Long-term intake of Lactobacillus helveticus enhances bioavailability of omega-3 fatty acids in the mouse retina.

Omega-3 (n-3) polyunsaturated fatty acids (PUFAs), particularly docosahexaenoic acid (DHA), are required for the structure and function of the retina. Several observational studies indicate that consumption of a diet with relatively high levels of n-3 PUFAs, such as those provided by fish oils, has a protective effect against the development of age-related macular degeneration. Given the accumulating evidence showing the role of gut microbiota in regulating retinal physiology and host lipid metabolism, we evaluated the potential of long-term dietary supplementation with the Gram-positive bacterium Lactobacillus helveticus strain VEL12193 to modulate the retinal n-3 PUFA content. A set of complementary approaches was used to study the impact of such a supplementation on the gut microbiota and host lipid/fatty acid (FA) metabolism. L. helveticus-supplementation was associated with a decrease in retinal saturated FAs (SFAs) and monounsaturated FAs (MUFAs) as well as an increase in retinal n-3 and omega-6 (n-6) PUFAs. Interestingly, supplementation with L. helveticus enriched the retina in C22:5n-3 (docosapentaenoic acid, DPA), C22:6n-3 (DHA), C18:2n-6 (linoleic acid, LA) and C20:3n-6 (dihomo gamma-linolenic acid, DGLA). Long-term consumption of L. helveticus also modulated gut microbiota composition and some changes in OTUs abundance correlated with the retinal FA content. This study provides a proof of concept that targeting the gut microbiota could be an effective strategy to modulate the retinal FA content, including that of protective n-3 PUFAs, thus opening paths for the design of novel preventive and/or therapeutical strategies for retinopathies.

Biogeographical patterns of the soil fungal:bacterial ratio across France.

Soils are one of the major reservoirs of biological diversity on our planet because they host a huge richness of microorganisms. The fungal:bacterial (F:B) ratio targets two major functional groups of organisms in soils and can improve our understanding of their importance and efficiency for soil functioning. To better decipher the variability of this ratio and rank the environmental parameters involved, we used the French Soil Quality Monitoring Network (RMQS)-one of the most extensive and a priori-free soil sampling surveys, based on a systematic 16 km × 16 km grid and including more than 2,100 samples. F:B ratios, measured by quantitative PCR targeting the 18S and 16S rDNA genes, turned out to be heterogenously distributed and spatially structured in geographical patterns across France. These distribution patterns differed from bacterial or fungal densities taken separately, supporting the hypothesis that the F:B ratio is not the mere addition of each density but rather results from the complex interactions of the two functional groups. The F:B ratios were mainly influenced by soil characteristics and land management. Among soil characteristics, the pH and, to a lesser extent, the organic carbon content and the carbon:nitrogen (C:N) ratio were the main drivers. These results improved our understanding of soil microbial communities, and from an operational point of view, they suggested that the F:B ratio should be a useful new bioindicator of soil status. The resulting dataset can be considered as a first step toward building up a robust repository essential to any bioindicator and aimed at guiding and helping decision making. IMPORTANCE In the face of human disturbances, microbial activity can be impacted and, e.g., can result in the release of large amounts of soil carbon into the atmosphere, with global impacts on temperature. Therefore, the development and the regular use of soil bioindicators are essential to (i) improve our knowledge of soil microbial communities and (ii) guide and help decision makers define suitable soil management strategies. Bacterial and fungal communities are key players in soil organic matter turnover, but with distinct physiological and ecological characteristics. The fungal:bacterial ratio targets these two major functional groups by investigating their presence and their equilibrium. The aim of our study is to characterize this ratio at a territorial scale and rank the environmental parameters involved so as to further develop a robust repository essential to the interpretation of any bioindicator of soil quality.

Potential of Meta-Omics to Provide Modern Microbial Indicators for Monitoring Soil Quality and Securing Food Production.

