high-throughput morphometric analysis of individual neurons

© Oxford University Press 2004; all rights reserved Cerebral Cortex DOI: 10.1093/cercor/bhh016

High-throughput Morphometric Analysis of Individual Neurons

Chi-Cheng Wu1, John F. Reilly1, Warren G. Young1,

John H. Morrison1,2 and Floyd E. Bloom1,3

1Neurome, Inc., 11149 North Torrey Pines Rd, La Jolla,

CA 92037, 2Fishberg Research Center, Mount Sinai School of

Medicine, Neurobiology, Box 1065, One Gustave L. Levy

Place, New York, NY 10029 and 3Department of

Neuropharmacology, The Scripps Research Institute, 10550

N. Torrey Pines Rd, La Jolla, CA 92037, USA

To facilitate high-throughput quantitative analysis of neuronal struc-ture, this study optimized the diOlistic method of whole neuronlabeling to examine multiple neurons in fixed brain, and optimizedimage acquisition parameters to preserve signal for subsequentphotoconversion. Fluorescent dye-coated gold particles weresuccessively delivered by helium-powered ejection to 250 µm thickbrain slices with loading density and penetration depth optimized tomaximize the yield of labeled neurons within the slice while avoidingoverlapping labeled dendritic processes in the x–y plane and z-axis.Labeled neurons were imaged using confocal laser-scanning micros-copy with pinhole aperture and scan speed enhanced to minimizecapture time and fluorescence degradation. Optimized image acqui-sition parameters preserved fluorescence signal and facilitatedsubsequent oxygen-enriched photoconversion for higher magnifica-tion dendritic spine analysis. Sampling criteria limited analysis toneurons whose z-axis dendritic processes were fully containedwithin the tissue slice and in which dye transport extended to themost distal portions of the dendrites. The yield of completely labeledneurons was, on average, more than 20 cells per brain region peranimal. With optimized spatio-temporal diOlistic loading parameters,along with image acquisition parameters optimized for subsequentphotoconversion, the present protocol provides a high-throughputstrategy for full-scale quantitative analysis of three-dimensionalneuronal morphology.

Keywords: cell morphology, diOlistic, photoconversion, single-cell resolution

IntroductionThe current methods for morphological characterization and

quantitative analyses of single neurons, such as Golgi staining,

intracellular injection and neuronal transfection, are labor-

intensive, technically demanding, and do not readily yield large

numbers of completely reconstructed neurons. Golgi impreg-

nation relies upon the crystallization of silver chromate.

However, the staining selectivity only labels less than 2–10% of

the neurons, which is insufficient for quantitative analysis, and

there is no experimental control over selection of neurons to

be studied. Moreover, data analysis is compromised by incom-

plete impregnation, unavoidable loss of dendritic branches due

to the plane of sectioning, and indistinguishable overlapping

fine dendritic processes. Dye loading into single cells by micro-

injection using intracellular or patch pipettes generates excel-

lent single-cell labeling but is technically demanding (e.g. Buhl

and Schlote, 1987; de Lima et al., 1990; Schmidt et al., 1996;

Taylor et al., 1996; Arnold et al., 2001; Morgan and Ohara,

2001; Duan et al., 2002). One of the major methodological

concerns with these techniques is that quantitative analysis

relies heavily upon subjective evaluations. The pipette tips are

maneuvered manually, thus the loading is likely to occur in

easy-to-access areas, such as a superficial cell layer, and/or in

large-diameter neurons. Therefore, the sampling of intra-

cellularly loaded cells often does not reflect the entire neuronal

population. Moreover, injection-induced damage and/or leakage

of dye via the needle track often results in unwanted labeling of

neighboring cells, which reduces the signal-to-noise ratio.

Using neuronal transfection methods, including micro-injec-

tion (Hall et al., 1997), electroporation (Lurquin, 1997), lipo-

fection (Strauss, 1996) and viral transfection (Robbins et al.,

1998), introducing DNA constructs into target cells and tissues

has become routine for examining gene regulation and func-

tion of the nervous system and for characterization of neuronal

morphology. However, several variables are responsible for

poor transfection efficiency using these methods. These

include DNA coating efficacy and intrinsic cell viability in the

cultures (Biewenga et al., 1997).

This neuronal transfection method has been improved by a

‘biolistic’ approach for in situ transfection and labeling of cells

(Lo et al., 1994; Usachev et al., 2000; O’Brien et al., 2001; Jin et

al., 2001; Danzer et al., 2002; Klimaschewski et al., 2002; Sun

et al., 2002). In this system, a hand-held gene gun utilizes a

pulse of helium gas to propel small particles coated with desic-

cated DNA, crossing plasma membrane to target cells. This

technique does not require the specialized equipment and

expertise that the conventional intracellular injection methods

rely upon. Furthermore, this biolistic approach provides a

means for random sampling, which is ideal for full-scale quanti-

tative analysis. However, temperature changes, decreased

atmospheric pressure, and high pressure-induced membrane

disruption potentially challenge the cell cycle and transcrip-

tion activity after bombardment, thereby affecting the expres-

sion of a gene product and the success of transfection

(Biewenga et al., 1997; Thomas et al., 1998).

A recent advancement of the biolistic approach has been

reported by Gan et al. (2000), who employed a gene gun to

propel gold particles coated with various combinations of

lipophilic dyes to target multiple neurons in live as well as

fixed slices. Although suitable for visualizing complex cell–cell

interactions, the ‘multi-diOlistic’ loading of neurons results in a

high density of labeled neurons, which constrains the ability to

perform quantitative morphological analysis of individual

neurons.

