm.nih.gov). The nucleic acid sequences encoding enzymes were translated using the EMBOSS TRANSEQ tool available at http://www.ebi.ac.uk/Tools/emboss/transeq/ and aligned using CLUSTALW to identify identical amino acid sequences (http://www.ebi.ac.uk/Tools/clustalw2/index.html). After alignment, we conserved only the different deduced amino acid sequences and then grouped them into operational taxonomic units (OTUs) at a cutoff level of 91% [START_REF] Heyer | Molecular phylogeny of type II methane-oxidizing bacteria isolated from various environments[END_REF][START_REF] Luton | The mcrA gene as an alternative to 16S rRNA in the phylogenetic analysis of methanogen populations in landfill[END_REF][START_REF] Kjeldsen | Diversity of sulfate-reducing bacteria from an extreme hypersaline sediment, Great Salt Lake (Utah)[END_REF] using DOTUR software [START_REF] Schloss | Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness[END_REF]. The input files for DOTUR were distance matrices generated by PROTDIST (http:// mobyle.pasteur.fr/cgi-bin/portal.py). One representative of each OTU was subsequently chosen to build phylogenetic trees in MEGA version 4 [START_REF] Tamura | MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0[END_REF] using the neighbor-joining method [START_REF] Saitou | The neighbor-joining method: a new method for reconstructing phylogenetic trees[END_REF]) and then bootstrapped with 1000 trials. Closely related sequences identified by BLAST and available from GenBank (http://www. ncbi.nlm.nih.gov/) plus sequences of characterized species were included in the phylogenetic trees to decipher microbial community diversity.

Nucleotide sequence accession numbers

Nucleotide sequences without PCR primer sequences were deposited in the GenBank database under accession numbers GQ389796-GQ390089 for the mcrA gene, GQ390100-GQ390158 and JF811254-JF811322 for the pmoA gene, and GQ390159-GQ390243 and GU472558-GU472841 for 16S rRNA genes.

Results

Geochemistry

The investigations were carried out using water samples collected in Lake Pavin. Figure 2 shows the vertical profiles of DO, conductivity at 25 1C (C25), temperature and CH 4 concentration for July 2007 and May 2009 (except CH 4 , which was not measured in May 2009). All parameters taken together, the profiles showed typical trends usually observed in Lake Pavin, i.e. O 2 depletion (detection limit o 1 mM) and a sharp increase in C25 and CH 4 at around 60 m depth [START_REF] Viollier | Geochemical study of a crater lake: Lake Pavin, Puy de Do ˆme, France. Constraints afforded by the particulate matter distribution in the element cycling within the lake[END_REF][START_REF] Michard | Vitesse des réactions de dissolution et précipitation au voisinage de l'interface oxydo-réducteur dans un lac méromictique: le lac Pavin (Puy de Do ˆme, France)[END_REF]. In July 2007, the maximum gradients for DO and C25 were located at 57 m depth (oxycline) and 62.1 m depth (mesolimnion), respectively. During this period, the maximum gradient for CH 4 was located at 62.5 m depth, i.e. almost superimposed with the mesolimnion. At 60 m depth, DO and CH 4 were 0.06 mg L À1 and 0.3 mM, respectively, corresponding to a small overlap between the two parameters.

Methanogen abundance and distribution

PCR amplicons of mcrA were obtained both from gDNA and cDNA using a specific primer set (MM_01-MM_02) that enables the coverage of a large portion of methanogens [START_REF] Mihajlovski | A putative new order of methanogenic Archaea inhabiting the human gut, as revealed by molecular analyses of the mcrA gene[END_REF] and subsequently used for the construction of separate clone libraries. Ten clone libraries consisting of 306 clones were constructed from gDNA samples collected in 2007, eight from water column samples No amplification of the mcrA gene could be achieved with gDNA collected from the water layer located above 63 m depth and with cDNA obtained from that located above 70 m depth. This suggested that the active methanogenic community was present only from nearly 70 m depth down to the sediments. Furthermore, considerable microdiversity was evident among the sequenced clones, as 303 unique mcrA nucleic acid sequences were identified that coded for 210 different polypeptides, taking into account all genetic code redundancy. In total, 20 distinct OTUs were detected among the inferred amino acid sequences of mcrA using an arbitrary 91% sequence identity threshold for grouping the retrieved environmental sequences. Nineteen OTUs were present in gDNA libraries and 10 in cDNA libraries. Comparisons at the amino acid sequence level of mcrA gene fragments revealed a number of associations. These OTUs covered three lineages encompassing Methanomicrobiales, Methanosarcinales and a putative third lineage.

Most of the mcrA sequences were closely related to the Methanomicrobiales order (52-100% of total gDNA clones and 58.6-92.3% of total cDNA clones, depending on the library). Two groups of sequences clustered within this order, where they formed a distinct branch (Fig. 3). One group (cluster I) included 12 OTUs (OTU1-12), which showed the strongest similarity to many environmental sequences [START_REF] Luton | The mcrA gene as an alternative to 16S rRNA in the phylogenetic analysis of methanogen populations in landfill[END_REF][START_REF] Castro | Phylogenetic characterization of methanogenic assemblages in eutrophic and oligotrophic areas of the Florida Everglades[END_REF][START_REF] Galand | Pathways for methanogenesis and diversity of methanogenic archaea in three boreal peatland ecosystems[END_REF][START_REF] Conrad | Soil type links microbial colonization of rice roots to methane emission[END_REF]. The second group (cluster II) included only four OTUs (OTU13-16), which showed 83-84% similarity to only one recognized species recently described in an acidic peat bog, Candidatus Methanoregula boonei [START_REF] Brauer | Isolation of a novel acidiphilic methanogen from an acidic peat bog[END_REF]. Of the 16 OTUs, six included sequences both from gDNA and cDNA libraries, nine included only sequences from gDNA libraries and one (OTU12) consisted of only one cDNA sequence (Fig. 3). Both gDNA and cDNA libraries were dominated by a small number of OTUs, the most abundant being OTU2 (Fig. 4). Moreover, the spatial distribution of these OTUs showed clear differences between water column and sediments, but also between sediments in contact with oxygenated water (40 m) and those in contact with anoxic water (92 m). Obviously, OTU7, OTU8, OTU10 and OTU11 dominated sediments collected at 92 m while they were poorly represented (in clone number) or absent in the water column (Fig. 4a). Similarly, OTU16 dominated sediments collected at 40 m, while it was not retrieved from those collected at 92 m. All these findings suggested that certain OTUs could be adapted to different environmental niches (organic matter content, microbial interactions, substrate availability). This hypothesis was reinforced by the analysis of mcrA transcripts with OTU2 and OTU4 from cluster I mainly expressed in the water column and OTU13 from cluster II preferentially expressed in the bottom of the water column and in sediments (Fig. 4b).

The second most abundant group of mcrA sequences was closely related to the Methanosarcinales order (2.7-12.5% of the total gDNA clones and 7.7-37.9% of the total cDNA clones, depending on the library). All sequences grouped into two distinct OTUs (OTU17 and OTU18), both converging on a monophyletic group that included the acetoclastic species Methanosaeta concilii (Fig. 3). This order, therefore, displayed a lower diversity than that of Methanomicrobiales. [START_REF] Tamura | MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0[END_REF]. Evolutionary history was inferred using the neighbor-joining method [START_REF] Saitou | The neighbor-joining method: a new method for reconstructing phylogenetic trees[END_REF]. The evolutionary distances were computed using the Poisson correction method and are in the units of the number of amino acid substitutions per site. All positions containing gaps and missing data were eliminated from the dataset (complete deletion option). There were a total of 127 positions in the final dataset. Bootstrap values 4 70% derived from 1000 replicates are indicated at the nodes. The number of clones assigned to each OTU is given in brackets together with the name of the representative clone used in this study. Methanopyrus kandleri sequence (AAB02003) was used as an outgroup. Arrow indicates the unique closest cultured methanogen species to environmental Methanomicrobiales sequences. Arrow indicates the species Candidatus Methanoregula boonei, which is the unique cultured species closely related to environmental sequences identified in this study. , Phylotype clustering gDNA and cDNA sequences; , phylotype with only a cDNA sequence.

