Methods of dendritic spine detection: From Golgi to high-resolution optical imaging

Abstract

Dendritic spines, the bulbous protrusions that form the postsynaptic half of excitatory synapses, are one of the most prominent features of neurons and have been imaged and studied for over a century. In that time, changes in the number and morphology of dendritic spines have been correlated to the developmental process as well as the pathophysiology of a number of neurodegenerative diseases. Due to the sheer scale of synaptic connectivity in the brain, work to date has merely scratched the surface in the study of normal spine function and pathology. This review will highlight traditional approaches to the imaging of dendritic spines and newer approaches made possible by advances in microscopy, protein engineering, and image analysis. The review will also describe recent work that is leading researchers toward the possibility of a systematic and comprehensive study of spine anatomy throughout the brain.

Introduction

Throughout the nervous system, dynamic changes in the number and structure of synapses are a hallmark of normal development and aging (Engert and Bonhoeffer, 1999, Maletic-Savatic et al., 1999, Bosch and Hayashi, 2011). Dendritic spines, named by Ramon y Cajal after ‘espinas’ or thorns in his native Spanish, are post-synaptic protuberances abundant in glutamate receptors (GluR) found primarily at excitatory synapses directly opposed to a presynaptic bouton. Composed of a round spine head and a thinner spine neck, dendritic spines serve as the point of contact between two neurons with an increased concentration of postsynaptic signaling components such as GluR (De Paola et al., 2006). Due to their unique size and shape, they provide essential sites for local signal integration and molecular compartmentalization, isolating rapid changes in local second messenger pathways particularly calcium (Shepherd, 1996, Yuste et al., 2000, Yuste and Bonhoeffer, 2001, Alvarez and Sabatini, 2007).

Because they are easily observable features of neuronal morphology, dendritic spines have been stained and imaged in fixed brain tissue for over a century. The availability of fixed brain samples from human patients of neurological disorders has allowed investigators to observe correlations between dendritic spine density and morphology with disease progression. Additionally, the number and health of dendritic spines are correlated to the health and functionality of synapses; in many neuronal subtypes, such as hippocampal pyramidal cells, there is a one-to-one correlation between spine number and synapse number (Nimchinsky et al., 2004, Alvarez and Sabatini, 2007). The use of animal models has allowed for the observation of dendritic spines throughout development and their response to disease treatments. More recently, the coupling of live tissue imaging, particularly with the advent of two-photon laser scanning microscopy, with electrophysiology has led to studies which examine the physiology of individual dendritic spines and correlate changes in their size and structure to changes in physiology (Kasai et al., 2010).

The gain, loss, and morphological remodeling of dendritic spines are normal processes in development, as well as in learning and memory (Engert and Bonhoeffer, 1999, Maletic-Savatic et al., 1999, Bosch and Hayashi, 2011). Spine dynamics, including spine turnover and changes in spine shape and motility, are vital for the development and function of neural circuits (Calabrese et al., 2006). Though most spines are stable over a long imaging period, a proportion of spines transiently appear and disappear and these synaptic changes, driven by novel sensory experience, underline experience-dependent remodeling of specific neuronal circuits (Knott and Holtmaat, 2008). In the accepted model of neuronal development, a postsynaptic neuron projects numerous small, thin filapodia which sample local synaptic inputs (Bhatt et al., 2009). Filipodia that receive sufficient synaptic input, mature into dendritic spines while those that do not may be pruned. More recently, it has been demonstrated that in adulthood changes in the size and shape of dendritic spines correlate with plasticity at individual synapses (Matsuzaki et al., 2004).

Distortions in the normal patterns of neuronal signaling caused by disease or substance abuse can manifest as changes in dendritic spine density and morphology, accompanied by corresponding functional changes (reviewed extensively in this issue). Dendritic spine abnormalities have been found in many pathological conditions and excitatory synapse loss, which can be observed in individual neurons as a reduction in spine density, are strongly related to cognitive impairment in neurodegenerative diseases such as Alzheimer’s or Rett’s Syndrome (Moolman et al., 2004, Bittner et al., 2010). Reduced spine density of 27% and a decrease in total dendritic length and complexity have also been observed in medium spiny neurons of the caudate nucleus and the putamen from Golgi-stained post-mortem tissue of Parkinson’s patients (Stephens et al., 2005), indicating that synaptic dysfunction and degeneration are likely a common manifestation of neuronal insult and disease resulting from a range of unrelated causes. Strikingly, treatments that alleviate the cognitive symptoms of neurodegenerative disease also have been shown to reverse their respective spine pathologies (Smith et al., 2009). The specifics of the dendritic spine pathologies for a number of conditions are covered extensively in this issue.

The number, morphology, and dynamics of healthy synapses throughout the brain are excellent indicators of neuronal development and function and can provide investigators with information about specific brain regions and neuronal subtypes. Optical imaging of dendritic spines provides an attractive diagnostic tool for studies of synaptic health in clinical (post-mortem human tissues) and basic research studies (animal models of disease). A true understanding of the effects of disease states on synaptic structure on a system level requires a comprehensive evaluation of changes in spine density and morphology throughout the entire brain. This presents a rather daunting challenge for optical image acquisition and analysis on a number of levels. First, the study of neurons throughout the entire anatomy of the brain requires sample preparation and microscopy techniques sufficient to preserve submicron imaging resolution for all neuronal subtypes in all brain regions. Second, the enormous number of neurons in the brain (on the order of 10¹¹) and the incomprehensible level of connectivity between them (on the order of 10¹⁴ synaptic connections with ∼90% of these terminating in spines) tax the limits of our abilities to gather and analyze data (Williams and Herrup, 1988, Nimchinsky et al., 2004). As current high-resolution imaging techniques allow for the collection of massive amounts of three-dimensional anatomical data from individual specimens, informatics becomes the rate-limiting factor, i.e., the bottleneck in these studies has become accurate image analysis and classification of anatomical structures. Manual spine classification or computer-assisted manual spine classification, long the standard approaches, are extremely labor intensive and unacceptably slow as well as subject to investigator variability and poor for 3D image analysis. Recently, a great deal of progress has been made toward the development of software tools that can accurately analyze dendritic structure and detect all classes of dendritic spines reproducibly using objective criteria (Rodriguez et al., 2006, Rodriguez et al., 2008, Fan et al., 2009, Li et al., 2010, Zhang et al., 2010, Son et al., 2011). Although to the human eye, the criteria that determine just what is a dendritic spine seem obvious, defining these criteria in an objective manner has been a challenge in algorithm development.

This review will recount traditional tissue staining and microscopy approaches that have been and remain invaluable in the post-mortem analysis of human neurological disease progression. Additionally, we will touch on more recent genetic tools and microscopy advances that have enabled researchers to study spine dynamics and correlate spine structure to neuronal physiology in animal models. Finally, we will discuss roadblocks in our study of dendritic spine pathology and future technical solutions that may soon address them.