Structural Circuits Core (SCC)

SCC led by

Paul Mermelstein, Medical School, Sarah Heilbronner, Medical School, Mark Sanders, Medical School and Thomas Pengo, U of M Informatics Institute.

The Structural Circuits Core (SCC) offers state-of-the-art anatomical mapping of neural circuits involved in addiction. Integrated with the University Imaging Centers (UIC) and UMN Informatics Institute (UMII), the SCC provides automated use of brain clearing technology paired with meso- and micro-scale imaging of the central nervous system.

P30DA048742-01A1, sub-project 6726

CURRENT SERVICES

CLEARING

The University Imaging Centers integrate state-of-the-art tissue clearing methods and technologies to help investigators prepare, image, and analyze biologically intact tissues and organs in three dimensions.

Tissue clearing brings a new dimension to histology services, where historically, tissue sectioning not only provides limited information of biological structures in its native form, but also proved to be a laborious and computationally intensive challenge in reconstruction from 2D to 3D. An assortment of tissue clearing methods has been developed in multiple laboratories within the last decade to make various tissues optically transparent by reducing light scattering intrinsic in tissues. This enables optimized whole-mount imaging on our specialized imaging systems, in particular, the Caliber ID RS-G4 Ribbon Scanning Confocal and the 3i Cleared Tissue Light Sheet (CTLS) microscope.

The UIC employs multiple tissue clearing approaches while primarily focusing on two: the PEGASOS organic-based and X-CLARITY hydrogel-based methods. PEGASOS and X-CLARITY are compatible with antibody and fluorescence staining, respectively, which allows for a comprehensive analysis of preserved internal structures.

IMAGING SYSTEMS

3i CTLS Light-Sheet Microscope

  • Sample dimension range 10mm x 10mm x 10mm

  • Lasers: 488 nm and 561 nm

  • Optimal with PEGASOS and other non-hydrogel methods

Caliber ID RS-G4 Ribbon Scanning Confocal Microscope

  • Sample dimension range 30mm x 30mm x 10mm

  • Lasers: 405 nm(not recommended), 488 nm, 561 nm, 647 nm and 785 (Reflectance Laser)

  • Optimal with X-CLARITY and PEGASOS methods

Resonant and Galvo Confocal Microscopes (A1RMP, A1Rsi-SIM, A1R-FLIM, C2 SPECTRAL)

  • For higher resolution applications with smaller field of views and spectral collection and spectral unmixing as needed.

ANALYSIS

  • Deformable registration (symmetric diffeomorphism) to the Allen Brain Atlas (ABA mouse P56 and rat currently) to either deform the atlas onto the image of the brain, or normalize the image of the brain into standard space.

  • Quantification of signal abundance in each ABA region in the original image

  • Estimation of cellular bodies count in each ABA region

  • Visualization using Bitplane Imaris, FIJI and open source software solutions

  • High speed networks (GSN )to enable data transfer, visualization, and analysis

SERVICES COMING SOON

  • Optimizing data handling and remote viewing for multi-terabyte data sets

  • Optimizing antibody labeling of cleared tissues with microwave-assisted methodology

SCC Staff

Paul G. Mermelstein, PhD is Associate Head and Professor of Neuroscience. He co-leads the SCC.

Sarah R. Heilbronner, PhD is an Assistant Professor of Neuroscience. She co-leads the SCC.

Thomas Pengo, PhD is the Director of Applications and Services at the University of Minnesota Informatics Institute. He oversees development and implementation of registration and analysis pipelines for the SCC.

Mark Sanders, PhD is the Program Director of the University Imaging Centers. He oversees development and implementation of clearing and imaging pipelines for the SCC.

Mary Brown, Patrick Willey and Nadia Kane are imaging specialists working with the SCC and UIC on brain clearing and imaging.

Publications