For these OTUs, the largest number of clones was retrieved from sediments (Fig. 5). Furthermore, they showed a clearly different distribution profile, with OTU18 retrieved mainly from sediments in contact with oxygenated water (40 m), whereas OTU17 was retrieved exclusively from those in contact with anoxic water (92 m) and the water column (Fig. 5). These results were consistent with those obtained from mRNA samples. Hence, the shift in Methanosaetaceae assemblage could be correlated with changes in environmental conditions (i.e. pressure, O 2 and microbial interactions).

The third lineage clustered only 12 clones (11 in OTU19, 1 in OTU20) that fell outside any described methanogenic order and formed a deep-branching cluster separate from the other five methanogen orders (Fig. 3). The evidence suggests that this cluster may represent a novel methanogenic lineage. These OTUs showed the highest similarity (80-83%) to mcrA sequences from remotely different habitats including wetland ecosystems [START_REF] Juottonen | Methanogen communities and bacteria along an ecohydrological gradient in a northern raised bog complex[END_REF], landfill [START_REF] Luton | The mcrA gene as an alternative to 16S rRNA in the phylogenetic analysis of methanogen populations in landfill[END_REF], drainage water [START_REF] Castro | Phylogenetic characterization of methanogenic assemblages in eutrophic and oligotrophic areas of the Florida Everglades[END_REF] and human gut [START_REF] Mihajlovski | A putative new order of methanogenic Archaea inhabiting the human gut, as revealed by molecular analyses of the mcrA gene[END_REF], whose phylogenetic affiliation remained doubtful. The fact that this lineage is recovered from various independent ecosystems suggests that it is widely distributed in the environment. In addition, transcripts for this lineage were detected in both the water column and the 92 m sediment. The closer relative of this lineage is the anaerobic methane oxidizer ANME-1 cluster (Fig. 3), which is characterized by a cysteine-rich (CCX4CX5C) stretch in its mcrA sequence [START_REF] Hallam | Identification of methyl coenzyme M reductase A (mcrA) genes associated with methane-oxidizing archaea[END_REF][START_REF] Shima | Methyl-coenzyme M reductase and the anaerobic oxidation of methane in methanotrophic Archaea[END_REF]. Because of the absence of this signature in mcrA sequences affiliated to the novel lineage, its involvement in methanogenesis or anaerobic methanotrophy remains unclear.

Methanotroph abundance and distribution

The planktonic methanotroph assemblages were investigated by pmoA gene amplification using a specific primer set [START_REF] Costello | Molecular characterization of functional and phylogenetic genes from natural populations of methanotrophs in lake sediments[END_REF] from fewer sample points along the water column. PCR amplicons of pmoA were subsequently used for the construction of separate clone libraries. Seven clone libraries consisting of 120 clones were constructed from gDNA samples, five from the oxic layer (20, 50, 60, 62 and 63 m) and two from the anoxic layer (70 and 75 m). Five additional clone libraries consisting of 119 clones were also constructed from cDNA samples (50, 55, 60, 63 and 65 m). Only one clone of the six sequenced for gDNA sample collected at 75 m was pmoA; therefore, amplicons obtained from greater anoxic depths were considered as false positives and not cloned. No reverse transcription (RT)-PCR products were achieved with cDNA from the water layer located below 65 m depth, suggesting that this gene was only expressed up to this zone, where O 2 was below the detection threshold. As for the mcrA gene, a large microdiversity was also observed for pmoA because 128 unique pmoA nucleic acid sequences were identified that coded for 94 different polypeptides. In total, six distinct OTUs were detected among the inferred pmoA amino acid sequences ( 4 91% sequence identity threshold); only two were present in cDNA libraries (Fig. 6).

The most abundant pmoA sequences, distributed into three OTUs (OTU1-3), were from type I methanotrophs closely related to the Methylobacter genus. These sequences were dominant at all the depths tested (Fig. 7). OTU1, which clustered the majority of clones both from gDNA and cDNA libraries, was more closely related to Methylobacter psychrophilus, whereas the last two OTUs were readily distinguishable from the known Methylobacter sp. and formed a separate branch within this group, clustering with environmental clones (Fig. 6). pmoA transcripts were detected only for OTU1 and OTU2, suggesting that they were the predominant active groups in this ecosystem. Figure 8 showed, subsequently, that transcripts for each OTU had a distinct distribution profile along the water column, OTU2 being mainly expressed in the upper part of the water column up to 55 m depth and OTU1 being most actively present below 55 m depth. These findings could suggest that OTU2 activity would be more sensitive to O 2 deprivation than OTU1, with an almost total disappearance of this gas being observed around 60 m depth.

The last three OTUs (OTU4-6) were only retrieved from gDNA libraries. They were only marginal (i.e. in terms of the relative clone abundance). Their distribution along the water column was different (Fig. 7), suggesting a vertical shift in their assemblage that could be linked to CH 4 or O 2 concentration (Fig. 2). Both OTU4 (seven clones) and OTU5 (15 clones) were associated with members of the Methylococcaceae, the first being closely related to Methylosarcina lacus (AAG13081) in type I methanotrophs and the second to the clone group B6 [START_REF] Pester | pmoA-Based analysis of methanotrophs in a littoral lake sediment reveals a diverse and stable community in a dynamic environment[END_REF] in type X methanotrophs. Obviously, only OTU6 (five clones) was associated with type II Methylocystaceae methanotrophs and was closely related to pmoA from Methylocystis parvus (AAQ10310), with one of the deduced amino acid sequences (clone 20A2) sharing 100% amino acid sequence identity with the M. parvus sequence.

Methanotroph community analysis from the 16S rRNA gene biomarker

16S rRNA gene fragments were PCR amplified from gDNA extracted at two critical points of the water column, for example at 62 m depth corresponding to the oxic-anoxic interface and at 70 m depth in the anoxic water layer, in order to confirm the pmoA results. In summary, 135 clones were sequenced, which clustered into 42 distinct OTUs (threshold Z97% sequence similarity). The relative abundance of dominant bacterial varied vertically, with Beta-, Epsilonand Gammaproteobacteria highly abundant at the oxicanoxic interface and both Actinobacteria and Verrucomicrobia increasing sharply with decreasing O 2 concentration at 70 m (Fig. 9). Most of the Gammaproteobacteria clones (79%) were related to type I methanotroph sequences, which were distributed into three distinct OTUs and matched most closely with the type strains of M. psychrophilus (97-99% similarity) and Methylobacter tundripaludum (95% similarity).