Soils are fundamental resources for agricultural production and play an essential role in food security. They represent the keystone of the food value chain because they harbor a large fraction of biodiversity-the backbone of the regulation of ecosystem services and "soil health" maintenance. In the face of the numerous causes of soil degradation such as unsustainable soil management practices, pollution, waste disposal, or the increasing number of extreme weather events, it has become clear that (i) preserving the soil biodiversity is key to food security, and (ii) biodiversity-based solutions for environmental monitoring have to be developed. Within the soil biodiversity reservoir, microbial diversity including Archaea, Bacteria, Fungi and protists is essential for ecosystem functioning and resilience. Microbial communities are also sensitive to various environmental drivers and to management practices; as a result, they are ideal candidates for monitoring soil quality assessment. The emergence of meta-omics approaches based on recent advances in high-throughput sequencing and bioinformatics has remarkably improved our ability to characterize microbial diversity and its potential functions. This revolution has substantially filled the knowledge gap about soil microbial diversity regulation and ecology, but also provided new and robust indicators of agricultural soil quality. We reviewed how meta-omics approaches replaced traditional methods and allowed developing modern microbial indicators of the soil biological quality. Each meta-omics approach is described in its general principles, methodologies, specificities, strengths and drawbacks, and illustrated with concrete applications for soil monitoring. The development of metabarcoding approaches in the last 20 years has led to a collection of microbial indicators that are now operational and available for the farming sector. Our review shows that despite the recent huge advances, some meta-omics approaches (e.g., metatranscriptomics or meta-proteomics) still need developments to be operational for environmental bio-monitoring. As regards prospects, we outline the importance of building up repositories of soil quality indicators. These are essential for objective and robust diagnosis, to help actors and stakeholders improve soil management, with a view to or to contribute to combining the food and environmental quality of next-generation farming systems in the context of the agroecological transition.

Correction: Mapping and predictive variations of soil bacterial richness across France.

[This corrects the article DOI: 10.1371/journal.pone.0186766.].

Inferring microbiota functions from taxonomic genes: a review.

Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes-compared with the human microbiota-especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.

Soil microbial communities in the face of changing farming practices: A case study in an agricultural landscape in France.

According to biogeography studies, the abundance and richness of soil microorganisms vary across multiple spatial scales according to soil properties and farming practices. However, soil microorganisms also exhibit poorly understood temporal variations. This study aimed at better understanding how soil microbial communities respond to changes in farming practices at a landscape scale over time. A regular grid of 269 sites was set up across a 1,200 ha farming landscape, and soil samples were characterized for their molecular microbial biomass and bacterial richness at two dates (2011 and 2016). A mapping approach highlighted that spatial microbial patterns were stable over time, while abundance and richness levels were modified. The drivers of these changes were investigated though a PLS-PM (partial least square path-modeling) approach. Soil properties were stable over time, but farming practices changed. Molecular microbial biomass was mainly driven by soil resources, whereas bacterial richness depended on both farming practices and ecological parameters. Previous-crop and management effects and a temporal dependence of the microbial community on the historical farming management were also highlighted.

BIOCOM-PIPE: a new user-friendly metabarcoding pipeline for the characterization of microbial diversity from 16S, 18S and 23S rRNA gene amplicons.

BACKGROUND: The ability to compare samples or studies easily using metabarcoding so as to better interpret microbial ecology results is an upcoming challenge. A growing number of metabarcoding pipelines are available, each with its own benefits and limitations. However, very few have been developed to offer the opportunity to characterize various microbial communities (e.g., archaea, bacteria, fungi, photosynthetic microeukaryotes) with the same tool. RESULTS: BIOCOM-PIPE is a flexible and independent suite of tools for processing data from high-throughput sequencing technologies, Roche 454 and Illumina platforms, and focused on the diversity of archaeal, bacterial, fungal, and photosynthetic microeukaryote amplicons. Various original methods were implemented in BIOCOM-PIPE to (1) remove chimeras based on read abundance, (2) align sequences with structure-based alignments of RNA homologs using covariance models, and (3) a post-clustering tool (ReClustOR) to improve OTUs consistency based on a reference OTU database. The comparison with two other pipelines (FROGS and mothur) and Amplicon Sequence Variant definition highlighted that BIOCOM-PIPE was better at discriminating land use groups. CONCLUSIONS: The BIOCOM-PIPE pipeline makes it possible to analyze 16S, 18S and 23S rRNA genes in the same packaged tool. The new post-clustering approach defines a biological database from previously analyzed samples and performs post-clustering of reads with this reference database by using open-reference clustering. This makes it easier to compare projects from various sequencing runs, and increased the congruence among results. For all users, the pipeline was developed to allow for adding or modifying the components, the databases and the bioinformatics tools easily, giving high modularity for each analysis.