The present study had two goals: (i) to enhance the yield of

non-overlapping labeled neurons in a given brain region by

standardizing morphological criteria for cell sampling under

controlled conditions of dye-coated gold particle delivery, and

(ii) to optimize the image acquisition process parametrically to

reduce photo-bleaching, and facilitate non-fluorescent optical

analysis of dendritic spines following a protocol for high-

throughput photoconversion. The present study presents a

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of 12 High-throughput Morphometric Analysis of Individual Neurons • Wu et al.

standardized and efficient workflow that combines high-

throughput randomized diOlistic loading, optimized image

acquisition and photoconversion for the comprehensive quan-

titative analysis of individual neuronal morphology. Prelim-

inary data of the present study have been reported in abstract

form (Wu et al., 2003).

Materials and Methods

Tissue Preparation and Storage

Ninety-day-old male C57BL/6 mice (n = 12) were anesthetized with

avertin (0.5 mg/g body weight) and transcardially perfused with

normal saline followed by 4% paraformaldehyde (PFA) in 0.1 M phos-

phate buffer (PB). Brains were dissected and post-fixed with 4% PFA

overnight. After postfixation, the brains were coronally sectioned

(250 µm) using a vibratome. The anterior–posterior axis of the

hippocampus was subdivided into three levels based on the atlas of

Hof et al. (2000). The brain sections were collected and stored in 4%

PFA at 4°C prior to diOlistic shootings. The postfixation period varied

from 1 h to 2 weeks, which allowed for repetitive delivery of the parti-

cles to the brain sections (see below). After delivery of the particles,

the sections were stored in freshly made 4% PFA for confocal imaging

(see below).

Gene Gun Bullet Preparation

The current protocol was developed partly based on the manufac-

turer’s manual (BioRad, Hercules, CA) and the procedure of Gan et al.

(2000).

Tefzel tubing (BioRad) was placed on a tubing preparation station

(BioRad) and air-dried for 45 min using nitrogen gas (0.4 l/min).

Fifteen milligrams of gold particles (1.6 µm in diameter; BioRad) were

thoroughly/evenly spread (2 × 2 cm2) on a glass slide using a razor

blade. Five milligrams of 1,1′ -dioctadecyl-3,3,3′,3′ -tetramethylindocar-

bocyanine perchlorate crystals (DiI; Molecular Probes, Eugene, OR)

were dissolved in 500 µl methylene chloride and then gently dropped

onto the thin layer of gold particles on the glass slide. The DiI-coated

gold particles were carefully scrapped off with a razor blade,

collected, and sonicated in 3 ml of distilled water for 30 min. In order

to prevent aggregation of DiI-coated particles, 0.75 µl poly-

vinylpyrrolidone (20 mg/ml) was added to the sonicated solution. The

solution was then vortexed for 15 s and immediately injected into the

pre-dried tubing. Slow and continuous injection was crucial to

prevent inclusion of air bubbles. The tubing was rotated for 30 min to

allow the DiI-coated particles to precipitate and settle onto the inside

surface of the tube (also see Discussion). The solution was then slowly

withdrawn and the particle-coated tube was rotated and air-dried

under constant nitrogen flow (0.4 l/min) for 2 h. The particle-coated

tube was then cut into small pieces (microcarriers), and stored in a

desiccated environment at room temperature. In order to maintain the

quality of the labeling, the bullets were used within 24 h after coating.

Delivery of Particles

A commercially available biolistic ‘Helios gene gun system’ (BioRad)

was used to propel DiI-coated particles into fixed tissue. The gene

gun was stabilized by a custom-fabricated adjustable stand with a

mobile z-axis (see Supplementary Material Fig. S1). A custom-fabri-

cated centering tool was used to adjust the distance of the gun from

the target tissue (3.0 cm) and to pinpoint the focus point of the

landing field of the delivered particles. In addition to the manufac-

turer’s diffusion screen, a membrane filter with a 3 µm pore size and

8.0 × 105 pores/cm2 (Falcon 3095; BD Biosciences Discovery Labware,

Bedford, MA) was placed between the gun and the tissue to filter out

large clusters of coated particles and to avoid shock wave damage to

the tissue. The particles were accelerated using inert helium gas

(200 psi) and each side of the tissue was shot up to three times inde-

pendently to enhance the yield of labeling. Each shooting was

performed after completion of confocal image acquisition (see

below).

Confocal Imaging and Optimized Parameters

Labeled neurons were imaged using a Zeiss CLSM PASCAL laser-scan-

ning confocal microscope (Carl Zeiss, Thornwood, NY) equipped

with a 10× Plan NeoFluar objective lens [numerical aperture (NA) =

0.3] and a 25× Plan NeoFluar water-immersion objective lens (NA =

0.8). For through-focus imaging, optical sections were collected using

the 25× objective with 0.5–1.2 µm z-axis steps to cover the full depth

of the dendritic trees. The z-axis stack compression that resulted from

water immersion was automatically corrected by the analysis soft-

ware. The 2-D stacks were superimposed digitally and the full 3-D

dataset was generated for visualization of dendritic complexity.

Labeled structures were excited using a 1 mW He:Ne laser (543 nm for

DiI) with their emissions passed through a 560 nm long pass filter set.

After scanning, images were taken using the 10× objective to docu-

ment anatomical localization of DiI-labeled neurons against a reflect-

ance-imaged background.

In order to enhance the imaging process, the pinhole aperture and

scan speed were systematically investigated and optimized. Targeted

neurons with either simple or complex dendrites were imaged separ-

ately using different pinhole apertures (48, 73 and 88 µm) with scan

speed held constant. Similarly, targeted neurons were imaged separ-

ately using different scan speeds (1.9, 3.9 and 7.8 s/scan), while

pinhole aperture was held constant. The scanned images were digi-

tized and reconstructed, and their dendritic lengths were then quanti-

fied and compared (see Results).