Discussion

Methanogenesis in Lake Pavin

In this study, we confirm that methanogens present in the water column of Lake Pavin are metabolically active (Figs 4 and5). This finding is in agreement with Lopes' model (Institut de Physique du Globe de Paris, pers. commun.), which suggests that this compartment could contribute to 20% of the total CH 4 production. Although the same trend was described by [START_REF] Winfrey | Microbial methanogenesis and acetate metabolism in a meromictic lake[END_REF] and [START_REF] Iversen | Big Soda Lake (Nevada). 3. Pelagic methanogenesis and anaerobic methane oxidation[END_REF] for Knaack Lake and Big Soda Lake, respectively, CH 4 produced by lakes seems mainly due to the CH 4 flux from the sediment. The absence of sulfate and nitrate in the [START_REF] Tamura | MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0[END_REF]. The evolutionary history was inferred using the neighbor-joining method [START_REF] Saitou | The neighbor-joining method: a new method for reconstructing phylogenetic trees[END_REF]. The evolutionary distances were computed using the Poisson correction method and are in the units of the number of amino acid substitutions per site. All positions containing gaps and missing data were eliminated from the dataset (complete deletion option). There were a total of 139 positions in the final dataset. Bootstrap values 4 70% derived from 1000 replicates are shown at nodes. The number of gDNA and cDNA clones assigned to each OTU is given in brackets, together with the name of the representative clone used in this study. Nitrospira sp. Enl299 sequence (ABM54176) was used as an outgroup. On the right, the name of the representative clone used for each phylotype is indicated. bottom waters of Lake Pavin corroborates this assumption [START_REF] Michard | Geochemical study of a crater lake: Pavin Lake, Franceidentification, location and quantification of the chemical reactions in the lake[END_REF].

Most of the mcrA OTUs identified in this study belonged to the Methanomicrobiales order. They were widely dominant in all the water samples tested and highly diverse compared with those belonging to the Methanosarcinales order. Additionally, as the closest relative of Methanomicrobiales sequences is the hydrogenotrophic species, C. Methanoregula boonei, it is likely that phylotypes present in Lake Pavin are hydrogenotrophic. However, this assumption remains unconfirmed (Fig. 3). The hydrogenotrophic methanogenesis could be, therefore, the main CH 4 production process in the water column. In contrast, in sediments, the number of clones related to Methanomicrobiales and Methanosarcinales was almost equivalent. As suggested by [START_REF] Schwarz | Community structure of Archaea and Bacteria in a profundal lake sediment Lake Kinneret (Israel)[END_REF], members of these two orders could be efficient syntrophic partners in the complete degradation of organic biomass in freshwater sediments.

Several studies report a greater involvement of hydrogenotrophic methanogens in CH 4 production as compared with acetoclastic methanogens [START_REF] Schwarz | Community structure of Archaea and Bacteria in a profundal lake sediment Lake Kinneret (Israel)[END_REF][START_REF] Nettmann | Archaea diversity within a commercial biogas plant utilizing herbal biomass determined by 16S rDNA and mcrA analysis[END_REF]. Although our study supports this observation, this contrasts with studies based on 16S rRNA gene that suggested that the acetoclastic methanogens dominated the water column and the sediment-water interface of Lake Pavin [START_REF] Lehours | Anaerobic microbial communities in Lake Pavin, a unique meromictic lake in France[END_REF][START_REF] Lehours | Phylogenetic diversity of archaea and bacteria in the anoxic zone of a meromictic lake (Lake Pavin, France)[END_REF]. This difference could be explained by a bias in the PCR where some sequences are amplified in preference to others. Bias in PCR has been observed when amplifying 16S rRNA genes where a single universal primer is used, leading to significant underestimation of true community diversity at all levels of taxonomic hierarchy [START_REF] Jeon | Environmental rRNA inventories miss over half of protistan diversity[END_REF][START_REF] Hong | Polymerase chain reaction primers miss half of rRNA microbial diversity[END_REF]. The acetoclastic methanogenesis pathway is also supported by a study using carbon isotope fractionation of acetate [START_REF] Whiticar | Carbon and hydrogen isotope systematics of bacterial formation and oxidation of methane[END_REF]. [START_REF] Goevert | Carbon isotope fractionation by sulfate-reducing bacteria using different pathways for the oxidation of acetate[END_REF] showed, however, that the sulfate reducer Desulfobacca acetoxidans, which uses the acetyl-CoA pathway, had a similar fractionation as acetoclastic methanogens using the same pathway. Both types of microorganisms were identified in the water column of Lake Pavin [START_REF] Biderre-Petit | Identification of sulfur-cycle prokaryotes in a low-sulfate lake (Lake Pavin) using aprA and 16S rRNA gene markers[END_REF]. Thus, carbon isotope fractionation of acetate in Lake Pavin may also be strongly dependent on the sulfate-reducing community oxidizing acetate.

The third lineage with two OTUs formed a deep branch with the highest similarity to environmental mcrA sequences from various methanogen ecosystems. The species carrying these sequences are metabolically active, suggesting an involvement of this lineage in the CH 4 cycle. Although their closest relative is the anaerobic methane oxidizer ANME-1, no specific signature for this cluster was identified.

Aerobic methanotrophy in Lake Pavin

In this study, we show that aerobic methanotrophy occurs at the oxic-anoxic interface both with functional and with phylogenetic biomarkers. This finding is also in good agreement with Lopes' model (pers. commun.), which suggests that aerobic CH 4 oxidation is the main CH 4 sink in the water column of Lake Pavin. The planktonic methanotroph assemblages investigated by pmoA gene analysis showed that the oxic zone of the water column lodges methanotrophic bacterial species that fall into type I, II and X methanotrophs (Fig. 6). Most of the clones obtained in this study were closely related to Methylobacter sp., particularly M. psychrophilus. This is consistent with results from different marker analyses in a wide variety of ecosystems [START_REF] Wartiainen | Methanotrophic diversity in high arctic wetlands on the islands of Svalbard (Norway) -denaturing gradient gel electrophoresis analysis of soil DNA and enrichment cultures[END_REF][START_REF] Pester | pmoA-Based analysis of methanotrophs in a littoral lake sediment reveals a diverse and stable community in a dynamic environment[END_REF][START_REF] Nercessian | Bacterial populations active in metabolism of C1 compounds in the sediment of Lake Washington, a freshwater lake[END_REF][START_REF] Rahalkar | Comparison of aerobic methanotrophic communities in littoral and profundal sediments of Lake Constance by a molecular approach[END_REF][START_REF] Kojima | Community structure of microorganisms associated with reddish-brown iron-rich snow[END_REF][START_REF] Liebner | Diversity of aerobic methanotrophic bacteria in a permafrost active layer soil of the Lena Delta, Siberia[END_REF]. These methanotrophs could be the key players in CH 4 oxidation regardless of selection pressure due to changes in O 2 and CH 4 concentrations. Moreover, in the present study, both 16S rRNA gene and pmoA biomarkers allowed the identification of three distinct phylotypes closely related to the genus Methylobacter: one more closely related to M. psychrophilus and two constituting a separate group within this cluster. These findings suggest that Methylobacter forms a microdiverse community at the species level in this ecosystem. These results were confirmed by the RT-PCR approach used to characterize pmoA gene expression. Only Methylobacter pmoA transcripts were detected in the water column up to 65 m. This suggests that it was the predominant active group in this ecosystem (Fig. 8). However, at 65 m, no O 2 could be measured, its concentration being below the detection limit ( o 1 mM) (Fig. 2). As Methylobacter sp. has not been conclusively demonstrated to adapt to anaerobic conditions, an explanation may be that the microaerophilic microorganisms, among which Methylobacter sp., could immediately consume the low amount of O 2 available in this zone by making it undetectable. Moreover, transcripts for OTU1 and OTU2 showed distinct distribution profiles along the water column, suggesting differences in their assemblage structure that could be correlated to substrate availability or changes in physicochemical parameters. This finding led us to speculate that the Methylobacter phylotype identified in the lower surface layer (OTU1) could be less sensitive to the O 2 concentration.

