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Abstract The specificity of dairy Protected Designation of Origin (PDO) products is related to their “terroir” of production. This relationship needs better understanding for efficient and sustainable productions preserving the agroecological equilibrium of agroecosystems, especially grasslands. Specificity of PDO Comté cheese was related to the diversity of natural raw milk bacterial communities, but their sources need to be determined. It is hypothesized that raw milk indigenous microbial communities may originate from permanent grazed grasslands by the intermediate of dairy cows according to the sequence soil–phyllosphere–teat–milk. This hypothesis was evaluated on a 44 dairy farms network across PDO Comté cheese area by characterizing prokaryotic and fungal communities of these compartments by metabarcoding analysis (16S rRNA gene: V3–V4 region, 18S rRNA gene: V7–V8 region). Strong and significant links were highlighted between the four compartments through a network analysis (0.34

The soil microbial community plays important roles in nutrient cycling, plant pathogen suppression, decomposition of residues and degradation of pollutants; as such, it is often regarded as a good indicator of soil quality. Repeated applications of mixed organic and inorganic materials in agriculture improve the soil microbial quality and in turn crop productivity. The soil microbial quality following several years of repeated fertilizer inputs has received considerable attention, but the dynamic of this community over time has never been assessed. We used high-throughput sequencing targeting 16S ribosomal RNA genes to investigate the evolution of the bacterial and archaeal community throughout 6 years of repeated organic and inorganic fertilizer applications. Soils were sampled from a field experiment in La Mare (Reunion Island, France), where different mixed organic-inorganic fertilizer inputs characterized by more or less stable organic matter were applied regularly for 6 years. Soil samples were taken each year, more than 6 months after the latest fertilizer application. The soil molecular biomass significantly increased in some organically fertilized plots (by 35-45% on average), 3-5 years after the first fertilizers application. The significant variations in soil molecular microbial biomass were explained by the fertilization practices (cumulated organic carbon inputs) and sometimes by the soil parameters (sand and soil carbon contents). The structure of the bacterial and archaeal community was more influenced by time than by the fertilization type. However, repeated fertilizer applications over time tended to modify the abundance of the bacterial phyla Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes , and Proteobacteria. To conclude, the present study highlights that the soil bacterial and archaeal community is lastingly modified after 6 years of repeated fertilizer inputs. These changes depend on the nature of the organic input and on the fertilization practice (frequency and applied quantity)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sadet-Bourgeteau, Djemiel, Chemidlin Prévost-Bouré and Feder.)

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., Competing Interests: BK was employed by the company Novasol Experts. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Djemiel, Dequiedt, Karimi, Cottin, Horrigue, Bailly, Boutaleb, Sadet-Bourgeteau, Maron, Chemidlin Prévost-Bouré, Ranjard and Terrat.)

The specificity of dairy Protected Designation of Origin (PDO) products is related to their "terroir" of production. This relationship needs better understanding for efficient and sustainable productions preserving the agroecological equilibrium of agroecosystems, especially grasslands. Specificity of PDO Comté cheese was related to the diversity of natural raw milk bacterial communities, but their sources need to be determined. It is hypothesized that raw milk indigenous microbial communities may originate from permanent grazed grasslands by the intermediate of dairy cows according to the sequence soil-phyllosphere-teat-milk. This hypothesis was evaluated on a 44 dairy farms network across PDO Comté cheese area by characterizing prokaryotic and fungal communities of these compartments by metabarcoding analysis (16S rRNA gene: V3-V4 region, 18S rRNA gene: V7-V8 region). Strong and significant links were highlighted between the four compartments through a network analysis (0.34 < r < 0.58), and were modulated by soil pH, plant diversity and elevation; but also by farming practices: organic fertilization levels, cattle intensity and cow-teat care. This causal relationship suggests that microbial diversity of agroecosystems is a key player in relating a PDO product to its "terroir"; this under the dependency of farming practices. Altogether, this makes the "terroir" even more local and needs to be considered for production sustainability., (© 2021. The Author(s).)

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., Competing Interests: NO authors have competing interests.

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.

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 km 2 ) 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., (© 2018 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.)

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.

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.

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., (© 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.)

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., β-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., (© 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.)

The evaluation of the taxa-area relationship (TAR) with molecular fingerprinting data demonstrated the spatial structuration of soil microorganisms and provided insights into the processes shaping their diversity. The increasing use of massive sequencing technologies in biodiversity investigations has now raised the question of the advantages of such technologies over the fingerprinting approach for elucidation of the determinism of soil microbial community assembly in broad-scale biogeographic studies. Our objectives in this study were to compare DNA fingerprinting and meta-barcoding approaches for evaluating soil bacterial TAR and the determinism of soil bacterial community assembly on a broad scale. This comparison was performed on 392 soil samples from four French geographic regions with different levels of environmental heterogeneity. Both molecular approaches demonstrated a TAR with a significant slope but, because of its more sensitive description of soil bacterial community richness, meta-barcoding provided significantly higher and more accurate estimates of turnover rates. Both approaches were useful in evidencing the processes shaping bacterial diversity variations on a broad scale. When different taxonomic resolutions were considered for meta-barcoding data, they significantly influenced the estimation of turnover rates but not the relative importance of each component process. Altogether, DNA meta-barcoding provides a more accurate evaluation of the TAR and may lead to re-examination of the processes shaping soil bacterial community assembly. This should provide new insights into soil microbial ecology in the context of sustainable use of soil resources.

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

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.

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.