µgreen-db: a reference database for the 23S rRNA gene of eukaryotic plastids and cyanobacteria.

Studying the ecology of photosynthetic microeukaryotes and prokaryotic cyanobacterial communities requires molecular tools to complement morphological observations. These tools rely on specific genetic markers and require the development of specialised databases to achieve taxonomic assignment. We set up a reference database, called µgreen-db, for the 23S rRNA gene. The sequences were retrieved from generalist (NCBI, SILVA) or Comparative RNA Web (CRW) databases, in addition to a more original approach involving recursive BLAST searches to obtain the best possible sequence recovery. At present, µgreen-db includes 2,326 23S rRNA sequences belonging to both eukaryotes and prokaryotes encompassing 442 unique genera and 736 species of photosynthetic microeukaryotes, cyanobacteria and non-vascular land plants based on the NCBI and AlgaeBase taxonomy. When PR2/SILVA taxonomy is used instead, µgreen-db contains 2,217 sequences (399 unique genera and 696 unique species). Using µgreen-db, we were able to assign 96% of the sequences of the V domain of the 23S rRNA gene obtained by metabarcoding after amplification from soil DNA at the genus level, highlighting good coverage of the database. µgreen-db is accessible at http://microgreen-23sdatabase.ea.inra.fr.

Biogeography of Soil Bacterial Networks along a Gradient of Cropping Intensity.

Although land use drives soil bacterial diversity and community structure, little information about the bacterial interaction networks is available. Here, we investigated bacterial co-occurrence networks in soils under different types of land use (forests, grasslands, crops and vineyards) by sampling 1798 sites in the French Soil Quality Monitoring Network covering all of France. An increase in bacterial richness was observed from forests to vineyards, whereas network complexity respectively decreased from 16,430 links to 2,046. However, the ratio of positive to negative links within the bacterial networks ranged from 2.9 in forests to 5.5 in vineyards. Networks structure was centered on the most connected genera (called hub), which belonged to Bacteroidetes in forest and grassland soils, but to Actinobacteria in vineyard soils. Overall, our study revealed that soil perturbation due to intensive cropping reduces strongly the complexity of bacterial network although the richness is increased. Moreover, the hub genera within the bacterial community shifted from copiotrophic taxa in forest soils to more oligotrophic taxa in agricultural soils.

Tillage intensity and pasture in rotation effectively shape soil microbial communities at a landscape scale.

Soil microorganisms are essential to agroecosystem functioning and services. Yet, we still lack information on which farming practices can effectively shape the soil microbial communities. The aim of this study was to identify the farming practices, which are most effective at positively or negatively modifying bacterial and fungal diversity while considering the soil environmental variation at a landscape scale. A long-term research study catchment (12 km2 ) representative of intensive mixed farming (livestock and crop) in Western Europe was investigated using a regular grid for soil sampling (n = 186). Farming systems on this landscape scale were described in terms of crop rotation, use of fertilizer, soil tillage, pesticides treatments, and liming. Molecular microbial biomass was estimated by soil DNA recovery. Bacterial and fungal communities were analyzed by 16S and 18S rRNA gene pyrosequencing. Microbial biomass was significantly stimulated by the presence of pasture during the crop rotation since temporary and permanent pastures, as compared to annual crops, increased the soil microbial biomass by +23% and +93% respectively. While soil properties (mainly pH) explained much of the variation in bacterial diversity, soil tillage seemed to be the most influential among the farming practices. A 2.4% increase in bacterial richness was observed along our gradient of soil tillage intensity. In contrast, farming practices were the predominant drivers of fungal diversity, which was mainly determined by the presence of pastures during the crop rotation. Compared to annual crops, temporary and permanent pastures increased soil fungal richness by +10% and +14.5%, respectively. Altogether, our landscape-scale investigation allows the identification of farming practices that can effectively shape the soil microbial abundance and diversity, with the goal to improve agricultural soil management and soil ecological integrity.

Biogeography of soil bacteria and archaea across France.