In terms of relative abundance, the number of sequences of Methylosarcina sp.-related type I methanotrophs, group B6-related type X methanotrophs and Methylocystis-related type II methanotrophs was only marginal. This is consistent with the results obtained by [START_REF] Rahalkar | Comparison of aerobic methanotrophic communities in littoral and profundal sediments of Lake Constance by a molecular approach[END_REF] and [START_REF] Nercessian | Bacterial populations active in metabolism of C1 compounds in the sediment of Lake Washington, a freshwater lake[END_REF] from Lake Constance and Lake Washington, respectively. However, to date, the B6 group and Methylosarcina-related sequences were only described in freshwater sediments and not in the pelagic water column [START_REF] Pester | pmoA-Based analysis of methanotrophs in a littoral lake sediment reveals a diverse and stable community in a dynamic environment[END_REF][START_REF] Nercessian | Bacterial populations active in metabolism of C1 compounds in the sediment of Lake Washington, a freshwater lake[END_REF][START_REF] Rahalkar | Comparison of aerobic methanotrophic communities in littoral and profundal sediments of Lake Constance by a molecular approach[END_REF]. Concerning type II methane oxidizers, it is generally assumed that they thrive in environments with high CH 4 and low O 2 concentrations [START_REF] Hanson | Methanotrophic bacteria[END_REF]. This is challenged by our results and those of several recent studies [START_REF] Knief | Response and adaptation of different methanotrophic bacteria to low methane mixing ratios[END_REF][START_REF] Mohanty | Differential effects of nitrogenous fertilizers on methaneconsuming microbes in rice field and forest soils[END_REF]. In our study, Methylocystis sp. was only recovered at 20 m, a zone that is O 2 rich, but almost entirely CH 4 depleted. Therefore, this finding may reflect a limited activity of Methylocystis sp. in CH 4 oxidation in this ecosystem. Moreover, the distribution of all these phylotypes along the oxic water column did not appear to be random, with their disappearance at the same time as the decrease in the O 2 concentration (Fig. 7). Finally, unlike Methylobacter, no transcript was detected for these phylotypes. This suggests that either the pmoA genes of these methanotrophs were not expressed or that their transcripts were present at levels below the detection limit of RT-PCR. A third explanation could be that these populations used another carbon source such as methanol or acetate [START_REF] Dunfield | Methylocapsa aurea sp. nov., a facultative methanotroph possessing a particulate methane monooxygenase, and emended description of the genus Methylocapsa[END_REF][START_REF] Belova | Acetate utilization as a survival strategy of peat-inhabiting Methylocystis spp[END_REF] and did not therefore express pmoA.

Fig. 1 .

 1 Fig. 1. Cross-section on Lake Pavin showing the location of sampling.

  (63, 65, 68 m and then every 5 m from 70 to 90 m) and two from sediments (40 and 92 m). Three additional clone libraries consisting of 67 clones were also constructed from cDNA samples collected in 2009 (70 m, 90 m and sediments at 92 m).

Fig. 2 .

 2 Fig. 2. Vertical profiles of DO, C25, temperature and CH 4 concentration along the water column of the Lake Pavin in July 2007 (a) and May 2009 (b).

Fig. 3 .

 3 Fig. 3. Evolutionary distance tree showing the phylogenetic relationship of the deduced McrA amino acid sequences including the representative sequences derived from this study and sequences of isolates and uncultivated organisms. Phylogenetic analyses were conducted in MEGA4[START_REF] Tamura | MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0[END_REF]. Evolutionary history was inferred using the neighbor-joining method[START_REF] Saitou | The neighbor-joining method: a new method for reconstructing phylogenetic trees[END_REF]. The evolutionary distances were computed using the Poisson correction method and are in the units of the number of amino acid substitutions per site. All positions containing gaps and missing data were eliminated from the dataset (complete deletion option). There were a total of 127 positions in the final dataset. Bootstrap values 4 70% derived from 1000 replicates are indicated at the nodes. The number of clones assigned to each OTU is given in brackets together with the name of the representative clone used in this study. Methanopyrus kandleri sequence (AAB02003) was used as an outgroup. Arrow indicates the unique closest cultured methanogen species to environmental Methanomicrobiales sequences. Arrow indicates the species Candidatus Methanoregula boonei, which is the unique cultured species closely related to environmental sequences identified in this study. , Phylotype clustering gDNA and cDNA sequences; , phylotype with only a cDNA sequence.

Fig. 4 .

 4 Fig. 4. Distribution pattern of the different OTUs related to the Methanomicrobiales order along the water column and in sediments. (a) Sequences retrieved from gDNA libraries. (b) Sequences retrieved from cDNA libraries.

Fig. 5 .

 5 Fig. 5. Distribution of sequences affiliated with the two OTUs related to the Methanosarcinales for each library. (a) Sequences retrieved from gDNA libraries. (b) Sequences retrieved from cDNA libraries.

Fig. 6 .

 6 Fig.6. Evolutionary distance tree showing the phylogenetic relationship of the deduced PmoA amino acid sequences including representative sequences derived from this study and sequences of isolates and uncultivated organisms. Phylogenetic analyses were conducted in MEGA4[START_REF] Tamura | MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0[END_REF]. The evolutionary history was inferred using the neighbor-joining method[START_REF] Saitou | The neighbor-joining method: a new method for reconstructing phylogenetic trees[END_REF]. The evolutionary distances were computed using the Poisson correction method and are in the units of the number of amino acid substitutions per site. All positions containing gaps and missing data were eliminated from the dataset (complete deletion option). There were a total of 139 positions in the final dataset. Bootstrap values 4 70% derived from 1000 replicates are shown at nodes. The number of gDNA and cDNA clones assigned to each OTU is given in brackets, together with the name of the representative clone used in this study. Nitrospira sp. Enl299 sequence (ABM54176) was used as an outgroup. On the right, the name of the representative clone used for each phylotype is indicated.

Fig. 7 .

 7 Fig. 7. Relative composition of pmoA clone libraries generated from gDNA samples at different depths along the water column of Lake Pavin. The sequences related to Methylobacter sp. and the sequences related to group B6 were broadly distributed through the water column, whereas Methylocystis and Methylosarcina sp. were specific to certain layers. The percentage of clones calculated for each depth is presented.

Fig. 8 .

 8 Fig. 8. Distribution pattern of transcripts along the water column for OTU1 and OTU2, both related to the Methylobacter genus. OTU2 was dominant up to 55 m and OTU1 from 55 to 65 m.

Fig. 9 .

 9 Fig. 9. Percentage contribution of 16S rRNA gene sequences in the water column of Lake Pavin assigned to the main bacterial phyla.

Table 1 .

 1 Primer sets and PCR conditions used to amplify pmoA, mcrA and 16S rRNA gene markers

				Annealing		Expected
	Amplification	Primers	Sequence (5 0 -3 0 )	temperature ( 1C)	No. of cycles	size (bp)	References
	pmoA	pmoA189f	GGNGACTGGGACTTCTGG	55	40 (DNA)	$500	Costello & Lidstrom (1999)
		mb661r	CCGGMGCAACGTCYTTACC
	mcrA	MM_01	TAYATGTCIGGYGGTGTHGG	48	30 (cDNA)	$500	Mihajlovski et al. (2008)
		MM_02	ACRTTCATIGCRTAGTTIGG
	16S rRNA gene	27F	AGAGTTTGATCMTGGCTCAG	59	30 (DNA)	$1500	Lane (1991)
		1492R	AGGRTACCTTGTTACGACTT

FEMS Microbiol Ecol 77 (2011) 533-545 FEMS Microbiology Ecology c 2011 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. No claim to original French government works

Acknowledgements

We thank Yves Gamblin and Antonio Vieira from the IPGP mechanics workshop for custom-building the 1-L syringe water sampler. We also thank Maxime Ossédat for his efficient technical assistance. This study is supported by grants from Région Auvergne, from Clermont Communauté, from the PRAI e-nnovergne LifeGrid program and from the French National Research Agency (METHANOX and METHANOLAC programs). The contribution number is IPGP: 2642.