Morphological Criteria for Cell Sampling

The criteria for selecting completely labeled targeted neurons were

based on (i) the loading of DiI-coated gold particle in the soma, which

was found to yield optimal dye transport; (ii) the tapering of DiI in the

most distal dendrites; (iii) the visualization of the complete 3-D profile

of dendritic trees using the 3-D display of Zeiss CLSM 5 PASCAL soft-

ware (v2.8; Carl Zeiss). Neurons with incomplete dye transport and

neurons with truncations due to the plane of sectioning were not

collected. Moreover, cells with dendrites labeled retrogradely by

particle impacts in the surrounding neuropil were excluded. In the

present study, the types of labeled neurons collected included pyram-

idal cells in CA1 and granule cells in the dentate gyrus of the mouse

hippocampus.

Double-labeling Procedures

For visualizing targeted neurons, the sections were pre-incubated in

Hoechst 33258 (10 mg/ml, Molecular Probes), a fluorescent nucleic

acid stain, for 15 min prior to diOlistic labeling. The precision of

neuron loading was visualized by the co-labeling of Hoechst-stained

nuclei (blue channel) and DiI-coated particle (red channel) under

epi-fluorescence microscopy. To examine the spatial correlation of

dendritic complexity of the neurons and their anatomical location,

sections containing labeled neurons were incubated with NeuroTrace

green fluorescent Nissl 500/525 (1:100 in PBS, Molecular Probes) for

2 h and then imaged using confocal microscopy.

Neuronal Tracing and Data Analysis

The stacks of digitized 2-D images were downloaded and exported as

a series of TIFF images to a PC workstation (530 MT, Dell, Round

Rock, TX) and Neurolucida (MicroBrightField Inc., Williston, VT) was

used to contour the dendritic processes of the digitized 2-D images.

During the course of contouring, the 3-D dendritic geometry was visu-

alized using the Zeiss CLSM PASCAL 3-D display software, with glow-

scale image processing used to highlight neuronal processes.

All of the reconstructed data were exported to NeuroExplorer

(MicroBrightField Inc., Williston, VT) for quantitative analysis. Total

dendritic length and averaged lengths of each dendritic branch of

labeled CA1 pyramidal neurons were generated using dendrogram and

Sholl analysis, respectively. To validate the imaging parameters, each

neuron was scanned under different pinhole apertures and scan

speeds and then contoured three times each. Total dendritic length

and average length of each dendritic branch were compared to

examine the inter-trial variability. The results were analyzed using uni-

and multivariate analysis of variance and Bonferroni post hoc tests,

with significance set at P < 0.05 and 0.001, respectively.

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Cerebral Cortex of 12

Photoconversion Protocol

After confocal imaging, the sections were washed 3 × 10 min with PBS

and pre-incubated in filtered ice-cold diaminobenzidine tetrahydro-

chloride (DAB, Sigma, St Louis, MO) solution (1.5 mg/ml in 0.1 M Tris

buffer, pH 8.2) for 6–12 h, a period that optimized the full penetration

of DAB into 250 µm tissue slabs. Results from preliminary studies led

to complete omission of all H2O2 (0.1%) from the DAB solution. After

washes for 3 × 10 min, the sections were transferred to a custom-fabri-

cated closed conversion chamber (CCC; see Supplementary Material

Fig. S2), modified from Kacza et al. (1997).

The chamber was connected with silicone tubing that regulated the

in- and out-flow of pure oxygen, which is suggested to significantly

enhance the photoconversion process (Sandell and Masland, 1988;

also see Lübke, 1993; Kacza et al., 1997). The sections were soaked in

10 ml DAB solution in the reservoir bath within the CCC and then

covered with a plastic plate with a tightly fitting passage that allowed

the 10× objective to navigate both horizontally and vertically to focus

on the tissue during the conversion process. The light source was

supplied by a 100 W mercury lamp. The airflow within the chamber

was carefully regulated to prevent tissue dehydration. Unlike most

photoconversion protocols (e.g. Buhl and Schlote, 1987; Balercia et

al., 1992), the current protocol did not require frequent replenishing

of the ice-cold DAB solution during conversion. The conversion

process consisted of 30–45 min of exposure to epi-fluorescent illumi-

nation at 546 ± 30 nm, and when necessary, as for complex cell types

such as pyramidal cells, the DAB solution was periodically exchanged

with fresh DAB solution in the CCC to enhance the photoconversion

process. Step-through focus of the light source during conversion was

found to facilitate the quality of the final DAB reaction product. Low

concentrations of glutaraldehyde were evaluated (0.05%) and elimi-

nated as a fixative during perfusion because it substantially enhanced

background fluorescence and thus increased non-specific background

staining of the tissue.

The photoconverted tissue was then rinsed 3 × 10 min in PBS, and

exposed to 0.1% osmium tetroxide for 3–5 min. In order to reduce

shrinkage of neuronal structures, tissue sections were not dehydrated

but mounted directly on slides and coverslipped with GelMount

(Biomeda, Foster City, CA) for light microscopic analysis.

Results

DiOlistic Loading

In the present study, the custom-fabricated adjustable stand

was used to standardize and optimize the parameters of the

diOlistic labeling protocol. Large diameter gold particles (diam-

eter 1.6 µm) were found to penetrate into individual soma

(Fig. 1A) more efficiently than those with smaller diameters

(0.6 and 1.0 µm), since the latter tended to clump together

following diOlistic delivery, producing labeled cells with over-

lapping and unanalyzable structures (see Fig. 1B,C).

