Combination of techniques to quantify the distribution of bacteria in their soil microhabitats at different spatial scales

To address a number of issues of great societal concern at the moment, like the sequestration of carbon, information is direly needed about interactions between soil architecture and microbial dynamics. Unfortunately, soils are extremely complex, heterogeneous systems comprising highly variable and dynamic micro-habitats that have significant impacts on the growth and activity of inhabiting microbiota. Data remain scarce on the influence of soil physical parameters characterizing the pore space on the distribution and diversity of bacteria. In this context, the objective of the research described in this article was to develop a method where X-ray microtomography, to characterize the soil architecture, is combined with fluorescence microscopy to visualize and quantify bacterial distributions in resin-impregnated soil sections. The influence of pore geometry (at a resolution of 13.4 μm) on the distribution of Pseudomonas fluorescens was analysed at macro- (5.2 mm × 5.2 mm), meso- (1 mm × 1 mm) and microscales (0.2 mm × 0.2 mm) based on an experimental setup simulating different soil architectures. The cell density of P. fluorescens was 5.59 x 107(SE 2.6 x 106) cells g−1 soil in 1–2 mm and 5.84 x 107(SE 2.4 x 106) cells g−1 in 2–4 mm size aggregates soil. Solid-pore interfaces influenced bacterial distribution at micro- and macroscale, whereas the effect of soil porosity on bacterial distribution varied according to three observation scales in different soil architectures. The influence of soil porosity on the distribution of bacteria in different soil architectures was observed mainly at the macroscale, relative to micro- and mesoscales. Experimental data suggest that the effect of pore geometry on the distribution of bacteria varied with the spatial scale, thus highlighting the need to consider an “appropriate spatial scale” to understand the factors that regulate the distribution of microbial communities in soils. The results obtained to date also indicate that the proposed method is a significant step towards a full mechanistic understanding of microbial dynamics in structured soils.