Laurent Philippot
email: laurent.philippot@dijon.inra.fr

Karl Ritz

Pascal Pandard

Sara Hallin

Fabrice Martin-Laurent

Standardisation of methods in soil microbiology: progress and challenges

Keywords: standardisation, DNA, ISO, soil, microorganisms, ecology

A plethora of methods have been developed over the few last decades to enable a better understanding of the ecology of soil microbial communities and their roles in soil functioning. However, there is generally considerable variation (both subtle and more extensive) in the actual realisation of these methods, and limited efforts have been devoted to their standardisation, despite this being crucial to underpin data comparison and integration. Ensuring comparable data across studies through standardisation is arguably best-practice, as well as necessary to effectively meet the objectives of various schemas, which require assessment of the consequences of the global change and intensification of human activities on the functioning of the soil ecosystem and its biological diversity. This article presents an overview of the existing and forthcoming ISO standards in soil microbiology and highlights possible future research efforts to be undertaken for developing new standards. We also discuss some practical and theoretical bottlenecks and hurdles that have limited standardisation in soil microbiology up to now.

Introduction

Microorganisms in soil ecosystems are ubiquitous, abundant, diverse and essential for many soil functions such as carbon and nitrogen cycling, plant productivity and climate regulation [START_REF] Whitman | Prokaryotes: the unseen majority[END_REF][START_REF] Torsvik | Prokaryotic diversitymagnitude, dynamics, and controlling factors[END_REF][START_REF] Falkowski | The microbial engines that drive Earth's biogeochemical cycles[END_REF][START_REF] Van Der Heijden | The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems[END_REF][START_REF] Bodelier | Towards understanding, managing and protecting microbial ecosystems[END_REF]. Because of their importance, there is a large volume of past and contemporary researches that aims to understand the ecology of soil microbial communities, with thousands of articles devoted to this research field published annually. Numerous methods have been developed to estimate abundance, diversity and activity of soil microorganisms. Several such procedures are now successfully applied on a regular and on-going basis, perhaps most notably the chloroform fumigation-extraction technique for estimating microbial biomass [START_REF] Vance | An extraction method for measuring soil microbial biomass-C[END_REF], and DNA fingerprinting approaches for estimating the structure of microbial communities. Perversely, many of these methods become victims of their own success, and a plethora of laboratory-or even user-specific protocols, which contain minor to major modifications of the initially described methods, are now used worldwide. However, these differences between protocols are far from being inconsequential as they often include inherent bias, which hamper data comparison across studies, let alone laboratories. Indeed, variations in data obtained by different laboratories or using different protocols are commonly reported [START_REF] Ocio | An evaluation of methods for measuring the microbial biomass in soils following recent additions of wheat straw and the characterization of the biomass that develops[END_REF][START_REF] Beck | An inter-laboratory comparison of ten different ways of measuring soil microbial biomass C[END_REF][START_REF] Krsek | Comparison of different methods for the isolation and purification of total community DNA from soil[END_REF][START_REF] Martin-Laurent | DNA extraction from soils: old bias for new microbial diversity analysis methods[END_REF][START_REF] Creamer | An interlaboratory comparison of multi-enzyme and multiple substrate-induced respiration assays to assess method consistency in soil monitoring[END_REF][START_REF] Pan | Impact of inter-and intralaboratory variation on the reproducibility of microbial community analyses[END_REF]. A theoretically obvious, albeit practically challenging, solution is to define and use standardised methods. This is becoming all the more important because an exponentially increasing volume of data is now being generated, particularly with the advent of automated or high-throughput techniques, notably in relation to molecular biology. Such techniques offer exciting opportunities for better understanding soil microbial diversity, how it relates to soil functions, and more effective ways to manage terrestrial ecosystems to meet the challenges of sustainability. This grand challenge should be facilitated by ensuring compa-rable data, which is necessary in order that our knowledge of soil microbial communities can be effectively integrated.

The concept, and practice, of standardisation in soil microbiological assays can be applied at a range of levels, from the individual researcher/group (vital to ensure coherence within a body of experimentation), through institutional (assists integration and coherence within institutional-level programmes), to national (e.g. British Standards and French National Organisation for Standardisation) and international [e.g. International Organisation for Standardisation, (ISO)]. Here we focus on the latter context, as this is arguably the most effective route to achieve the higher-level aims of standardisation. Moreover, science itself is an international collaborative effort and comparisons across studies need to be performed beyond country borders, not least because soils and the organisms they support operate entirely independently of such boundaries. Standards providing internationally agreed methods for assessing soil microorganisms have mostly been developed by the International Organisation for Standardisation (ISO). However, the number of ISO standardised methods is still scant in relation to the numerous methods that have been developed within the field of soil microbiology. In addition, the use of ISO methods in soil microbiology research articles, outside of ecotoxicology studies, is in our perception relatively rare. In this article, we underline the importance of standardisation in soil microbiology, present an overview of the existing and forthcoming ISO standards, and discuss some technical and cultural hurdles. One aim is to stimulate debate in this field and to encourage a move toward the development and greater dissemination of internationally agreed standards in soil microbiology.

Standardisation in soil microbiology: dealing with the natural complexity and diversity

Soils are arguably the most complex systems on the planet, given the extraordinary diversity of their chemical and biological constituents, as well as the extreme structural heterogeneity [START_REF] Ritz | Soil as a paradigm of a complex system[END_REF]. There are also a wide range of soil types, with huge numbers of classes of soil recognised in taxonomic schemes both at global down to national scales, for example, some 748 Soil Series are recognised in the Soil Survey of England and Wales [START_REF] Clayden | Critieria for differentiating soil series[END_REF] and thousands of types in the lower-order taxa of World Reference Base (FAO, 2006). The geo-spatial distribution of soils is also complex across virtually all size scales, which means that studies at almost any spatial scale involve a variety of soil types, which may confound the ready application of standard techniques. This diversity of constitution and basic characteristics severely challenges the ability to set standards in measuring soil properties and processes. This is particularly true for biological aspects of soil systems, and in part accounts for the concomitant diversity in methodological variants. Even something as outwardly straightforward as determining soil organic carbon is confounded by the fact that soils can vary from essentially 0-100% organic matter, there is potential (and variable) interference from inorganic forms of carbon, and the same procedure is certainly not appropriate for soils at the two extremes [START_REF] Nelson | Total carbon, organic carbon and organic matter[END_REF]. It is often then the case that no single method is universally appropriate and that variants within methods are needed to compensate for differences in properties that may occur if they are to be applicable to the gamut of soils. For example, measuring soil respiration by CO 2 emission is relatively straightforward if the pH of the soil is lower than 7.5, but in more alkaline soils, the partition coefficient of CO 2 between air and water starts to confound the technique because proportionately more CO 2 will prevail in the pore water [START_REF] Anderson | Soil respiration. Methods of Soil Analysis[END_REF]. The quality and quantity of organic matter and clay vary between soils that affects the nature and extent of potential absorption of biochemicals, notably nucleic acids, such that a range of devices to counter such effects need to be applied, contingent on the soil. These factors can be compensated for by variants in technique, and such variants can be duly standardised. In principle, such matters do not then preclude the setting of standards, but they certainly prevent the setting of simple standards. Furthermore, there is a significant issue that affects data comparability, as with complex protocols, there is an increased likelihood that different operators will determine different absolute values for measurements, because of accumulations of even subtle differences between each of the steps in such procedures.