Using 200 psi of helium pressure, the particles were deliv-

ered, on average, 65–85 µm below the surface of a fixed

coronal slice (arrows in Fig. 1D). This penetration depth not

only reduced the labeling of neurons whose dendrites were

truncated as a result of the prior tissue sectioning, but it also

allowed for successive delivery of particles to target cells on

Figure 1. (A) Gold particle (1.6 µm) in the soma visualized immediately following diOlistic delivery. (B) Ectopic loading of gold particles in the soma, which produces a ‘ghost’ neuronadjacent to target neurons. (C) Clumping of loaded particles in the neuropil results in retrograde transport of DiI, which makes it extremely difficult to discriminate the origins(somata) of these overlapped dendritic processes. (D) Penetration of DiI-coated particles in the fixed section 15 min after diOlistic shooting. Two particles were found at depths of65 and 85 µm. Note the transport of DiI in dendritic processes (arrowheads). The optical thickness was restricted to 150 µm, devoid of the remaining portion of the section. Mon-ochrome CLSM image was pseudo-colored with glow-scale image processing to highlight neuronal processes. (E) High-resolution morphology of an individual neuron (blue:Hoechst-stained nuclei; red: DiI-coated particles and dendritic spines). It was noted that the DiI-coated particle was located within the soma.


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both sides of the tissues sufficiently far apart to avoid over-

lapping of their dendritic trees in the z-axis. The latter was

especially critical for enhancing the yield of loading, since

loading cells onto both sides of the tissue slice at different time

points appears technically impossible using conventional

methods. Moreover, to identify targeted cells precisely, the

double-labeling method was used to visualize Hoechst-stained

nuclei and DiI-coated particles within the soma (Fig. 1E). The

penetration of a single DiI-coated particle within the soma was

found to produce the optimal dye transport of neuronal

processes. Note the absence of lateral diffusion of DiI along the

penetration path, confirming an adequate velocity of bombard-

ment using the current protocol.

Placement of a cell culture filter between the gene gun and

the tissue was used to filter aggregated particles, and enabled

us to disperse single dye-coated gold particles within the tissue

(Fig. 2A). Optimal inter-particle distance of loaded somata

varied between 75 and 100 µm over the target area, which is

much greater than previously suggested by Gan et al. (see

detail in Discussion). The combination of optimized loading

density and penetration depth significantly reduced overlap-

ping of dendritic processes between labeled neurons and,

therefore allowed for full 3-D visualization of the neuronal

dendritic trees. Figure 2B presents a collapsed CLSM image in

which several dentate granule cells (GC) were concurrently

labeled at an interval of 80–100 µm in the dorsal and ventral

blades of the dentate gyrus, allowing for independent visualiza-

tion with minimal overlapping of labeled dendritic processes.

The somata of labeled cells were mainly located in the deep

granule cell layer (GCL). Note that the somata in the middle

position of Figure 2B (asterisk) did not contain labeled proc-

esses, mainly due to insufficient diffusion of DiI (see Discus-

sion). One advantage of using DiI as a marker is that it labels

extremely fine structures, such as spine necks, that are poorly

illuminated by conventional intracellular loaded dyes. For

example, Lucifer yellow (LY) readily diffuses through neuronal

cytoplasm, which not only significantly increases background

fluorescence, but also yields a LY-labeled dendritic trunk with

detached spine heads (Fig. 2C,D). On the other hand, the trans-

port of DiI efficiently labeled various types of spines with high

resolution (arrows in Fig. 2D), assuring the quality of the subse-

quently photoconverted DAB (see below).

Morphological Criteria and Effective Yield of Cell

Loading

In order to avoid artificial truncation of the dendritic tree,

sampling of loaded neurons was limited to those with cell

bodies sufficiently deep to the cut surface. Because an epi-fluo-

rescent microscope is optically limited to the x–y plane, a

confocal laser-scanning microscope was utilized to adequately

visualize the z-axis of labeled neurons. Zeiss 3-D display CLSM

PASCAL software was used to monitor full dendritic geometry

Figure 2. (A) Optimized dispersion of DiI-coated particles following delivery. The distance between particles, on average, varied between 75 and 100 µm (see detail in text).(B) Multiple cells were concurrently labeled in the dentate gyrus of hippocampus following diOlistic shooting. The inter-particle distance among three-labeled somata was ∼ 80 µm.Note the neuron in the middle position did not contain labeled processes (asterisk). (C, D) Comparison of spine density labeled by Lucifer yellow (LY) and DiI. Note that some spinesappear detached from the dendritic trunks labeled by LY (arrows). Abbreviations: GCL, the granule cell layer; ML, the molecular layer; HL: hilus.


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with a 360° image rotation. This helped to verify the complete

filling of transported dye, which was evidenced by the tapering

of DiI in the most distal dendrites (arrows of Fig. 3A,B). Impor-

tantly, the lateral view of the CLSM image was used to verify

that the full extent of the dendritic profile of labeled neurons

(arrows of Fig. 3C) was contained within the slice. Neurons

with insufficient transports of DiI (arrows of Fig. 3D,E), due to

suboptimal fixation of tissue and/or inconsistent coating of DiI

to gold particles, or neurons with amputation of primary

dendritic processes (arrows of Fig. 3F) were excluded during

the sampling process.