Over the last two decades, a considerable effort has been made to decipher the biogeography of soil microbial communities as a whole, from small to broad scales. In contrast, few studies have focused on the taxonomic groups constituting these communities; thus, our knowledge of their ecological attributes and the drivers determining their composition and distribution is limited. We applied a pyrosequencing approach targeting 16S ribosomal RNA (rRNA) genes in soil DNA to a set of 2173 soil samples from France to reach a comprehensive understanding of the spatial distribution of bacteria and archaea and to identify the ecological processes and environmental drivers involved. Taxonomic assignment of the soil 16S rRNA sequences indicated the presence of 32 bacterial phyla or subphyla and 3 archaeal phyla. Twenty of these 35 phyla were cosmopolitan and abundant, with heterogeneous spatial distributions structured in patches ranging from a 43- to 260-km radius. The hierarchy of the main environmental drivers of phyla distribution was soil pH > land management > soil texture > soil nutrients > climate. At a lower taxonomic level, 47 dominant genera belonging to 12 phyla aggregated 62.1% of the sequences. We also showed that the phylum-level distribution can be determined largely by the distribution of the dominant genus or, alternatively, reflect the combined distribution of all of the phylum members. Together, our study demonstrated that soil bacteria and archaea present highly diverse biogeographical patterns on a nationwide scale and that studies based on intensive and systematic sampling on a wide spatial scale provide a promising contribution for elucidating soil biodiversity determinism.

Comparative Microbiome Analysis of a Fusarium Wilt Suppressive Soil and a Fusarium Wilt Conducive Soil From the Châteaurenard Region.

Disease-suppressive soils are soils in which specific soil-borne plant pathogens cause only limited disease although the pathogen and susceptible host plants are both present. Suppressiveness is in most cases of microbial origin. We conducted a comparative metabarcoding analysis of the taxonomic diversity of fungal and bacterial communities from suppressive and non-suppressive (conducive) soils as regards Fusarium wilts sampled from the Châteaurenard region (France). Bioassays based on Fusarium wilt of flax confirmed that disease incidence was significantly lower in the suppressive soil than in the conducive soil. Furthermore, we succeeded in partly transferring Fusarium wilt-suppressiveness to the conducive soil by mixing 10% (w/w) of the suppressive soil into the conducive soil. Fungal diversity differed significantly between the suppressive and conducive soils. Among dominant fungal operational taxonomic units (OTUs) affiliated to known genera, 17 OTUs were detected exclusively in the suppressive soil. These OTUs were assigned to the Acremonium, Chaetomium, Cladosporium, Clonostachys, Fusarium, Ceratobasidium, Mortierella, Penicillium, Scytalidium, and Verticillium genera. Additionally, the relative abundance of specific members of the bacterial community was significantly higher in the suppressive and mixed soils than in the conducive soil. OTUs found more abundant in Fusarium wilt-suppressive soils were affiliated to the bacterial genera Adhaeribacter, Massilia, Microvirga, Rhizobium, Rhizobacter, Arthrobacter, Amycolatopsis, Rubrobacter, Paenibacillus, Stenotrophomonas, and Geobacter. Several of the fungal and bacterial genera detected exclusively or more abundantly in the Fusarium wilt-suppressive soil included genera known for their activity against F. oxysporum. Overall, this study supports the potential role of known fungal and bacterial genera in Fusarium wilt suppressive soils from Châteaurenard and pinpoints new bacterial and fungal genera for their putative role in Fusarium wilt suppressiveness.

High Microbial Diversity Promotes Soil Ecosystem Functioning.

