Why use intact samples for your research?

Take advantage of whole-sample methods to:

  1. Reduce processing work and view samples in multiple anatomical planes
  2. Localize regions of interest more confidently by visualizing organ-sized datasets that provide greater context
  3. Acquire data on all sample regions in parallel, facilitating analyses that are more quantitatively robust
  4. Explore fertile ground where novel and unexpected discoveries can take place

Histological analysis has classically been performed on thin tissue sections so that fine-scale features such as individual neuronal cell bodies and cellular processes can be resolved using light microscopy. This tissue-thickness limitation is due to two primary mechanisms: (1) contamination of the focal plane by out-of-focus light, and (2) the limited penetration depth of light into dense and highly-scattering tissues such as the brain.

Advances in optics such as confocal microscopy have largely mitigated light contamination issues, but even with multi-photon excitation light penetration limitations often preclude working with tissue pieces beyond ~1 mm in thickness. This restriction means that performing imaging and analysis on intact rodent organs that express fluorescent reporters, which are of interest in basic biology and disease-modeling studies alike, is typically out of reach even with either of these advanced microscopy techniques.

Optical tissue clearing, the approach of homogenizing the refractive index throughout the sample, offers an easy way around light penetration limitations and enables researchers to image cell-level detail in large, intact samples without the need for sectioning or even multi-photon microscopy. By using chemical engineering-inspired techniques such as CLARITY (Chung et al., 2013, Nature) and SHIELD (Park et al., 2018, Nature Biotech) to preserve the structural and biomolecular integrity of the sample before its light-scattering cell membranes are removed using a combination of detergents and electrophoresis, the sample can be rendered optically transparent and imaged en bloc using light-sheet microscopy.

What deeper questions can I address by overcoming the limitations of thin tissue sections (< 1mm)?

Studying rodent organs and other large samples intact offers numerous distinct advantages over classical thin-section histology.

First, destructively sectioning multi-millimeter -scale tissues into dozens or even hundreds of sections is not only time-consuming, but creates downstream challenges in that the sections need to be imaged individually and then aligned with one another using computational methods in order to digitally reconstruct the 3D organ from the series of 2D sections.

This multi-step workflow can introduce significant error as sections are lost, damaged, physically warped from sectioning and mounting processes, or cut at unintended off-plane angles, leading to misinterpretations and inaccuracies that can be propagated to adjacent sections. Keeping the sample intact not only obviates each of these issues, but by imaging the sample as one contiguous volume that can then be re-sliced virtually with cell-level resolution, researchers gain the unique opportunity to view the same sample in multiple anatomical planes. This greatly increases confidence when localizing features to a given brain region, and along with the ability to align this master dataset to a reference atlas aids transparency in publications and promotes reproducibility.

Second, studying organs such as the brain intact allows researchers to ask deeper and more meaningful questions by enabling all sub-regions of a sample to be studied in tandem in an objective manner. This helps combat spotlight effects and confirmation biases as well as creates fertile ground for unexpected discoveries to take place.

Traditional sectioning methods are plagued by limitations and pain points: time consuming, destructive, computationally expensive, and prone to confirmation and spotlight bias.

For instance, say you are studying a mouse model of schizophrenia. You may be inclined to look for cellular changes in the frontal cortical regions of the brain, where cognitive abilities affected in the disease state are thought to have their neural base. While effects observed in these areas may very well be important for understanding disease processes, lacking the context of what changes may exist in other brain regions makes these data hard to interpret. Indeed, studies have revealed a complex network of interconnections between frontal cortex and upstream areas such as the hippocampus and thalamus (Meyer-Lindenberg et al., 2005, Arch Gen PsychiatryWoodward et al., 2012, Am J Psychiatry), and the finding that these areas exhibit their own changes in schizophrenia highlights the value of adopting the big picture perspective that whole-organ analysis affords when investigating complex biology.

Basic biology experiments, such as those utilizing cutting-edge viral tracing tools (Callaway & Luo, 2015, J Neurosci) and sparse expression techniques, can also benefit greatly from whole-sample approaches. Revolutionary advances in rabies viral engineering have allowed researchers to visualize only those neurons that provide monosynaptic input to a spatially- and molecularly-defined group of starter cells. Such experiments offer long-sought answers regarding the brain’s wiring diagram, with brain-wide maps of the constellation of connected neurons being the end result.

Rather than physically sectioning the brain for imaging only to have to reassemble these images for analysis, experiments aimed at elucidating the areal topography of labeled cells can obtain more robust datasets ‒ i.e., without the ambiguity that arises from cell bodies being cut in two ‒ by clearing the brain and then imaging it intact using light-sheet microscopy. This streamlined workflow not only reduces the amount of hands-on time required to prepare and image the tissue in its entirety, but also enables even more sophisticated, higher-order analyses spanning the thickness of multiple tissue sections to be performed.

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