Marion Devers-Lamrani

Even decades after being banned in Europe, atrazine and its main metabolites can still be found in soils. While bioaugmentation using pesticide-degrading bacteria is already employed as a strategy for remediating polluted soils, there is still a need to improve its efficiency. Therefore, investigating the application of carrier materials to deliver and stabilize pesticide-degrading microorganisms in situ emerges as an interesting approach for further exploration. Here, we generated atrazine-degrading biocomposites by cultivating either a single strain or a 4-species bacterial consortium as biofilms on zeolite, which serves as the carrier material. Using a microcosm experiment, we then evaluated their efficiency to mineralize ¹⁴ C-atrazine in an agricultural soil comparing to free-living cells, and assessed the side effects of the two inoculation methods on the native soil bacterial community using 16S rDNA amplicon sequencing. We showed that, right after inoculation, the atrazine mineralization potential of the free-living cells was higher than that of the biocomposites. However, microcosms inoculated with the biocomposites displayed significantly higher atrazine mineralization potential than the ones inoculated with free-living cells after 15 and 45 days of incubation, not only indicating a higher efficiency but also a better stability in the soil environment, further confirmed by qPCR of the atz genes. We also showed that the inoculation of free-living cells and biocomposites differently influences the diversity and composition of the native microbial community, and that these effects are modulated by the scenario of atrazine contamination during soil inoculation. Altogether, our results provide a thorough evaluation of the efficiency and the ecotoxicological impact of atrazine-degrading biocomposites in soil.

Pesticides are widely used in conventional agriculture, either applied separately or incombination during the culture cycle. Due to their occurrence and persistence in soils, pesticideresidues may have an impact on soil microbial communities and on supported ecosystemservices. In this regard, the EFSA (European Food Safety Authority) recently published ascientific opinion inciting to change pesticide risk assessment to better protect soil microbe-mediated processes. Climate change is another major concern for all living organisms includingsoil microbial community stability. Extreme climatic events, such as heat waves or heavyrainfalls, are becoming more and more frequent and their impact on soil microbial diversity andfunctions have already been demonstrated.The objectives of this study were to evaluate the effects of temperature and humiditydisturbances and pesticide active ingredients exposure on soil microbial community structureand functions. To this end, 250 soil microcosms were exposed to either a heat disturbance, ahigh humidity to mimic heavy rain, or no environmental disturbance. After three days ofrecovery, soil microcosms were treated with different active ingredients: clopyralid (herbicide),cypermethrin (insecticide) and pyraclostrobin (fungicide). The treatments were applied aloneor in combination at 1x or 10x of the agronomical dose. We then evaluated the effects of thedisturbances and the active ingredients on various microbial endpoints related to the diversityand the structure of soil microbial communities, and with a specific focus on microbial guildsinvolved in nitrification.Overall, we demonstrated that the impact of environmental disturbances applied to soilmicrocosms, especially heat, on microbial endpoints was stronger than that of the activeingredients applied alone or in combinations. Compounded effects of environmentaldisturbances and active ingredients were detected, but sparsely and were of small scale for thechosen pesticides and applied doses.

During crop growth cycle, often several different plant protection products (PPPs) are applied, in combination or sequentially. Such sequential applications result in unintentional mixtures of residues that may affect ecosystem services supported by non-target organisms such as soil microbes and nematodes. This scenario of sequential PPP application is frequent in agricultural practice but rarely addressed experimentally at field scale with regard to environmental impacts. The objective of this study was to evaluate the effect of individual and sequential application of three PPPs (the herbicide clopyralid, the insecticide zeta-cypermethrin, and the fungicide pyraclostrobin) on soil microbial communities, and on the abundance of free-living nematode. Single applications (at 1× or 10× the agronomical dose) were made to triplicated field plots with each one of the PPPs or all three PPPs in sequence, with untreated plots serving as controls. Plots were sampled prior to each application, and 7 and 28 days thereafter. The fungal community’s composition and abundance were found to be more susceptible than the bacterial community to PPP applications, while the bacterial was mainly driven by the in-field heterogeneity of soil properties. Transient effects of PPP applications were detected on nematode abundance. Higher tier ecotoxicological studies offer greater ecological relevance compared to the standard laboratory tests but are challenged by environmental variations that should be accounted for when evaluating the ecotoxicity of pesticides on soil organisms.