Another factor arising from the need for sophisticated/ adjusted/complex protocols is the ease with such protocols are agreed upon within the context of a standards setting framework, particularly an international one. This is because the optimal procedures are not necessarily readily defined and can become more a matter of best judgement. For example, it can be argued either way that the pH of the buffer medium in enzyme assays should be standardised to a particular pH, or the pH of the particular soil under scrutiny [START_REF] German | Optimization of hydrolytic and oxidative enzyme methods for ecosystem studies[END_REF], but there are then supplementary issues of how to determine that pH. Another concern is at which temperature one should measure soil respiration? The same for a sub-arctic tundra soil as one from Namibia or a 'locally pertinent' temperature? And then what moisture content is optimal for respiration measurements and how should that be determined? Such questions are undoubtedly very important

Current standards in soil microbiology

Despite the inherent complexity and diversity of soils described earlier, some methods to study soil microorganisms have been standardised since 1997 (Table 1). Due to a strong concern regarding the degradation of soils in relation to local and diffuse contamination or loss of biodiversity, the existing standards were developed by the 'Soil quality' Technical Committee ISO/TC 190 with a strong focus on assessing the effects of chemicals and pollution on the soil fauna and soil microorganisms [START_REF] Nortcliff | Standardisation of soil quality attributes[END_REF]. Methods for measuring soil microbial biomass using substrate-induced respiration and fumigation-extraction were the first ones to be standardised in the field of soil microbiology in the late nineties (ISO 14240, Table 1). Indeed, these methods based on pioneering work of [START_REF] Vance | An extraction method for measuring soil microbial biomass-C[END_REF] were proposed to provide a sensitive indicator for measuring changes in the total quantity of soil microorganisms in response to environ- 1). This trend is particularly obvious for ISO 14238 'Determination of nitrogen mineralisation and nitrification in soils and the influence of chemical on these processes' and ISO 15473 'Testing for biodegradation of organic chemicals in soil'. Thus, ISO 14238 was designed to determine the effects of different concentrations of a chemical on the N-cycling processes using dose-response curves while ISO 15473 gives general guidelines for the selection and method of tests to determine the biological degradation of organic chemicals introduced into the soil either intentionally or accidentally.

Criteria related to applicability and effectiveness of standards for routine analyses such as high throughput analysis, cost, usability or data interpretation have up to now excluded molecular methods, such as terminal fragment length polymorphism for assessing microbial diversity, despite their widespread use in research. However, among the new ISO standards, the development of the ISO 11063 standard for soil DNA extraction [START_REF] Petric | Inter-laboratory evaluation of the ISO standard 11063 "Soil quality -Method to directly extract DNA from soil samples[END_REF] is of special interest because it is the first step of all PCR-, hybridisation, and sequencing-based molecular analyses of the diversity and abundance of soil microbial communities. As a result, thousands of studies are performed yearly in environmental microbiology using soil DNA extraction methods. Due to this important business market, at least ten companies are commercialising soil DNA extraction kits, which add to the list of home-made protocol. This is despite it being well established that the apparent microbial diversity determined by any nucleic acid analysis procedure is contingent on the DNA extraction method [START_REF] Frostega ˚rd A ˚ | Quantification of bias related to the extraction of DNA directly from soils[END_REF][START_REF] Martin-Laurent | DNA extraction from soils: old bias for new microbial diversity analysis methods[END_REF][START_REF] Deliphtay | Impact of DNA extraction method on bacterial community composition measured by denaturing gradient gel electrophoresis[END_REF][START_REF] Feinstein | Assessment of bias associated with incomplete extraction of microbial DNA from soil[END_REF][START_REF] Pan | Impact of inter-and intralaboratory variation on the reproducibility of microbial community analyses[END_REF][START_REF] Delmont | Accessing the soil metagenome for studies of microbial diversity[END_REF]. The ISO 11063 standard for soil DNA extraction is based on both chemical and physical approaches for extraction and lyses of the microbial cells as described by [START_REF] Petric | Inter-laboratory evaluation of the ISO standard 11063 "Soil quality -Method to directly extract DNA from soil samples[END_REF]. This ISO is timely since studies of soil microbial diversity based on soil DNA extraction are generating an exponential amount of sequence data, and large scale projects aiming at sequencing the soil metagenome are now launched [START_REF] Vogel | TerraGenome: a consortium for the sequencing of a soil metagenome[END_REF]. Knowledge of the identity and the quantity of each compound used in the ISO 11063 or any ISO protocol provides transparency and allow users a complete quality control, which is a major advantage over commercial kits. Thus, production batch effects can occur, and this has been observed for some commercial soil DNA extraction kits (unpublished data). A transparent protocol also avoids the risk of subsequent modifications of the kit reagents by companies or risks associated to the versatility of their business strategies such acquisition and merging, which are common activities for biotechnology industry.

While no nucleic acid-based method for assessing soil microbial diversity have yet been proposed for international standardisation, two lipid-based methods have recently became ISO standards (Table 1). Phospholipid fatty acid (PLFA) and phospholipid ether lipids (PLEL) analyses are rapid and inexpensive methods for providing a quantitative measure of the viable soil biomass and complex microbial community profiles. They offer the advantage of targeting the entire microbial community, thus allowing calculation of the fungal/bacteria ratio using markers PLFA specific of these domains [START_REF] Frostega | The use of phospholipid fatty acid analysis to estimate bacterial and fungal biomass in soil[END_REF]. Since the late 1990s, several comprehensive reviews discussing the strengths and weaknesses of the use of lipid fatty acids for assessing microbial biomass and community structure in soil have been published [START_REF] Olsson | Signature fatty acids provide tools for determination of the distribution and interactions of mycorrhizal fungi in soil[END_REF][START_REF] Zelles | Fatty acid patterns of phospholipids and lipopolysaccharides in the characterisation of microbial communities in soil: a review[END_REF][START_REF] Kaur | Phospholipid fatty acida bioindicator of environment monitoring and assessment in soil ecosystem[END_REF][START_REF] Frostega ˚rd A ˚ | Use and misuse of PLFA measurements in soils[END_REF]. Unfortunately, while some of the ISO standards described in Table 1 have been published more than 10 years ago, their use by the scientific community is still very limited. Thus, the ISO has no power to enforce the implementation of the standards it develops and therefore adoption of the ISO standard is still mainly voluntary.

Directions for future standards

The standardisation effort is uneven between methods addressing the abundance, the diversity and the activity of the soil microbial community. Indeed, while there are already three ISO standards for quantifying soil microbial biomass, a new work item proposing a standard to estimate the abundance of the soil bacterial community by 16S rRNA gene targeted quantitative PCR (qPCR) was recently adopted by the Soil quality ISO technical committee (Australia, September 2011). The recent developments of qPCR analyses also allow the quantification of the abundances of specific functional or taxonomical microbial groups, which may represent useful bioindicators [START_REF] Wessen | Abundance of archaeal and bacterial ammonia oxidizerspossible bioindicator for soil monitoring[END_REF]. With the use of appropriate blanks, internal and surrogate standards, qPCR is a reliable method having the advantage to offer high throughput and cost-effective analyses.