In soil, the link between microbial diversity and carbon transformations is challenged by the concept of functional redundancy. Here, we hypothesized that functional redundancy may decrease with increasing carbon source recalcitrance and that coupling of diversity with C cycling may change accordingly. We manipulated microbial diversity to examine how diversity decrease affects the decomposition of easily degradable (i.e., allochthonous plant residues) versus recalcitrant (i.e., autochthonous organic matter) C sources. We found that a decrease in microbial diversity (i) affected the decomposition of both autochthonous and allochthonous carbon sources, thereby reducing global CO2 emission by up to 40%, and (ii) shaped the source of CO2 emission toward preferential decomposition of most degradable C sources. Our results also revealed that the significance of the diversity effect increases with nutrient availability. Altogether, these findings show that C cycling in soil may be more vulnerable to microbial diversity changes than expected from previous studies, particularly in ecosystems exposed to nutrient inputs. Thus, concern about the preservation of microbial diversity may be highly relevant in the current global-change context assumed to impact soil biodiversity and the pulse inputs of plant residues and rhizodeposits into the soil.IMPORTANCE With hundreds of thousands of taxa per gram of soil, microbial diversity dominates soil biodiversity. While numerous studies have established that microbial communities respond rapidly to environmental changes, the relationship between microbial diversity and soil functioning remains controversial. Using a well-controlled laboratory approach, we provide empirical evidence that microbial diversity may be of high significance for organic matter decomposition, a major process on which rely many of the ecosystem services provided by the soil ecosystem. These new findings should be taken into account in future studies aimed at understanding and predicting the functional consequences of changes in microbial diversity on soil ecosystem services and carbon storage in soil.

Correction: Mapping and predictive variations of soil bacterial richness across France.

[This corrects the article DOI: 10.1371/journal.pone.0186766.].

Mapping and predictive variations of soil bacterial richness across France.

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Bacterial Community Diversity Harboured by Interacting Species.

All animals are infected by microbial partners that can be passengers or residents and influence many biological traits of their hosts. Even if important factors that structure the composition and abundance of microbial communities within and among host individuals have been recently described, such as diet, developmental stage or phylogeny, few studies have conducted cross-taxonomic comparisons, especially on host species related by trophic relationships. Here, we describe and compare the microbial communities associated with the cabbage root fly Delia radicum and its three major parasitoids: the two staphylinid beetles Aleochara bilineata and A. bipustulata and the hymenopteran parasitoid Trybliographa rapae. For each species, two populations from Western France were sampled and microbial communities were described through culture independent methods (454 pyrosequencing). Each sample harbored at least 59 to 261 different bacterial phylotypes but was strongly dominated by one or two. Microbial communities differed markedly in terms of composition and abundance, being mainly influenced by phylogenetic proximity but also geography to a minor extent. Surprisingly, despite their strong trophic interaction, parasitoids shared a very low proportion of microbial partners with their insect host. Three vertically transmitted symbionts from the genus Wolbachia, Rickettsia, and Spiroplasma were found in this study. Among them, Wolbachia and Spiroplasma were found in both the cabbage fly and at least one of its parasitoids, which could result from horizontal transfers through trophic interactions. Phylogenetic analysis showed that this hypothesis may explain some but not all cases. More work is needed to understand the dynamics of symbiotic associations within trophic network and the effect of these bacterial communities on the fitness of their hosts.

FT-IR spectroscopy: A powerful tool for studying the inter- and intraspecific biodiversity of cultivable non-Saccharomyces yeasts isolated from grape must.

The efficiency of the FT-IR technique for studying the inter- and intra biodiversity of cultivable non-Saccharomyces yeasts (NS) present in different must samples was examined. In first, the capacity of the technique FT-IR to study the global diversity of a given sample was compared to the pyrosequencing method, used as a reference technique. Seven different genera (Aureobasidium, Candida, Cryptococcus, Hanseniaspora, Issatchenkia, Metschnikowia and Pichia) were identified by FT-IR and also by pyrosequencing. Thirty-eight other genera were identified by pyrosequencing, but together they represented less than 6% of the average total population of 6 musts. Among the species identified, some of them present organoleptic potentials in winemaking, particularly Starmerella bacillaris (synonym Candidazemplinina). So in a second time, we evaluated the capacity of the FT-IR technique to discriminate the isolates of this species because few techniques were able to study intraspecific NS yeast biodiversity. The results obtained were validated by using a classic method as ITS sequencing. Biodiversity at strain level was high: 19 different strains were identified from 58 isolates. So, FT-IR spectroscopy seems to be an accurate and reliable method for identifying major genera present in the musts. The two biggest advantages of the FT-IR are the capacity to characterize intraspecific biodiversity of non-Saccharomyces yeasts and the possibility to discriminate a lot of strains.