Figure 4A,B illustrates full 3-D views of diOlistically labeled

neurons found in CA1 and the dentate gyrus of the mouse

hippocampus (see Supplementary Material Movies 1–2). The

basal dendrites of the labeled pyramidal cell reached the pial

surface, reflecting the optimal transport of DiI to the distal

dendrites (Fig. 4A). Similarly, we observed dentate GCs whose

apical dendrites were fully labeled throughout the molecular

Figure 3. Morphological criteria of diOlistic sampling. (A, B, C) Selection of a pyramidal neuron with complete transport of DiI in dendritic processes. Arrows indicate the taperingof DiI in most the distal dendrites. Lateral view of the images was used to verify the full dendritic profile (arrows in C). (D, E, F) Exclusion of a neuron with amputated dendriticprocesses. Incomplete transport of DiI was revealed in D and E (arrows). Lateral view reveals amputated apical dendrite (arrows in F).

Figure 4. DiOlistically labeled neurons with full 3-D visualization of dendritic trees. (A) A pyramidal cell of the dorsal portion of the CA1 was found to extend basal dendrites to thepia surface (asterisk). (B) A dentate granule cell with fully labeled dendritic trees in the molecular layer (ML). Note that the soma was located in a relatively deep position of thegranule cell layer (GCL). (C) Spatial correlations of the dentate ML and the dendritic arbors of labeled granule cell. See Supplementary Material movies 1–3 for 360° rotations ofimage stacks.


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layer (ML; Fig. 4B). In some cases, the somata of GCs resided in

a deep portion of the GCL and thus had an initial unbranched

apical dendrite (also see Fig. 2B). DiOlistic labeling with DiI

was combined with NeuroTrace, a fluorescent Nissl stain, to

reveal the laminar location of labeled neurons and dendritic

arbors (Fig. 4C). Thus, diOlistically labeled granule cell

dendrites could be defined relative to their position within the

dentate ML (see Supplementary Material, Movie 3). Dentate

granule cells located in a more superficial portion of GCL

tended to branch immediately upon entering the molecular

layer.

Based on the current protocol, on average, 20 analyzable

cells per region per animal were obtained. For example, in the

course of the anterior–posterior axis of CA1, the peak distribu-

tion of labeled cells was found in the mid-level of the hippo-

campus, mainly due to its prominent anatomical area (Fig. 5A).

Similar results were found in the dentate gyrus (∼ 25 cells/

animal; not shown). These yields significantly outnumber that

reported for other conventional cell loading methods (see

Discussion). Following diOlistic delivery, there was a high

degree of morphological heterogeneity of CA1 pyramidal cells

that varied with regard to their anatomical sites (see Fig. 5B).

Figure 5. (A) Distribution of diOlistically loaded pyramidal neurons in the A–P axis of the CA1. The anterior, middle, and posterior portion of the hippocampus were divided basedon Hof et al. (2000), each of which was composed of four serial sections. The middle level contained a relatively larger portion than the remainder of the CA1. (B) The heterogeneityof diOlistically loaded pyramidal neurons in the CA1 of the hippocampus. Note the difference in dendritic morphology of pyramidal cells relative to their anatomical locations. (C) Themontage image of the hippocampus following multiple diOlistic shootings. Arrows indicate specific cell types of the hippocampus (red: CA1 pyramidal cells; blue: granule cells;yellow: polymorphic cells). (D, E) Pyramidal, granule, and polymorphic cells were concurrently labeled in the same section as shown in C. The color contrast of CLSM images wasadjusted using Zeiss PASCAL software. Abbreviations: DG, dentate gyrus; GC, granule cell; HL, hilus; PYC, pyramidal cell; polymorph., polymorphic cell.


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Note that several pyramidal cells were concurrently labeled in

the same section (the third figure of lower panel in Fig. 5B).

More importantly, the current protocol optimally loaded

multiple cells in other hippocampal subfields, including the

dentate gyrus and the hilus (colored arrows in Fig. 5C). High-

magnification images of labeled cells from Figure 5C are

presented in Figure 5D and E. Thus, the present study demon-

strates that successive diOlistic shootings of the same tissue

slice can be used to yield a large population of labeled neurons.

The inherent random sampling approach of the diOlistic

method is ideal for quickly and reliably revealing inter-animal

variability. In the present study, a pilot analytical study was

conducted by reconstructing diOlistically labeled CA1 pyra-

midal neurons of 90-day-old male C57 mice (n = 4). Morpholog-

ical differences of randomly labeled cells along the anterior-to-

posterior axis of the hippocampus (n = 10 cells/animal) were

quantified and compared by using dendrograms and Sholl

analysis (NeuroExplorer). In the dendrogram analysis (Fig. 6A),

a significant main effect on total length of apical dendrites was

found across the four mice (P < 0.05), whereas only a marginal

difference was found for basal dendrites. In the Sholl analysis

(Fig. 6B,C), the number of intersections of both apical and

basal dendrites was compared at 10 µm intervals from the soma

and was found to vary significantly among the four mice (P <

0.05). Although the total number of dendritic intersections

varied across the four mice, the total number of dendritic inter-

sections peaked at similar distances from the soma (arrows in

Fig. 6B,C). In apical dendrites, dendritic intersections peaked

at a distance of 65–215 µm from the soma, whereas in basal

dendrites, the peak was found at an approximate distance of

50–135 µm from the soma. Note that this pilot study did not

investigate hippocampal asymmetry, therefore no information

regarding inter-animal difference in the above-mentioned

dendritic parameters is available. The reported data of dendro-

grams and Sholl analysis strongly suggest that robust quan-

titative analyses can be obtained from diOlistically labeled

neurons.

