Lionel Ranjard

Characterization of Bacterial and Fungal Soil Communities by Automated Ribosomal Intergenic Spacer Analysis Fingerprints: Biological and Methodological Variability

ABSTRACT Automated rRNA intergenic spacer analysis (ARISA) was used to characterise bacterial (B-ARISA) and fungal (F-ARISA) communities from different soil types. The 16S-23S intergenic spacer region from the bacterial rRNA operon was amplified from total soil community DNA for B-ARISA. Similarly, the two internal transcribed spacers and the 5.8S rRNA gene (ITS1-5.8S-ITS2) from the fungal rRNA operon were amplified from total soil community DNA for F-ARISA. Universal fluorescence-labeled primers were used for the PCRs, and fragments of between 200 and 1,200 bp were resolved on denaturing polyacrylamide gels by use of an automated sequencer with laser detection. Methodological (DNA extraction and PCR amplification) and biological (inter- and intrasite) variations were evaluated by comparing the number and intensity of peaks (bands) between electrophoregrams (profiles) and by multivariate analysis. Our results showed that ARISA is a high-resolution, highly reproducible technique and is a robust method for discriminating between microbial communities. To evaluate the potential biases in community description provided by ARISA, we also examined databases on length distribution of ribosomal intergenic spacers among bacteria (L. Ranjard, E. Brothier, and S. Nazaret, Appl. Environ. Microbiol. 66:5334–5339, 2000) and fungi.

Monitoring complex bacterial communities using culture-independent molecular techniques: application to soil environment.

Over the last decade, important advances in molecular biology led to the development of culture-independent approaches to describing bacterial communities. These new strategies, based on the analysis of DNA directly extracted from environmental samples, circumvent the steps of isolation and culturing of bacteria, which are known for their selectivity leading to a non-representative view of the extent of bacterial diversity. This review provides an overview of the potentials and limitations of some molecular approaches currently used in microbial ecology. Examples of applications to the study of indigenous soil microbial community illustrate the feasibility and the power of such approaches.

Comparison of nifH Gene Pools in Soils and Soil Microenvironments with Contrasting Properties

ABSTRACT The similarities and differences in the structures of thenifH gene pools of six different soils (Montrond, LCSA-p, Vernon, Dombes, LCSA-c, and Thysse Kaymor) and five soil fractions extracted from LCSA-c were studied. Bacterial DNA was directly extracted from the soils, and a region of thenifH gene was amplified by PCR and analyzed by restriction. Soils were selected on the basis of differences in soil management, plant cover, and major physicochemical properties. Microenvironments differed on the basis of the sizes of the constituent particles and the organic carbon and clay contents. Restriction profiles were subjected to principal-component analysis. We showed that the composition of the diazotrophic communities varied both on a large scale (among soils) and on a microscale (among microenvironments in LCSA-c soil). Soil management seemed to be the major parameter influencing differences in the nifH gene pool structure among soils by controlling inorganic nitrogen content and its variation. However, physicochemical parameters (texture and total C and N contents) were found to correlate with differences amongnifH gene pools on a microscale. We hypothesize that the observed nifH genetic structures resulted from the adaptation to fluctuating conditions (cultivated soil, forest soil, coarse fractions) or constant conditions (permanent pasture soil, fine fractions). We attempted to identify a specific band within the profile of the clay fraction by cloning and sequencing it and comparing it with the gene databases. Unexpectedly, the nifH sequences of the dominant bacteria were most similar to sequences of unidentified marine eubacteria.

