Abstract
We present a cluster spatial analysis method using nanoscopic dSTORM images to determine changes in protein cluster distributions within brain tissue. Such methods are suitable to investigate human brain tissue and will help to achieve a deeper understanding of brain disease along with aiding drug development. Human brain tissue samples are usually treated postmortem via standard fixation protocols, which are established in clinical laboratories. Therefore, our localization microscopy-based method was adapted to characterize protein density and protein cluster localization in samples fixed using different protocols followed by common fluorescent immunohistochemistry techniques. The localization microscopy allows nanoscopic mapping of serotonin 5-HT1A receptor groups within a two-dimensional image of a brain tissue slice. These nanoscopically mapped proteins can be confined to clusters by applying the proposed statistical spatial analysis. Selected features of such clusters were subsequently used to characterize and classify the tissue. Samples were obtained from different types of patients, fixed with different preparation methods, and finally stored in a human tissue bank. To verify the proposed method, samples of a cryopreserved healthy brain have been compared with epitope-retrieved and paraffin-fixed tissues. Furthermore, samples of healthy brain tissues were compared with data obtained from patients suffering from mental illnesses (e.g., major depressive disorder). Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level. Furthermore, the presented workflow marks a unique technological advance in the characterization of protein distributions in brain tissue sections.
Highlights
Recent developments in fluorescence microscopy methods allow for the localization of single molecules with subdiffraction precision
Our work demonstrates the applicability of localization microscopy and image analysis methods for comparison and classification of human brain tissues at a nanoscopic level
The fast-imaging process further allows the recording of large sets of high-resolution images, which renders the comparative analysis between different tissue samples possible
Summary
Recent developments in fluorescence microscopy methods allow for the localization of single molecules with subdiffraction precision. The best known examples of deterministic imaging techniques include stimulated emission depletion and structured illumination microscopy.[1,2,3,4,5] In contrast, stochastic super-resolution imaging techniques rely on precise positional determination of single molecules and image reconstruction. These techniques include, for example, photo-activated localization microscopy and stochastic optical reconstruction microscopy.[6,7,8,9,10,11] One application for super-resolution microscopy is the accurate determination of a protein’s spatial and temporal cellular distributions. Apart from localization, these techniques provide additional information about protein cluster characteristics (e.g., number of molecules per cluster and density), which are not available when imaged with conventional diffraction-limited optics.[12,13] Recently, the mentioned techniques were adapted for imaging human tissues.[14,15,16] In our study, we applied STORM
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