Optimization of CLSM Imaging Parameters

High-resolution confocal images require a small pinhole aper-

ture with a long scan speed in order to optimize signal-to-noise

ratio. However, the consequence of lengthy scanning is

bleaching of fluorescent signal in small-diameter dendritic

spines. Also, because the intensity of membrane labeling

decreases in proportion to the distance from the soma, scan-

ning with a small pinhole aperture results in loss of fluorescent

labeling in distal dendrites. To retain these subtle signals, the

total scan time was reduced by increasing the pinhole aperture

and shortening the scan speed at the expense of increased

background fluorescence.

To test whether this optimization would affect image acqui-

sition or quantitative data with respect to variability (three

trials per image; also see Experimental Procedures), confocal

images of the same labeled neurons were acquired with 48, 73

and 88 µm pinhole apertures, and the total dendritic length

was obtained with reconstruction. ANOVA revealed a signifi-

cant main effect of pinhole aperture between the three groups

(P < 0.001). Bonferroni post hoc test confirmed that total

dendritic length was smaller with 48 µm-pinhole scanned

images (see Supplementary Material Fig. S3-A) compared to 73

or 88 µm-pinhole scanned images (P < 0.001), while no differ-

ence was found between the other two groups. It was noted

that scanning with a pinhole aperture of 48 µm underestimated

the total dendritic length by ∼ 10% compared to images

collected with 73 and 88 µm apertures. An interaction effect

was also found between pinhole aperture and branch order

(P < 0.05) and post hoc tests showed that the averaged length

of the most distal, sixth-order dendrites was underestimated

using 48 µm pinhole aperture (P < 0.05), while no difference

was found in other branch orders among the three groups

(see Supplementary Material Fig. S3-B). Therefore, the under-

estimated total dendritic length with the 48 µm pinhole aper-

ture is mainly attributable to the loss of the most distal

dendritic branches.

Similarly, confocal images of labeled neurons were acquired

with 1.9, 3.9 and 7.8 s/scan, and the total dendritic length was

obtained with reconstruction. No significant difference of total

dendritic length was found among the three groups (see

Supplementary Material Fig. S3-C). Post hoc tests showed no

difference in the averaged length of each branch order among

the three groups (see Supplementary Material Fig. S3-D). These

Figure 6. Quantitative analyses of CA1 pyramidal cells of 90-day-old male C57 mice(n = 4). For each animal, 10 cells were reconstructed using Neurolucida and subse-quently quantified using NeuroExplorer. (A) Dendrograms. There was a significant dif-ference in total length of both apical and basal dendrites among these animals (P <0.05). (B) Sholl analysis. In apical dendrites, a peak of dendritic intersections was foundat a distance of 65–215 µm from the soma, whereas in basal dendrites, the peak wasfound at a distance of 50–135 µm from the soma. It was noted that the number of den-dritic intersections varied significantly among the four mice (P < 0.05). Significant dif-ferences were found in both apical and basal dendrites, at the distance of 65–215 and50–135 µm from soma, respectively (P < 0.05; see detail in text).


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data suggested that scanning with a fast speed, 1.9 s/scan,

could obtain estimates of dendritic length as accurately as

scans with slower speeds.

Thus, with imaging parameters optimized to reduce

bleaching, at the expense of increased background fluores-

cence, accurate measurements of dendritic lengths can be

obtained. Most importantly, the optimization process has

reduced the total scan time by as much as ∼ 30% (see Supple-

mentary Material Fig. S4), minimizing dye bleaching and

preserving signal for subsequent photoconversion (see below).

Photoconversion of Diolistically Loaded Neuron

To validate the efficiency and applicability of the current

version of the CCC, the progress of photoconversion of a diOl-

istically labeled neuron was monitored. The presence of DAB

reaction product was found within the cytoplasm 5 min after

commencement of photoconversion (Fig. 7A). It was noted

that the dendritic geometry of a CLSM-imaged neuron resem-

bled that of the photoconverted cell, implying that a sufficient

amount of DiI signal is preserved (Fig. 7B,C). In the present

study, a 10× objective lens was used to illuminate the tissue

because the higher objective lens (25×) was found to easily

dehydrate the tissue using the CCC (not shown). Moreover, the

field of view of a 10× objective lens allowed for photoconver-

sion of multiple neurons concurrently labeled, as shown in

Figure 2B. Conventionally, it requires, on average, 1.5–2 h to

photoconvert the full dendritic tree of a diOlistically labeled

pyramidal cell. However, the current protocol has enhanced

the entire conversion process by reducing the illumination

time by 50% (Table 1).

With optimized imaging parameters that have minimized dye

bleaching, previously CLSM-imaged neurons could be photo-

converted for dendritic spine analysis (see Fig. 8A–G). Based

on the current protocol, the complete 3-D structure of diOlisti-

cally labeled neurons can be quickly acquired using optimized

CLSM parameters (Fig. 8A) in order to perform reconstruction

(Fig. 8B) for quantitative analysis, including dendrogram and

Sholl analysis (Fig. 8C). Meanwhile, the CLSM-imaged neurons,

with minimized bleaching, can be directly photoconverted

using the CCC method (Fig. 8D,E) for spine analysis (Fig.

8F,G). It was noted that the dendritic geometry of a CLSM-

imaged neuron resembled that of the photoconverted cell (Fig.

8A,E). This workflow provides the most accessible and effi-

cient way of obtaining systematic quantitative data for both the

dendritic arbor and spine density of individual neurons.

Discussion

The present study has enhanced the protocol of the current

diOlistic method for large-scale quantitative analyses of

neuronal morphology in fixed brain tissue. Using optimized

imaging parameters and morphological criteria, this study

systematically characterized diOlistically loaded neurons with

the preservation of diffuse signals in dendritic spines, allowing

for subsequent photoconversion to reveal spine morphology.

