The effect of wheat genotype on the microbiome is more evident in roots and varies through time.

Crop breeding has traditionally ignored the plant-associated microbial communities. Considering the interactions between plant genotype and associated microbiota is of value since different genotypes of the same crop often harbor distinct microbial communities which can influence the plant phenotype. However, recent studies have reported contrasting results, which led us to hypothesize that the effect of genotype is constrained by growth stages, sampling year and plant compartment. To test this hypothesis, we sampled bulk soil, rhizosphere soil and roots of 10 field-grown wheat genotypes, twice per year, for 4 years. DNA was extracted and regions of the bacterial 16 S rRNA and CPN60 genes and the fungal ITS region were amplified and sequenced. The effect of genotype was highly contingent on the time of sampling and on the plant compartment sampled. Only for a few sampling dates, were the microbial communities significantly different across genotypes. The effect of genotype was most often significant for root microbial communities. The three marker genes used provided a highly coherent picture of the effect of genotype. Taken together, our results confirm that microbial communities in the plant environment strongly vary across compartments, growth stages, and years, and that this can mask the effect of genotype.

Rhizosphere shotgun metagenomic analyses fail to show differences between ancestral and modern wheat genotypes grown under low fertilizer inputs.

It is thought that modern wheat genotypes have lost their capacity to associate with soil microbes that would help them acquire nutrients from the soil. To test this hypothesis, ten ancestral and modern wheat genotypes were seeded in a field experiment under low fertilization conditions. The rhizosphere soil was collected, its DNA extracted and submitted to shotgun metagenomic sequencing. In contrast to our hypothesis, there was no significant difference in the global rhizosphere metagenomes of the different genotypes, and this held true when focusing the analyses on specific taxonomic or functional categories of genes. Some genes were significantly more abundant in the rhizosphere of one genotype or another, but they comprised only a small portion of the total genes identified and did not affect the global rhizosphere metagenomes. Our study shows for the first time that the rhizosphere metagenome of wheat is stable across a wide variety of genotypes when growing under nutrient poor conditions.

Microbial indicators are better predictors of wheat yield and quality than N fertilization.

In view of their key roles in many soil- and plant-related processes, we hypothesized that soil microorganisms could play a larger role in determining wheat baking quality than nitrogen fertilization. A field experiment was conducted under bread wheat production conditions, where different fertilization treatments, ranging from 0-120 kg/ha NH4NO3, were applied. Soil samples were taken in May, June and July. Functional genes in the nitrogen cycle were quantified and amplicons of the 16S rRNA gene and the ITS region were sequenced. Wheat yields were measured, and the grain baking quality was analysed for each plot. Fertilisation did not significantly influence the yields and the grain quality. Many bacterial and fungal Amplicon Sequence Variants showed significant positive or negative correlations with yield and grain baking quality parameters. Among the functional gene quantified, the archaeal amoA showed strong negative correlations with the wheat yields and many grain and flour quality parameters. Regression models were able to explain up to 81% of the variability in grain quality based on the microbial data from the May sampling. A better understanding of the microbiology of wheat fields could lead to an optimized management of the N fertilization to maximize yields and grain quality.

Towards the development of multifunctional molecular indicators combining soil biogeochemical and microbiological variables to predict the ecological integrity of silvicultural practices.

The impact of mechanical site preparation (MSP) on soil biogeochemical structure in young larch plantations was investigated. Soil samples were collected in replicated plots comprising simple trenching, double trenching, mounding and inverting site preparation. Unlogged natural mixed forest areas were used as a reference. Analysis of soil nutrients, abundance of bacteria and gas exchanges unveiled no significant difference among the plots. However, inverting site preparation resulted in higher variations of gas exchanges when compared with trenching, mounding and unlogged natural forest. A combination of the biological and physicochemical variables was used to define a multifunctional classification of the soil samples into four distinct groups categorized as a function of their deviation from baseline ecological conditions. According to this classification model, simple trenching was the approach that represented the lowest ecological risk potential at the microsite level. No relationship was observed between MSP method and soil bacterial community structure as assessed by high-throughput sequencing of bacterial 16S rRNA gene; however, indicator genotypes were identified for each multifunctional soil class. This is the first identification of multifunctional molecular indicators for baseline and disturbed ecological conditions in soil, demonstrating the potential of applied microbial ecology to guide silvicultural practices and ecological risk assessment.

Harnessing phytomicrobiome signaling for rhizosphere microbiome engineering.

The goal of microbiome engineering is to manipulate the microbiome toward a certain type of community that will optimize plant functions of interest. For instance, in crop production the goal is to reduce disease susceptibility, increase nutrient availability increase abiotic stress tolerance and increase crop yields. Various approaches can be devised to engineer the plant-microbiome, but one particularly promising approach is to take advantage of naturally evolved plant-microbiome communication channels. This is, however, very challenging as the understanding of the plant-microbiome communication is still mostly rudimentary and plant-microbiome interactions varies between crops species (and even cultivars), between individual members of the microbiome and with environmental conditions. In each individual case, many aspects of the plant-microorganisms relationship should be thoroughly scrutinized. In this article we summarize some of the existing plant-microbiome engineering studies and point out potential avenues for further research.

Land-use influences the distribution and activity of high affinity CO-oxidizing bacteria associated to type I-coxL genotype in soil.

Soil carboxydovore bacteria are the biological sink of atmospheric carbon monoxide (CO). The initial oxidation of CO is catalyzed by a CO-dehydrogenase (CODH), and the gene coxL encodes the large subunit of the enzyme. Only a few carboxydovore isolates were shown to oxidize atmospheric CO and little is known about the potential impact of global change on the ecophysiology of this functional group. The main objective of this study was to assess the impact of land-use and soil properties on coxL gene diversity and identify molecular indicators for the soil uptake of atmospheric CO. Soil samples were collected in three neighboring sites encompassing different land-use types, namely deciduous forest, larch plantation and maize field. CO uptake activity was related to total carbon and nitrogen content in soil, with the highest activity observed in deciduous forest. An extensive coxL database was assembled to optimize a PCR detection assay targeting sequences belonging to functional type I-CODH and hypothetical type II-CODH. Fully replicated coxL gene libraries unveiled a unique molecular signature in deciduous forest soil, with enrichment of type I sequences. Genetic profiles of larch and maize monocultures were not statistically different and showed higher level of coxL gene richness than deciduous forest. Soil water content and CO uptake activity explained 38% of the variation of coxL gene profiles in a canonical ordination analysis, leading to the identification of sequences belonging to the δ-Proteobacteria cluster as indicator for high affinity CO uptake activity. Enrichment of type I and δ-Proteobacteria coxL sequences in deciduous forest were confirmed by qPCR in an independent soil survey. CO uptake activity in model carboxydovore bacteria suggested that a significant fraction of detected putative high affinity CO oxidizers were active in soil. Land-use was a driving force separating coxL diversity in deciduous forest from monocultures.