For a better understanding of soil microbial activity, or more generally of soil functioning, several methods for quantifying potential enzyme activity have been developed. Even though these methods providing an insight of the size of the enzyme pool have some limits [START_REF] Wallenstein | Emerging tools for measuring and modeling the in situ activity of soil extracellular enzymes[END_REF], they are commonly used as microbiological indicators of soil quality and should therefore be ª 2012 Federation of European Microbiological Societies FEMS Microbiol Ecol 82 (2012) 1-10 Published by Blackwell Publishing Ltd. All rights reserved standardised for comparison of microbial activities both between soils and laboratories. For example, because of their environmental and agronomical importance, microorganisms involved in N-cycling are of key interest. In addition, they are popular models in soil microbial ecology for relating microbial diversity and soil functioning. However, only measurement of potential nitrification has been internationally standardised up to now, while methods for monitoring other N-processes such as nitrogen fixation and denitrification also necessitate standardisation. For example, the original protocol for estimating potential denitrification [START_REF] Smith | Phases of denitrification following oxygen depletion in soil[END_REF] has been modified in many ways. In this assay, to measure the activity of the pool of denitrification enzymes in the soil at the time of sampling, soil slurries are incubated in the laboratory in non-limiting denitrification conditions (without oxygen, addition of nitrate and carbon, and of chloramphenicol to avoid de novo synthesis) so that only the amount of enzyme is rate-limiting. Changes in the original protocol include excluding the chloramphenicol, which can decrease the activity of synthesized enzymes, addition of different carbon types and amount (glucose, acetate, glumatic acid, etc) and incubation of the soil slurries in various conditions. Similarly, determination of the nitrogenase activity using the acetylene reduction technique [START_REF] Hardy | The acetylene-ethylene assay for N 2 fixation: laboratory and field evaluation[END_REF]) is subjected to various modifications of the protocol resulting, for example, in variants of the acetylene concentration (0.03-0.1 v/v). In contrast to other methods, most modifications of these methods are not soil-specific and both potential denitrification and nitrogen-fixation assays could readily be standardised in future.

Finally, regarding methods to monitor the diversity and the structure of the soil microbial community, the adoption of the ISO 29843 for PLFA and PLEL analyses opens the path for other standards. While it is too early to propose any standardisation of the new high-throughput sequencing technologies (e.g. 454 pyrosequencing, etc…), other powerful approaches such as those based on taxonomic and functional microarrays meet the criteria to become standards. Of course these perspectives for the development of future standards in soil microbiology are not exhaustive, and we encourage soil microbiologists to expand it by proposing other popular methods for standardisation.

The ISO standardisation process

If one is interested in developing new international standards, it is worth reviewing how standards are developed within the ISO framework. According to ISO, a standard is a document that is established by consensus and approved by a recognised body (ISO/IEC, 2004). It provides, for common and repeated use, rules, guidelines or characteristics for activities or their results, aimed at the achievement of the optimum degree of order in a given context. Standards should be based on the consolidated results of science, technology and experience, and aimed at the promotion of optimum community benefits (ISO/ IEC, 2004). Different types of standards can be developed within this framework (e.g. terminology, product, process, service, testing standards). Such standards are elaborated by technical committees and/or subcommittees that usually comprise representatives from the industrial, technical, business sectors as well as representatives of government agencies, testing laboratories, consumer associations, nongovernmental organizations and academia.

The standardisation process includes six successive stages, taking place over a time period usually not exceeding 48 months: viz. proposal, preparatory, committee, enquiry, approval and publication stages (ISO/IEC, 2009) (Fig. 1). To confirm the need for the development of a new standard, the new work item proposal should be supported by scientific papers presenting the scientific background, and some results demonstrating the applicability and the relevance of the method. A proposal is accepted when at least five participating countries vote positively and nominate experts to participate actively in Step 3: Commitee stage

Development and acceptance of a committee draft (CD) describing all the technical aspects of the standard

Step 4: Enquiry stage

Enquiry on the draft standard (DIS) revised according to the results of the interlaboratory test

Step 5: Approval stage

Approval of final draft (FDIS)

Step 6: Publication stage Publication of the international standard (IS)

Acceptance of the new work item (5 countries which vote positively and 5 experts nominated)

Interlaboratory test for assessing the reproducibility of the method

The form should be submitted with additional information (preferably peer-reviewed articles): Scientific relevance of the method, improvement compared to other accepted methods, sensitivity , scope of application… Standardisation in soil microbiology its development. The first draft of the method is submitted to the experts for discussion and improvements until a consensus has been reached on the technical content. Then, the draft document is distributed for voting and comments by the participating countries of the technical or sub-committees. In case of major disagreements, successive committee drafts may be considered before submission of the text as a draft international standard.

The validation process of a future standard is crucial before publication as an international standard. It involves laboratories from National Bodies of the relevant technical or sub-committees (but not exclusively) for evaluation of the reproducibility of the test method under standardisation. The resulting performance characteristics of this inter-laboratory trial are part of the standard. When all due processes have been satisfactorily completed, the standard is then officially published and released for adoption. International standards are then reviewed at the least 3 years after publication and every 5 years after the first review by all the ISO member bodies to incorporate, in particular, improvements of the method or technical changes. During this review process, members of the technical or sub-committees decide whether the standard should be confirmed, revised or withdrawn.

Fictitious, cultural and real hurdles

As underlined by [START_REF] Pan | Impact of inter-and intralaboratory variation on the reproducibility of microbial community analyses[END_REF], inter-calibration of protocols is not a common practice in environmental microbiology. As a consequence, while an impressive list of methods, regularly summarised in books, has been developed for studying microorganisms in soils, limited effort has been devoted to standardisation. This paradox is accentuated by the fact that most of these methods are subjected to almost endless modifications of their protocols, which can affect the results and hamper data comparison. These subtle to deep changes can be as a result of weaknesses in the original protocols, which are often related to a failure when applied to a different soil. However, a large number of variations in protocols can still be found in the literature for similar or even identical soils. One could therefore ask whether the existence of so many deviating protocols only reflects a true need for modifications because of the overwhelming diversity and complexity of the soils, or if there are other factors involved conveyed by a certain lack of rigor.

Possibly the fact that soil microbiology is still facing an tremendous and ongoing method development can be considered as contradictory to developing standards. However, evolving fields with technological evolution, new methods or new quality and safety requirements are not an obstacle to standardisation. Indeed, in biomedical science, laboratory-based medical and scientific microbiologists from throughout the Health Protection Agency in Scotland have developed the National Standards Methods, which include, for example, a standard for the detection of influenza viruses by qPCR. Within the ISO, all existing standards are reviewed at intervals of not more than 5 years to evaluate whether a revision is required. This is, for example, the case of the ISO 15685 'Determination of potential nitrification and inhibition of nitrificationrapid test by ammonium oxidation', which was revised in 2011.

Another obstacle could be the naı ¨ve thinking that certain of our methods are inadequate for standardisation. It is essential that standardised methods provide meaningful information, but not that they are 'perfect'. In soil microbiology, such perfection would apply to an assay that provides a true picture of microorganisms' activity, diversity or abundance in the soil. Given the complexity of the soil system and inherent biodiversity, this may in any case be untenable. As the accuracy of any method in soil microbiology cannot be estimated directly but only through the prism of other methods, microbiologists are facing a potentially unsolvable paradox. In addition, sample-specific optimisation of methods can lead to 'nearsightedness', the more detailed description of the studied soil being at the price of not seeing the bigger picture because of the impossibility to compare and integrate data across studies.

Evaluation of the best protocol to standardise is also often hampered by a trade-off situation in which one advantage is lost for another. An example of such a circumstance is the trade-off in relation to soil DNA extraction where the DNA yield can be increased, but typically at the cost of lower quality which may then compromise its apparent representativity, particularly where annealing processes are important.

