NIH Public Access - Seeing Circuits Assemble

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This is a free access article from the NIH on the new technology allowing the observation of neurons being assembled in the brain - the imaging also shows disassembly of neurons, which was suspected in the past. We know that brains create and destroy neurons at the same time while building brains - now we can watch it happen.

Seeing Circuits Assemble

Jeff W. Lichtman^2* and Stephen J. Smith^1*

¹Department of Physiology, Stanford University, Palo Alto, CA 94304, USA

²Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA

^*Correspondence: Email: jeff@mcb.harvard.edu

Developmental neurobiology has been greatly invigorated by a recent string of breakthroughs in molecular biology and optical physics that permit direct in vivo observation of neural circuit assembly. The imaging done thus far suggests that as brains are built, a significant amount of unbuilding is also occurring. We offer the view that this tumult is the result of the intersecting behaviors of the many single-celled creatures (i.e., neurons, glia, and progenitors) that inhabit brains. New tools will certainly be needed if we wish to monitor the myriad cooperative and competitive interactions at play in the cellular society that builds brains.

Introduction

The 2008 Chemistry Nobel Prize shared by Shimomura, Chalfie, and Tsien adds an exclamation point to a revolution that biology, and most particularly neurobiology, has undergone since the dawn of molecular biology. The emergence of imaging as the tool of choice for the analysis of cellular and molecular phenomena in the nervous system has been stunningly rapid. Notably, many neuroscientists trained in electrophysiology or molecular biology have eagerly retooled to take advantage of the powerful new imaging-based approaches. Even those of us who have worked in this field for a long time are hard pressed, however, to keep up with the rapid pace of the ongoing innovations.

These new methods have been especially powerful for those researchers interested in understanding the ways in which neural circuits assemble. But new methods come with new challenges for the practicing neuroscientist. First, of course, is mastery of the diverse technologies of fluorescence-based optical imaging. Second is the challenge of learning how to turn images into data. If experiences of the two authors are any guide, neither of these challenges is trivial. Moreover, if our aim is to understand neurodevelopmental phenomena, even overcoming these challenges may be insufficient. Our aim here is to take stock of where this fast moving field is presently and where we think it might profitably head in the immediate future. We will emphasize the dominant role of imaging in modern attempts to explain the development of the nervous system. But as powerful as the new tools, which we will review briefly here, may be, we will also try to make the case that continuing efforts to develop new tools, still more powerful, will be needed to really begin to understand how the vast and intricate circuitry of the nervous system comes into being.

1. Imaging Biology

The triumphs that led to this imaging revolution occurred largely in the 1990s and are in two general areas: molecular biology and imaging technology. By the millennium, both of these fields more or less inadvertently coalesced in the GFP revolution. Now, thanks to genetically encoded labeling strategies, scientists can label virtually any aspect of the nervous system from widespread populations of neurons (Feng et al., 2000) to selective long axon tracks (Bareyre et al., 2005) to dendrite spines (Chen et al., 2000); from neuronal mitochondria (Misgeld et al., 2007) to synaptic vesicles (Meyer and Smith, 2006); from microtubule-associated proteins (Jacobs et al., 2007) to CaM kinase II (Shen et al., 1998); etc., and can do so in the brains of living animals!

The origins of the GFP revolution stem from the powerful molecular biology toolkit developed in the 1980s. Thus, when Prasher and colleagues obtained the sequence for GFP (Prasher et al., 1992), very little time passed before Chalfie and Tsien took advantage of his clone to demonstrate the magic of genetically encoded fluorescent labels (Chalfie et al., 1994; Heim et al., 1994). Because the background fluorescence of most animal cells is so low with the visible excitation used for GFP visualization, GFP provides inherently high sensitivity. In many circumstances, even single molecules of a fluorescent probe are visible. Moreover, because genetically encoded GFP is introduced by the cell's endogenous protein synthesis machinery, many of the problems of biological perturbation and spillage background associated with earlier methods of vital staining (e.g., with absorbance dyes like methylene blue a century earlier [Lu and Lichtman, 2007]or the decades old uses of exogenous fluorescence dyes [Honig and Hume, 1989; Magrassi et al., 1987]) are automatically circumvented. Other advantages include the fact that the cell can continue synthesizing the fluorescent protein throughout its life so it is possible to monitor the same cells over arbitrarily long durations even if some of the dye degrades or is bleached by imaging. Moreover unlike small organic fluorescent molecules, GFP evolved over the eons to have relatively low phototoxicity. The fluorescent moiety is an imidazolone ring structure that is formed by the posttranslational cyclization of a tripeptide, ser65-tyr66-gly67. It is situated at the center of the cylinder created by the 238 amino acid peptide along an alpha chain that runs down the center of protein (Yang et al., 1996; Ormö et al., 1996). Because fluorescent excitation can lead to free radical formation (see Lichtman and Conchello, 2005 for discussion), this design may keep the reactive species a bit removed from nearby unrelated proteins.