Determinants of the distribution of nitrogen-cycling microbial communities at the landscape scale

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. However, a landscape perspective is needed to understand the relative importance of local and regional factors and land management for the microbial communities and the ecosystem services they provide. In the most comprehensive analysis of spatial patterns of microbial communities to date, we investigated the distribution of functional microbial communities involved in N-cycling and of the total bacterial and crenarchaeal communities over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 × 16 km2 sampling grid. At each sampling site, the abundance of total bacteria, crenarchaea, nitrate reducers, denitrifiers- and ammonia oxidizers were estimated by quantitative PCR and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time, and soil physico-chemical properties to the spatial distribution of the different communities were analyzed by canonical variation partitioning. Our results indicate that 43–85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of microbial communities at the landscape scale. The present study highlights the potential of a spatially explicit approach for microbial ecology to identify the overarching factors driving the spatial heterogeneity of microbial communities even at the landscape scale.

Heterogeneous Cell Density and Genetic Structure of Bacterial Pools Associated with Various Soil Microenvironments as Determined by Enumeration and DNA Fingerprinting Approach (RISA)

A bstractThe cell density and the genetic structure of bacterial subcommunities (further named pools) present in the various microenvironments of a silt loam soil were investigated. The microenvironments were isolated first using a procedure of soil washes that separated bacteria located outside aggregates (outer part) from those located inside aggregates (inner part). A nondestructive physical fractionation was then applied to the inner part in order to separate bacteria located inside stable aggregates of different size (size fractions, i.e., two macroaggregate fractions, two microaggregate fractions, and the dispersible day fraction). Bacterial densities measured by acridine orange direct counts (AODC) and viable heterotrophic (VH) cell enumerations showed the heterogeneous quantitative distribution of cells in soil. Bacteria were preferentially located in the inner part with 87.6% and 95.4% of the whole AODC and VH bacteria, respectively, and in the microaggregate and dispersible clay fractions of this part with more than 70% and 80% of the whole AODC and VH bacteria, respectively. The rRNA intergenic spacer analysis (RISA) was used to study the genetic structure of the bacterial pools. Different fingerprints and consequently different genetic structures were observed between the unfractionated soil and the microenvironments, and also among the various microenvironments, giving evidence that some populations were specific to a given location in addition to the common populations of all the microenvironments. Cluster and multivariate analysis of RISA profiles showed the weak contribution of the pools located in the macroaggregate fractions to the whole soil community structure, as well as the clear distinction between the pool associated to the macroaggregate fractions and the pools associated to the microaggregate ones. Furthermore, these statistical analyses allowed us to ascertain the influence of the clay and organic matter content of microenvironments on the genetic structure relatedness between pools.

Metaproteomics: A New Approach for Studying Functional Microbial Ecology

In the postgenomic era, there is a clear recognition of the limitations of nucleic acid-based methods for getting information on functions expressed by microbial communities in situ. In this context, the large-scale study of proteins expressed by indigenous microbial communities (metaproteome) should provide information to gain insights into the functioning of the microbial component in ecosystems. Characterization of the metaproteome is expected to provide data linking genetic and functional diversity of microbial communities. Studies on the metaproteome together with those on the metagenome and the metatranscriptome will contribute to progress in our knowledge of microbial communities and their contribution in ecosystem functioning. Effectiveness of the metaproteomic approach will be improved as increasing metagenomic information is made available thanks to the environmental sequencing projects currently running. More specifically, analysis of metaproteome in contrasted environmental situations should allow (1) tracking new functional genes and metabolic pathways and (2) identifying proteins preferentially associated with specific stresses. These proteins considered as functional bioindicators should contribute, in the future, to help policy makers in defining strategies for sustainable management of our environment.

Sequencing Bands of Ribosomal Intergenic Spacer Analysis Fingerprints for Characterization and Microscale Distribution of Soil Bacterium Populations Responding to Mercury Spiking