This study reports draft genomes of 30 bacteria representative of the plant food system microbiota and isolated from different sources in Italy and France. Individual genomes were reconstructed using PacBIO DNA sequencing: taxonomic classification and distribution of genes involved in microbe-environment interactions are reported to facilitate strains' characterization and utilization.

Parallel to the important use of pesticides in conventional agriculture there is a growing interest for green technologies to clear contaminated soil from pesticides and their degradation products. One specific technique, the inoculation of degrading micro-organisms in polluted soil, known as bioaugmentation, is a promising method still in needs of further developments. Specifically, improvements in the understanding of how degrading microorganisms must overcome abiotic filters and interact with the autochthonous microbial communities are needed in order to efficiently design bioremediation strategies. Here we designed a protocol aiming at studying the degradation of two herbicides, glyphosate (GLY) and isoproturon (IPU), via experimental modifications of two source bacterial communities. We used statistical methods stemming from genomic prediction to link community composition to herbicides degradation potentials. Our approach proved to be efficient with correlation estimates over 0.8 - between model predictions and measured pesticide degradation values. OTUs significantly associated with the degradation ability, and therefore identified as relevant by the models were confronted to the literature. Next, multi-degrading bacterial communities were obtained by coalescing bacterial communities with high GLY or IPU degradation ability based on their community-level properties. Finally, we evaluated the efficiency of constructed multi-degrading communities to remove pesticide contamination in a different soil. While results are less clear in the case of GLY, we showed an efficient transfer of degrading capacities towards the receiving soil even at relatively low inoculation levels in the case of IPU. Altogether, we developed an innovative protocol for building multi-degrading simplified bacterial communities with the help of genomic prediction tools and coalescence, and proved their efficiency in a contaminated soil.

The interspecific interactions play an important role in the establishment of a community phenotype. Furthermore, the evolution of a community can not only occur through an evolution of the species composing the community but also of the interactions among them. In this study, we investigated how widespread was the evolution of interspecific interactions in the evolutionary response of eight two-bacterial species communities regarding productivity. We found evidence for an evolution of the interactions in half of the studied communities which gave rise to a mean change of 15% in community productivity as compared to what was expected from the individual responses. Even when the interactions did not evolve themselves, they influenced the evolutionary responses of the bacterial strains within the communities which further affected community response. We found that the evolution within a community often promoted an adaptation of the bacterial strains to the abiotic environment, especially for the dominant strain in a community. Overall, this study suggested that the evolution of the interspecific interactions was frequent and that it could increase community response to evolution. We propose that the existence of an evolution of the interspecific interactions can justify the consideration of the community as a unit of selection.

Artificial selection can be conducted at the community level in the laboratory through a differential propagation of the communities according to their level of expression of a targeted function (i.e. community phenotype). Working with communities instead of individuals as selection units brings in additional sources of variation in the considered phenotype that can arise through changes in community structure and influence the outcome of the artificial selection. These sources of variation could even be increased by manipulating species diversity. In this study, we wanted to assess the effect of manipulating initial community richness on artificial selection efficiency, defined as the change in the targeted function over time as compared to a control treatment without artificial selection. We applied artificial selection for a high productivity on synthetic bacterial communities varying for their initial richness level (from one to 16 strains). Our results showed that, overall, the communities that were artificially selected were 16% more productive than the control communities. Community richness positively influenced community productivity and metabolic capacities and was a strong determinant of the dynamics of community evolution. Our results suggested that community richness could influence artificial selection efficiency but a convergence of the community composition might have limited the effect of diversity on artificial selection efficiency. We propose that applying artificial selection on communities varying for their diversity could allow to find communities differing for their level of expression of a function but also for their responsiveness to artificial selection, provided that their initial composition is different enough.