To our knowledge, this is the first report that has combined the

diOlistic and photoconversion methods for full-scale quantita-

tive characterization of individual neurons.

Diolistic versus Current Loading Methods

Most conventional methods, such as Golgi impregnation and

intracellular loading used to illustrate the dendritic morphology

are not only technically demanding but also are inadequate

to systematically characterize neurons. Furthermore, these

methods lack random sampling, making the resultant quantita-

tive data highly variable. Although the biolistic transfection

method is able to overcome the aforementioned limitations

and produces excellent staining of dendritic trees, the effi-

ciency of transfection heavily depends on the biological state

of the living cells after bombardment. A clear advantage of

Figure 7. High-throughput photoconversion protocol. (A) Validation of the efficiency of CCC. It was noted that the cytoplasm contained DAB reaction products 5 min after com-mencement of photoconversion. (B) Comparison of the distribution of dendritic spines before and after photoconversion. The distribution of dendritic spines of the two imagesappears similar (arrows).

Table 1 Comparison of time required per cell for photoconversion between conventional and CCC methods

aThe number of cells converted is indicated in parenthesis.bThe refreshing of DAB might facilitate oxidation of complex cells, i.e. pyramidal cells of thick sections.

CA1 pyramidal cells Dentate granule cells DAB refreshing

Conventional 2.1 h (n = 15)a 1.5 h (n = 10) >5 times

CCC 1.0 h (n = 15) 0.8 h (n = 10) <1–2 timesb


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Figure 8. Photoconversion of a CLSM-imaged pyramidal cell. (A) A collapsed CLSM image of a diOlistically labeled pyramidal cell with fully labeled dendrites. Asterisks indicatesurrounding DiI clusters, which do not interfere with visualization of the dendritic trees. (B) Neuron reconstructed using Neurolucida. (C) Quantitation, including dendrogram (upperpanel) and Sholl analyses (lower panel). Note that the data of B and D were derived from the pilot study shown in Figure 6. (D) Low magnification view (2.5×) of a photoconvertedtissue slab. Note the high background of the converted area. (E) A photoconverted pyramidal cell. The suboptimal resolution of the cell was due to the optical limitation of imageacquisition in a 250 µm section. It was noted that the dendritic geometry of the converted pyramidal cell appeared similar to that of the collapsed CLSM and reconstructed images(see A and B). The box indicates one of the basal dendrites. (F) High resolution of spine morphology. The shapes of the spines are clearly visualized using a light microscope. (G)Spine analysis. The spine counting (red dots and arrows) is conducted using Neurolucida. Abbreviations: cc, corpus callosum; sp, stratum pyramidale; so, stratum oriens; sr, stratumradiatum.


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using the diOlistic approach on fixed tissue is the liberty of

tissue handling. Not only can the tissue be repeatedly

bombarded, but the diOlistic loading is also independent of the

cell’s gene transcription and protein synthesis.

In most biolistic studies, the source of labeled cells is mainly

from organotypic slice cultures. Due to the above-mentioned

factors that determine transfection efficiency, the yield of

loaded cells for large-scale morphological analyses can only be

increased by using a greater number of animals and/or tissue

samples. Recently, Jin et al. (2001) quantified the polarization

of dendritic trees of green fluorescent protein-transfected

cortical neurons from 143 slice cultures of 48 animals. The

number of successful transfected cells fluctuated at a wide

range, which resulted in a low yield of loading (∼ 3 cells/animal

or ∼ 1 cell/slice). Also, a recent report utilized the gene gun

system to conduct a large-scale morphological survey of mouse

retinal ganglion cells derived from 63 retinal slices (Sun et al.,

2002). The morphology of the subtypes of retinal ganglion

cells has been elegantly presented and quantitated, but the

yield of loaded cells was only, on average, ∼ 8 cells/retinal slice.

While the difference in the cell density of the loaded region

may account for the difference in the yield of loading between

the two studies, the yield of Sun et al. seems sub-optimal given

that the diOlistically bombarded area of the whole-mount

retina is significantly larger than that of many regions of the

brain, such as the CA1 and dentate gyrus of the hippocampus

in the current study. In contrast, the present protocol has

generated a high yield (>20 cells/region per animal) without

exhausting a large pool of animal subjects (n = 6). The present

diOlistic protocol is able to generate a good dispersion of

loaded particles and, more importantly, allows successive diOl-

istic delivery onto both sides of the fixed tissue at different

time points (up to three independent shots) resolving both the

spatial and temporal limitations encountered when performing

intracellular injections.

One aspect that deserves clarification between the present

and previous studies is the definition of optimal loading density

of dye-coated particles. It has been suggested that in order to

obtain a density of 15 labeled cells/mm2 in the hippocampus or

cortex, the delivery of ∼ 100–200 particles/mm2 was required

(Gan et al., 2000; Kettunen et al., 2002). While these studies

did not include a quantitative analysis, it is likely that such an

overly high density of loaded particles would render quantita-

tive analysis difficult due to significant overlapping of dendrites

in adjacent neurons. Instead, the present study attempted to

achieve a balance between a high yield of neurons and minimal

overlap of dendritic processes (compared to Thomas et al.,

1998). An optimal 3-D spatial arrangement maximized the

multiple loading of distinguishable neurons within a given

brain region. This optimized arrangement facilitated full visual-

ization of the individual neurons in order to meet our standard-

ized morphological criteria of sampling. Exclusion of neurons

with dendritic truncations or distal dendrites with incomplete

filling, generated quantitative data with minimal technical arti-

facts. Moreover, the double-labeling method for delineating the

spatial correlation of targeted neurons and their anatomical

sites has provided an efficient means to categorize the cells

concurrently labeled in diverse regions of the brain. Thus, our

diOlistic protocol appears to be the most flexible and efficient

system to obtain multiple labeled cells for quantitative analysis.