Final remarks

In the recent years, increasing efforts have been made to promote consistency among laboratories. These efforts were mostly devoted to improving standardisation and transparency in metadata capture and exchange such as the minimum information about a genome sequence [START_REF] Field | The minimum information about a genome sequence (MIGS) specification[END_REF], the minimum information about a marker gene sequence [START_REF] Yilmaz | Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications[END_REF] or the genomic standards consortium: bringing standards to life for microbial ecology [START_REF] Yimaz | The genomic standards consortium: bringing standards to life for microbial ecology[END_REF]. As protocols continue to evolve and diversify, guidance modules for reporting in a standardised manner, the use of techniques have also been described. Thus, the lack of consensus on how to perform qPCR experiments has led [START_REF] Bustin | The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments[END_REF] to propose the minimum information for publication of quantitative real-time PCR experiments (MIQE) guidelines. There are several precedents such as the minimum ª 2012 Federation of European Microbiological Societies FEMS Microbiol Ecol 82 (2012) 1-10 Published by Blackwell Publishing Ltd. All rights reserved information about a proteomics experiment [START_REF] Taylor | The minimum information about a proteomics experiment (MIAPE)[END_REF] or the minimum information about a microarray experiment (MIAME) [START_REF] Brazma | Minimum information about a microarray experiment (MIAME) toward standards for microarray data[END_REF]. The MIAME is now an accepted reference as the reflected by the number of citations, which exceed 1600 (ISI Web of Knowledge). These efforts also highlight that there are other paths for standardisation than the ISO. However, standardisation should proceed within the auspices of international working bodies and be preferably in open access or with a very low cost to facilitate the dissemination within the scientific community. Standard adoption also requires both information and a stronger involvement of leading researchers within the field. There is a clearly a need and room for new standards in soil microbiology. New standards would be beneficial to researchers, nongovernmental organisations, governments, farmers and other land managers, for better monitoring soil quality and understanding of soil functioning. Developing standard protocols in soil microbiology is crucial to meet the objectives of the Millennium Ecosystem Assessment (2005) and of the emerging EU Soil Framework Directive (Commission of the European Community, 2006) for assessing the consequences of the intensification of human activities on the functioning of the soil ecosystem and its biodiversity.

In conclusion, we argue that there is a need to avoid the perhaps inevitable procrastination in setting standards that arises from the range of issues discussed earlier, and we need to be pragmatic in getting standards accepted and implemented, with caveats duly acknowledged. There is a trade-off between the urge for perfect methods vs. standardised methods, and we believe that standardisation allowing data comparison across studies, and therefore facilitating the quest for 'unifying principles in soil ecology' as described by [START_REF] Fierer | Searching for unifying principles in soil ecology[END_REF], is more important than describing a few specific samples 'perfectly'. The rewards from such an approach would far exceed the drawbacks.

Step 1 :

 1 New work item proposalStep 2: Preparatory stage Preparation of working draft(s)studied and improved by the expert group (WD)

Fig. 1 .

 1 Fig. 1. Flow chart summarising the different steps for standardising a new test method within the ISO framework.

Table 1 .

 1 ISO standardised methods in soil microbiology Most of the other existing ISO standards were developed for similar purposes and are therefore biased toward effective monitoring of the soil microbial community to meet extant policy requirements (Table

	Year	Method	ISO reference	Bibliography
	1997	Determination of soil microbial biomass -part 1:	ISO 14240-1	Jenkinson & Powlson (1976); Anderson & Domsch
		substrate-induced respiration method		(1978)
	1997	Determination of soil microbial biomass -part 2:	ISO 14240-2
		fumigation-extraction method
				Alef &
				Nannipieri (1995)
	2002	Laboratory methods for determination of microbial	ISO 16072	Gupta & Singh (1977); Nordgren (1988); Watts et al.
		soil respiration		(2000)
	2004 UR	Determination of potential nitrification and	ISO 15685	Belser & Mays (1980); Hansson et al. (1991); Stenberg
		inhibition of nitrification -rapid test by		et al. (1998); Winkel et al. (1999)
		ammonium oxidation
	2005	Determination of dehydrogenase activity in soils -	ISO 23753-1	Thalmann (1968); Glathe & Thalmann (1970); Wilke
		part 1: method using triphenyltetrazolium chloride		(1982); Ohlinger (1995)
		(TTC)
	2005	Determination of dehydrogenase activity in soils -	ISO 23753-2	Thalmann (1968); Glathe & Thalmann (1970); vonMersi
		part 2: method using iodotetrazolium chloride		& Schinner (1991); Spothelfer-Magan ˜a et al. (1993);
		(INT)		Fuchs et al. (1994); Ohlinger (1995)
	2010	Measurement of enzyme activity patterns in soil	ISO 22939	Tabatabai (1994); Stemmer et al. (1998); Marx et al.
		samples using fluorogenic substrates in micro-well		(2001); Vepsa ¨la ¨inen et al. (2001, 2004); Marx et al.
		plates		(2005); Niemi & Vepsalainen (2005)
	2010	Determination of soil microbial diversity -part 1:	ISO 29843-1	Blight & Dyer (1959); White et al. (1979); Findlay et al.
		method by PLFA analysis and PLEL analysis		(1990); Frostega ˚rd et al. (1991); Zelles & Bai (1993);
				Alef & Nannipieri (1995); Zelles (1999); Gattinger
				et al. (2003)
	2011	Determination of soil microbial diversity -part 2:	ISO 29843-2	Blight & Dyer (1959); White et al. (1979); Zelles & Bai
		method by PLFA analysis using the 'simple PLFA		(1993); Gattinger et al. (2003)
		extraction method'
	2011

[START_REF] Brookes | Chloroform fumigation and the release of soil-nitrogen -a rapid direct extraction method to measure microbial biomass nitrogen in soil[END_REF]

;

[START_REF] Vance | An extraction method for measuring soil microbial biomass-C[END_REF]

;

[START_REF] Ocio | An evaluation of methods for measuring the microbial biomass in soils following recent additions of wheat straw and the characterization of the biomass that develops[END_REF]

;

[START_REF] Sparling | Estimation of soil microbial C by a fumigation extraction method -use on soils of high organic-matter content, and a reassessment of the K ec -factor[END_REF]

;

[START_REF] Wu | Measurement of soil microbial biomass C by fumigation extractionan automated procedure[END_REF]

;

[START_REF] Inubushi | Soil microbial biomass C, N and ninhydrin-N in aerobic and anaerobic soils measured by the fumigation-extraction method[END_REF]

;

[START_REF] Mueller | Estimation of soil microbial biomass-C in the presence of living roots by fumigation extraction[END_REF]

;

Harden et al. (1993a, b)

1997 Determination of nitrogen mineralization and nitrification in soils and the influence of chemicals on these processes ISO 14238 Bremner (1965); Henriksen & Selmer-Olsen (1970); Selmer-Olsen (1971); Stanford & Smith (1972); Andersch & Anderson (1991) 2002 Determination of abundance and activity of soil microflora using respiration curves ISO 17155 Anderson & Domsch (1978); Nordgren et al. (1988); Arnebrant & Schnurer (1990); Chander & Brookes (1991); VanBeelen et al. (1991); Stenstrom et al. (1998); Wilke et al. (1998) 2002 Soil qualityguidance on laboratory testing for biodegradation of organic chemicals in soil under anaerobic conditions ISO 15473 Beland et al. (1974); Gowda & Sethunathan (1976); Healy & Young (1979); Attaway et al. (1982); Kearney (1982); Shelton & Tiedje (1984); Ward (1986); UP Method to directly extract DNA from soil samples ISO 11063 Tsai & Olson (1991); Smalla et al. (1993); Zhou et al. (1996); van Elsas et al. (2000); Martin-Laurent et al. (2001); Niemi et al. (2001) UR, under revision; UP, under publication. FEMS Microbiol Ecol 82 (2012) 1-10 ª 2012 Federation of European Microbiological Societies Published by Blackwell Publishing Ltd. All rights reserved Standardisation in soil microbiology mental factors or anthropogenic disturbances.

Acknowledgements

We would like to thank many colleagues who have, directly or indirectly, contributed to the ideas presented in this work. This work was partly supported by the European Commission within EcoFINDERS project (FP7-264465) and the Ecofun Microbiodiv project (FP7 ERA NET 216/01).