Ironically the initial uses of this tool—and perhaps the majority of its current uses—relate more to histology than to molecular biology. The emergence of imaging comes as a counterpoint to the molecular triumphs in neurobiology. Synaptic function (Sudhof, 2004), synaptic plasticity (Thomas and Huganir, 2004), axon pathfinding (Charron and Tessier-Lavigne, 2007), synaptogenesis (Montgomery et al., 2004), and neuronal migration (Hatten, 2002), to name a few, have all yielded to molecular analyses giving rise to the outlines of biochemical pathways as explanations for cellular phenomena. Now these same phenomena are being revisited with tools that allow them to be directly witnessed. For the first time it is possible to see synaptic vesicle release and recycling (Schweizer and Ryan, 2006), dendritic spine plasticity (Yuste and Bonhoeffer, 2004), axon pathfinding (Hechler et al., 2006), synaptogenesis (Alsina et al., 2001; Jontes and Smith, 2000; Niell et al., 2004; Meyer and Smith, 2006), and neuronal migration (Hatta et al., 2006).

How did all these phenomena become imageable? GFP, while certainly part of the story, is not the whole story. The 1990s not only saw a maturation of molecular biological sophistication but also were marked by breakthrough after breakthrough in imaging technologies. These advances included (1) the utilization of lasers as ultra-bright light sources for laser scanning confocal microscopy (Amos and White, 2003); (2) the advancement of solidstate detectors designed for low light level fluorescence imaging (Aikens et al., 1989); (3) the realization that nonlinear fluorescence excitation by 2- or 3-photon fluorescence excitation with a scanning pulsed laser gave optical sectioning, less photobleaching, and greater depth penetration (Denk et al., 1990); (4) the advent of a large number of small organic fluorescent probes that worked as Ca²⁺ indicator dyes (Tsien, 1989); and (5) the beginnings of the use of genetically encoded indicators such as the cameleons (Miyawaki et al., 1997; Zhang et al., 2002), the last two of these being the fundamental contributions from the lab of Roger Tsien—not to mention his central role in the development of a range of spectral variants based on GFP, for which he shared this year's chemistry Nobel.

The use of scanning microscopy techniques requires special comment. Confocal microscopy was first described by Marvin Minsky in the 1950s, but hardly anyone noticed (Minsky, 1998). In the last several years confocal imaging became commonplace when second generation spinning disc (Tanaami et al., 2002)and laser scanning approaches (Amos and White, 2003) both became robust enough to be commercially viable. This optical sectioning technique gives excellent images that are uncontaminated by out of focus light, but for imaging dynamics it has some serious drawbacks (Conchello and Lichtman, 2005). First confocal imaging has limited depth penetration in living tissue that scatters light, so it is not optimal for viewing thick volumes of in vivo. Second, confocal detection is inherently inefficient, often requiring more illumination of the live specimen than it can endure before bleaching or phototoxicity occurs. The invention of two-photon microscopy in 1990 (Denk et al., 1990) was a watershed, as this technique solved these two major problems with confocal in one stroke. Over the past 18 years many thousands of papers have used two-photon microscopy to image biological phenomena not only in neurobiology but also in immunology, developmental biology, and many other fields (Benninger et al., 2008). The rise of two-photon imaging has allowed the study of the live brain tissues in situ over periods of days to months with little or none of the phototoxicity effects that limited previous methods. Prior to two-photon microscopy, neurobiologists interested in structural dynamics of neural structures in intact organisms had to content themselves to work with accessible peripheral nervous system dendrites and synapses that could be imaged with much less sophisticated imaging tools (Purves et al., 1986; Lichtman et al., 1987).

Given the power of two-photon imaging it is remarkable that yet another revolution in imaging has also been underway to overcome what many have considered the most impenetrable barrier to understanding: the limited resolution of optical microscopy. Microscopists have traditionally accepted that imaging resolution was limited to approximately half the wavelength of light being detected due to the fundamental optical phenomenon of diffraction. This so-called hard limit in resolution hinders the ability of light microscopy to bridge the enormous chasm between the molecular interactions occurring on the scale of a few nanometers and images of neurons with resolutions that are at best several hundred nanometers. Researchers interested in molecular interactions have in some cases overcome this limitation by FRET-based imaging techniques in which fluorescence signals are modified by nanometer proximity between donor and acceptor fluorescent molecules (Roy et al., 2008). In addition, tracking single particles has long been accomplished with nanometer precision (Vale et al., 1996). But neither of these approaches produces actual images beyond the traditional diffraction limit. However, thanks to a number of new so-called “nanoscopic” fluorescence techniques (Hell, 2007), the diffraction barrier itself has been breached with what may soon provide electron microscope type resolution for standard fluorescence imaging applications. Techniques such as STED (Willig et al., 2006), PALM (Betzig et al., 2006), FPALM (Hess et al., 2006), STORM (Rust et al., 2006), and structured illumination (Gustafsson, 2005) provide the imager with a way to see fluorescently labeled structures with nanometer resolutions. Recent use of these approaches in fast modes allowed imaging dynamics in living cells at subdiffraction resolutions (Shroff et al., 2008; Hein et al., 2008).

While imaging tools have matured there has been a steady drift in the kinds of neural preparations that can be studied. Imaging neurons and glia in culture has traditionally been preferred over more intact preparations because of the greater transparency of monolayer cultures. While cellular dynamics such as growth cone behavior and dendritogenesis are much easier to image in cell cultures, the milieu is abnormally simple, motivating many developmental neuroscientists to migrate to more intact preparations such as slice cultures or acute slices. But neither acute nor cultured slices can be accepted uncritically as faithful models for an organism's development. Now, the use of two-photon imaging allows the imaging of CNS development over any time period desired.

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Tags: Psychology, brain, technology, NIH, Public Access, Seeing Circuits Assemble, neurons, glia, progenitors, neuroscience, Jeff W. Lichtman, Stephen J. Smith, Developmental neurobiology, imaging biology