Small-scale geochemical gradients are a key feature of aquifer contaminant plumes, highlighting the need for functional and structural profiling of corresponding microbial communities on a similar scale. The purpose of this study was to characterize the microbial functional and structural diversity with depth across representative redox zones of a hydrocarbon plume and an adjacent wetland, at the Bemidji Oil Spill site. A combination of quantitative PCR, denaturing gradient gel electrophoresis, and pyrosequencing were applied to vertically sampled sediment cores. Levels of the methanogenic marker gene, methyl coenzyme-M reductase A (mcrA), increased with depth near the oil body center, but were variable with depth further downgradient. Benzoate degradation N (bzdN) hydrocarbon-degradation gene, common to facultatively anaerobic Azoarcus spp., was found at all locations, but was highest near the oil body center. Microbial community structural differences were observed across sediment cores, and bacterial classes containing known hydrocarbon degraders were found to be low in relative abundance. Depth-resolved functional and structural profiling revealed the strongest gradients in the iron-reducing zone, displaying the greatest variability with depth. This study provides important insight into biogeochemical characteristics in different regions of contaminant plumes, which will aid in improving models of contaminant fate and natural attenuation rates.

Light-sheet fluorescence microscopy (LSFM) provides access to multi-dimensional and multi-scale in vivo imaging of animal models with highly coherent volumetric reconstruction of the tissue morphology, via a focused laser light sheet. The orthogonal illumination and detection LSFM pathways account for minimal photobleaching and deep tissue optical sectioning through different perspective views. Although rotation of the sample and deep tissue scanning constitutes major advantages of LSFM, images may suffer from intrinsic problems within the modality, such as light mismatch of refractive indices between the sample and mounting media and varying quantum efficiency across different depths. To overcome these challenges, we hereby introduce an illumination correction technique integrated with depth detail amelioration to achieve symmetric contrast in large field-of-view images acquired using a low power objective lens. Due to an increase in angular dispersion of emitted light flux with the depth, we combined the dehazing algorithm with morphological operations to enhance poorly separated overlapping structures with subdued intensity. The proposed method was tested on different LSFM modalities to illustrate its applicability on correcting anisotropic illumination affecting the volumetric reconstruction of the fluorescently tagged region of interest.

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