Scanning Transmission Soft X-ray Microscopy of Cell and Tissue Samples from Spruces, Mice and Humans

This doctoral thesis covers studies of tissue and cell samples with scanning transmission X-ray spectroscopy (STXM) in soft X-ray energy range (100 - 1000 eV). STXM is based on X-ray absorption. The radiation transmitted through the sample at each location is measured as a function of radiation energy. The absorption of X-rays depends on the material it passes through. This can be used to chemically map the sample. The focus of this thesis was on finding out how well accumulated biomaterials can be detected and measured in biological specimens. The plant study was done in collaboration with Natural Resources Institute of Finland (Luke) to detect and differentiate valuable lignans from structural biomolecules in Norway spruce knotwood. We were able to detect lignans and differentiate them from lignin which is part of the cell wall. We were also able to differentiate the cell wall layers from each other based on their chemical composition. The experiments on mouse and human cells and tissues were done in collaboration with Pediatric Neurology Research Group, University of Oulu, and Biocenter Oulu to study sialic acid accumulation in Salla disease. The study was done with genetically modified mouse tissues and with Salla disease patient-derived fibroblasts. We were unable to detect the sialic acid accumulations in the Salla disease experiments, but this seemed to be a problem caused by common sample preparation methods. We were, however, able to distinguish cellular compartments using STXM. The overall result was that STXM can differentiate biological materials within a cell, however common sample preparation methods seem to remove water-soluble materials, leaving mostly structural materials intact. With further sample preparation development aiming to retain soluble materials, STXM should be a good tool to study cell and tissue samples. It can be used in medical research to help better understand diseases and their underlying mechanisms. It can also be used detect valuable biomolecules within plants, which can be valuable for the forestry industries.