One issue remaining in the current diOlistic protocol is that

the bullet quality seems to affect the yield of cell loading. First,

there is no systematic way to precipitate DiI onto the gold

particles during the coating process, making it difficult to

evenly coat DiI onto the surface of the gold particles. As a

result, some neurons are loaded with a gold particle into the

soma but there is little to no dye-transport (also see Fig. 2B).

Secondly, due to the weight of the gold particles, it is difficult

to evenly suspend the DiI-coated gold particles in liquid. This

non-uniform suspension leads to the uneven adhesion of dye-

coated gold particles onto the inner surface of the pre-dried

tubing, producing an irregular distribution of coated particles

onto the landing field of the tissue. Because these factors may

subsequently affect the loading efficiency (also compared to

the DNA-coating procedure by O’Brien and Lummis, 2002), it

is recommended that both the bullet quality and the focus of

the target area relative to the landing field be tested prior to

diOlistic bombardment (also see Wellmann et al., 1999).

Enhanced Throughput for Image Acquisitions

One aspect of optimizing the current diOlistic protocol was to

enhance the throughput of the CLSM imaging process. By

acquiring images of loaded neurons using increased pinhole

apertures with a fast scan speed, the total scan time was

reduced by up to 30% (see above). Underestimated branch

length in the most distal dendrite using 48 µm pinhole aperture

in the present study demonstrated for the first time that scan-

ning with small pinhole aperture has the tendency to bias

dendritic measurements. Underestimated sixth-order branch

length is most likely due to the fact that the lateral resolution is

much more sensitive to pinhole size than the axial resolution

(Wilson, 1995). It is reasoned that small pinhole size improves

x–y resolution at the cost of reducing the signal level. Instead,

increasing the pinhole size enhances sensitivity and improves

the spatial resolution by providing more photons for the micro-

scope to detect in the z-axis, optimizing the collection of

diffuse signals in distal dendrites. Moreover, the absence of a

significant difference in total dendritic lengths between the

three different scan speeds suggested that scanning at a fast

scan speed, although elevating background fluorescence,

would not only obtain accurate dendritic measurements, but

would also reduce the total scan time and, therefore, minimize

loss of signal after CLSM scanning. An important note was that

illumination under 25× objective lens with optimized imaging

parameters has allowed us to acquire the full range of the

dendritic trees with minimal bleaching for photoconversion,

thereby allowing quantitation of spine morphology (see

below). Thus, the use of a high objective lens (100×) was not

practical or desirable in the present study.

High-throughput Photoconversion of CLSM-imaged

Neurons

Photoconversion prevents light-induced bleaching of most

fluorescent markers by transforming the fluorescent compounds

into electron-dense DAB reaction products (Sandell and

Masland, 1988; Lübke, 1993). To establish an efficient work-

flow of the quantitative morphometric protocol, the present

study has adapted the CCC of Kacza et al. (1997) to illuminate

DiI-labeled tissue in an environment of pure oxygen, which has

been suggested to facilitate the photoconversion process

(Sandell and Masland, 1988; Lübke, 1993; also see Kacza et al.,

1997).

With optimized image acquisition parameters, the present

protocol was able to photoconvert DiI signals in neurons that


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were previously imaged using the CLSM. The current protocol

has enhanced the quality of DAB reaction products as well as

reduced the oxidation time by 50% (see Results). While the

percentage loss of DiI signal in dendritic spines after CLSM

imaging requires further investigation, the present finding has

demonstrated a rather comparable resolution of the spine

signals before and after photoconversion (see Fig. 7B). These

data have validated our method for preservation of DiI signals

in dendritic spines after fast CLSM scanning for subsequent

photoconversion. Moreover, the quality of photoconversion

depends, among other factors, on the duration and intensity of

light irradiation, which are determined by the magnification

and numerical aperture of the objective lens that is used. While

most of the studies favor the use of a 20× or higher objective

lens, the present study utilized the wider illuminated field of

the 10× objective lens to simultaneously photoconvert multiple

labeled cells. This is highly advantageous for enhancing the

yield of photoconverted neurons, and thus has added a plus to

the high-throughput process of our combined protocols.

Accordingly, ultra-structural examinations of the dendritic

spines of diOlistically labeled neurons are feasible following

photoconversion.

ConclusionOur combined protocols have proven capable of (i) enhancing

the throughput of randomized cell loading by resolving the

spatial (3-D inter-particle space) and temporal (multiple shoot-

ings of the same tissue at different time points) restrictions that

often occur in conventional labeling techniques, (ii) opti-

mizing the image acquisition process to readily obtain dendro-

grams, and to (iii) subsequently conduct photoconversion of

previously CLSM-imaged neurons, for visualization and quanti-

tative analysis of spine morphology. This approach represents

the most efficient throughput for revealing the systematic

correlation of the dendrites and spines of individual neurons.

Because the morphology of the neurons reflects the physiology

and function of the nervous system, the current protocol is a

powerful tool for revealing subtle changes in the dendrites and

spines of neuropathologic specimens.

Supplementary MaterialSupplementary material can be found at:

http://cercor.oupjournals.org.

NotesThe authors are thankful for the scientific advice of Drs Barry E.

Kosofsky and Jeff M. Redwine, and excellent technical support from

Dr Ron S. Broide, Mr Faisal Chawla and Ms Anna M. Cervantes.

Address correspondence to Floyd E. Bloom, Neurome, Inc., 11149

North Torrey Pines Rd., La Jolla, CA 92037, USA. Email:

[email protected].

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