Land Use History Shifts In Situ Fungal and Bacterial Successions following Wheat Straw Input into the Soil.

Soil microbial communities undergo rapid shifts following modifications in environmental conditions. Although microbial diversity changes may alter soil functioning, the in situ temporal dynamics of microbial diversity is poorly documented. Here, we investigated the response of fungal and bacterial diversity to wheat straw input in a 12-months field experiment and explored whether this response depended on the soil management history (grassland vs. cropland). Seasonal climatic fluctuations had no effect on the diversity of soil communities. Contrastingly fungi and bacteria responded strongly to wheat regardless of the soil history. After straw incorporation, diversity decreased due to the temporary dominance of a subset of copiotrophic populations. While fungi responded as quickly as bacteria, the resilience of fungal diversity lasted much longer, indicating that the relative involvement of each community might change as decomposition progressed. Soil history did not affect the response patterns, but determined the identity of some of the populations stimulated. Most strikingly, the bacteria Burkholderia, Lysobacter and fungi Rhizopus, Fusarium were selectively stimulated. Given the ecological importance of these microbial groups as decomposers and/or plant pathogens, such regulation of the composition of microbial successions by soil history may have important consequences in terms of soil carbon turnover and crop health.

Mapping and determinism of soil microbial community distribution across an agricultural landscape.

Despite the relevance of landscape, regarding the spatial patterning of microbial communities and the relative influence of environmental parameters versus human activities, few investigations have been conducted at this scale. Here, we used a systematic grid to characterize the distribution of soil microbial communities at 278 sites across a monitored agricultural landscape of 13 km². Molecular microbial biomass was estimated by soil DNA recovery and bacterial diversity by 16S rRNA gene pyrosequencing. Geostatistics provided the first maps of microbial community at this scale and revealed a heterogeneous but spatially structured distribution of microbial biomass and diversity with patches of several hundreds of meters. Variance partitioning revealed that both microbial abundance and bacterial diversity distribution were highly dependent of soil properties and land use (total variance explained ranged between 55% and 78%). Microbial biomass and bacterial richness distributions were mainly explained by soil pH and texture whereas bacterial evenness distribution was mainly related to land management. Bacterial diversity (richness, evenness, and Shannon index) was positively influenced by cropping intensity and especially by soil tillage, resulting in spots of low microbial diversity in soils under forest management. Spatial descriptors also explained a small but significant portion of the microbial distribution suggesting that landscape configuration also shapes microbial biomass and bacterial diversity.

Contrasting spatial patterns and ecological attributes of soil bacterial and archaeal taxa across a landscape.

Even though recent studies have clarified the influence and hierarchy of environmental filters on bacterial community structure, those constraining bacterial populations variations remain unclear. In consequence, our ability to understand to ecological attributes of soil bacteria and to predict microbial community response to environmental stress is therefore limited. Here, we characterized the bacterial community composition and the various bacterial taxonomic groups constituting the community across an agricultural landscape of 12 km(2) , by using a 215 × 215 m systematic grid representing 278 sites to precisely decipher their spatial distribution and drivers at this scale. The bacterial and Archaeal community composition was characterized by applying 16S rRNA gene pyrosequencing directly to soil DNA from samples. Geostatistics tools were used to reveal the heterogeneous distribution of bacterial composition at this scale. Soil physical parameters and land management explained a significant amount of variation, suggesting that environmental selection is the major process shaping bacterial composition. All taxa systematically displayed also a heterogeneous and particular distribution patterns. Different relative influences of soil characteristics, land use and space were observed, depending on the taxa, implying that selection and spatial processes might be differentially but not exclusively involved for each bacterial phylum. Soil pH was a major factor determining the distribution of most of the bacterial taxa and especially the most important factor explaining the spatial patterns of α-Proteobacteria and Planctomycetes. Soil texture, organic carbon content and quality were more specific to a few number of taxa (e.g., ß-Proteobacteria and Chlorobi). Land management also influenced the distribution of bacterial taxa across the landscape and revealed different type of response to cropping intensity (positive, negative, neutral or hump-backed relationships) according to phyla. Altogether, this study provided valuable clues about the ecological behavior of soil bacterial and archaeal taxa at an agricultural landscape scale and could be useful for developing sustainable strategies of land management.