Coupled X-ray Fluorescence and X-ray Absorption Spectroscopy for Microscale Imaging and Identification of Sulfur Species within Tissues and Skeletons of Scleractinian Corals

Soft X-ray Fluorescence and Near-Edge Absorption Microscopy for Investigating Metabolic Features in Biological Systems: A Review

Scanning transmission X-ray microscopy (STXM) provides the imaging of biological specimens allowing the parallel collection of localized spectroscopic information by X-ray fluorescence (XRF) and/or X-ray Absorption Near Edge Spectroscopy (XANES). The complex metabolic mechanisms which can take place in biological systems can be explored by these techniques by tracing even small quantities of the chemical elements involved in the metabolic pathways. Here, we present a review of the most recent publications in the synchrotrons' scenario where soft X-ray spectro-microscopy has been employed in life science as well as in environmental research.

A Mineral-Doped Micromodel Platform Demonstrates Fungal Bridging of Carbon Hot Spots and Hyphal Transport of Mineral-Derived Nutrients

Soil fungi facilitate the translocation of inorganic nutrients from soil minerals to other microorganisms and plants. This ability is particularly advantageous in impoverished soils because fungal mycelial networks can bridge otherwise spatially disconnected and inaccessible nutrient hot spots. However, the molecular mechanisms underlying fungal mineral weathering and transport through soil remains poorly understood primarily due to the lack of a platform for spatially resolved analysis of biotic-driven mineral weathering. Here, we addressed this knowledge gap by demonstrating a mineral-doped soil micromodel platform where mineral weathering mechanisms can be studied. We directly visualize acquisition and transport of inorganic nutrients from minerals through fungal hyphae in the micromodel using a multimodal imaging approach. We found that Fusarium sp. strain DS 682, a representative of common saprotrophic soil fungus, exhibited a mechanosensory response (thigmotropism) around obstacles and through pore spaces (~12 μm) in the presence of minerals. The fungus incorporated and translocated potassium (K) from K-rich mineral interfaces, as evidenced by visualization of mineral-derived nutrient transport and unique K chemical moieties following fungus-induced mineral weathering. Specific membrane transport proteins were expressed in the fungus in the presence of minerals, including those involved in oxidative phosphorylation pathways and the transmembrane transport of small-molecular-weight organic acids. This study establishes the significance of a spatial visualization platform for investigating microbial induced mineral weathering at microbially relevant scales. Moreover, we demonstrate the importance of fungal biology and nutrient translocation in maintaining fungal growth under water and carbon limitations in a reduced-complexity soil-like microenvironment. IMPORTANCE Fungal species are foundational members of soil microbiomes, where their contributions in accessing and transporting vital nutrients is key for community resilience. To date, the molecular mechanisms underlying fungal mineral weathering and nutrient translocation in low-nutrient environments remain poorly resolved due to the lack of a platform for spatial analysis of biotic weathering processes. Here, we addressed this knowledge gap by developing a mineral-doped soil micromodel platform. We demonstrate the function of this platform by directly probing fungal growth using spatially resolved optical and chemical imaging methodologies. We found the presence of minerals was required for fungal thigmotropism around obstacles and through soil-like pore spaces, and this was related to fungal transport of potassium (K) and corresponding K speciation from K-rich minerals. These findings provide new evidence and visualization into hyphal transport of mineral-derived nutrients under nutrient and water stresses.

MAP2XANES: a Jupyter interactive notebook for elemental mapping and XANES speciation

MAP2XANES is an intuitive Jupyter notebook that automatizes the analysis of synchrotron X-ray fluorescence imaging and X-ray absorption spectroscopy for the characterization of complex and heterogeneous samples. The notebook uses basic modules and functions from Numpy, Scipy, Pandas, iPywidgets and Matplotlib libraries for a powerful data reduction process that, in just a few clicks, guides the user through the visualization of elemental maps, space-resolved absorption spectra and their automatized analysis. In particular, by means of linear combination fit of the XANES spectra, the notebook determines the chemical species distribution in the sample under investigation. The direct output of the analysis process is the correlation between the different elemental distributions and the spatial localization of the chemical species detected. An application to mineralogy is thus presented, analyzing the Mn²⁺, Mn³⁺ and Mn⁴⁺ distribution in a mineral sample of hausmannite (Mn²⁺Mn₂³⁺O₄), courtesy of the Museum of Natural Science of Barcelona.

Robust framework and software implementation for fast speciation mapping

One of the greatest benefits of synchrotron radiation is the ability to perform chemical speciation analysis through X-ray absorption spectroscopies (XAS). XAS imaging of large sample areas can be performed with either full-field or raster-scanning modalities. A common practice to reduce acquisition time while decreasing dose and/or increasing spatial resolution is to compare X-ray fluorescence images collected at a few diagnostic energies. Several authors have used different multivariate data processing strategies to establish speciation maps. In this manuscript, the theoretical aspects and assumptions that are often made in the analysis of these datasets are focused on. A robust framework is developed to perform speciation mapping in large bulk samples at high spatial resolution by comparison with known references. Two fully operational software implementations are provided: a user-friendly implementation within the MicroAnalysis Toolkit software, and a dedicated script developed under the R environment. The procedure is exemplified through the study of a cross section of a typical fossil specimen. The algorithm provides accurate speciation and concentration mapping while decreasing the data collection time by typically two or three orders of magnitude compared with the collection of whole spectra at each pixel. Whereas acquisition of spectral datacubes on large areas leads to very high irradiation times and doses, which can considerably lengthen experiments and generate significant alteration of radiation-sensitive materials, this sparse excitation energy procedure brings the total irradiation dose greatly below radiation damage thresholds identified in previous studies. This approach is particularly adapted to the chemical study of heterogeneous radiation-sensitive samples encountered in environmental, material, and life sciences.