ABSTRACT Two major emerging bands (a 350-bp band and a 650-bp band) within the RISA (ribosomal intergenic spacer analysis) profile of a soil bacterial community spiked with Hg(II) were selected for further identification of the populations involved in the response of the community to the added metal. The bands were cut out from polyacrylamide gels, cloned, characterized by restriction analysis, and sequenced for phylogenetic affiliation of dominant clones. The sequences were the intergenic spacer between the rrs andrrl genes and the first 130 nucleotides of therrl gene. Comparison of sequences derived from the 350-bp band to The GenBank database permitted us to identify the bacteria as being mostly close relatives to low G+C firmicutes (Clostridium-like genera), while the 650-bp band permitted us to identify the bacteria as being mostly close relatives to β-proteobacteria (Ralstonia-like genera). Oligonucleotide probes specific for the identified dominant bacteria were designed and hybridized with the RISA profiles derived from the control and spiked communities. These studies confirmed the contribution of these populations to the community response to the metal. Hybridization of the RISA profiles from subcommunities (bacterial pools associated with different soil microenvironments) also permitted to characterize the distribution and the dynamics of these populations at a microscale level following mercury spiking.

Validation and Application of a PCR Primer Set to Quantify Fungal Communities in the Soil Environment by Real-Time Quantitative PCR

Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen® method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affected by length polymorphism and may provide sufficiently small targets, a crucial criterion for enhancing accuracy and reproducibility of the detection technique. An in silico analysis of 33 primer sets targeting the 18S rRNA gene was performed to select the primer set with the best potential for real-time Q-PCR: short amplicon length; good fungal specificity and coverage. The best consensus between specificity, coverage and amplicon length among the 33 sets tested was the primer set FR1 / FF390. This in silico analysis of the specificity of FR1 / FF390 also provided additional information to the previously published analysis on this primer set. The specificity of the primer set FR1 / FF390 for Fungi was validated in vitro by cloning - sequencing the amplicons obtained from a real time Q-PCR assay performed on five independent soil samples. This assay was also used to evaluate the sensitivity and reproducibility of the method. Finally, fungal abundance in samples from 24 soils with contrasting physico-chemical and environmental characteristics was examined and ranked to determine the importance of soil texture, organic carbon content, C∶N ratio and land use in determining fungal abundance in soils.

Turnover of soil bacterial diversity driven by wide-scale environmental heterogeneity

Spatial scaling and determinism of the wide-scale distribution of macroorganism diversity has been largely demonstrated over a century. For microorganisms, and especially for soil bacteria, this fundamental question requires more thorough investigation, as little information has been reported to date. Here by applying the taxa-area relationship to the largest spatially explicit soil sampling available in France (2,085 soils, area covered ~5.3 × 10(5) km(2)) and developing an innovative evaluation of the habitat-area relationship, we show that the turnover rate of bacterial diversity in soils on a wide scale is highly significant and strongly correlated with the turnover rate of soil habitat. As the diversity of micro- and macroorganisms appears to be driven by similar processes (dispersal and selection), maintaining diverse and spatially structured habitats is essential for soil biological patrimony and the resulting ecosystem services.

Molecular biomass and MetaTaxogenomic assessment of soil microbial communities as influenced by soil DNA extraction procedure

Three soil DNA extraction procedures (homemade protocols and commercial kit) varying in their practicability were applied to contrasting soils to evaluate their efficiency in recovering: (i) soil DNA and (ii) bacterial diversity estimated by 16S rDNA pyrosequencing. Significant differences in DNA yield were systematically observed between tested procedures. For certain soils, 10 times more DNA was recovered with one protocol than with the others. About 15 000 sequences of 16S rDNA were obtained for each sample which were clustered to draw rarefaction curves. These curves, as well as the PCA ordination of community composition based on OTU clustering, did not reveal any significant difference between procedures. Nevertheless, significant differences between procedures were highlighted by the taxonomic identification of sequences obtained at the phylum to genus levels. Depending on the soil, differences in the number of genera detected ranged from 1% to 26% between the most and least efficient procedures, mainly due to a poorer capacity to recover populations belonging to Actinobacteria, Firmicutes or Crenarchaeota. This study enabled us to rank the relative efficiencies of protocols for their recovery of soil molecular microbial biomass and bacterial diversity and to help choosing an appropriate soil DNA extraction procedure adapted to novel sequencing technologies.