In order for the nervous system to function properly, neurons in the brain must establish specific connections during embryonic development. Formation of neuronal circuits involves axons extending from cell bodies and navigating through diverse tissues to reach their targets in the brain. Once axons reach their target tissues, they arborize and make synaptic connections. Axon pathfinding is driven by dynamic motility behaviors expressed by terminal growth cones at the tips of the axons. Here, we applied morphometrics to determine quantitative values for six morphological and motility parameters for growth cones of optic axons navigating through the optic tract of a living brain preparation from a Xenopus laevis tadpole. Our results demonstrate an increase in length, decrease in width, increase in perimeter, decrease in area, increase in number of filopodia, and a decrease in number of lamellipodia, of the growth cones in the optic tract. Therefore, optic axonal growth cones become less circular and more elongated and protrusive during their navigation through the optic tract. Quantitatively deconstructing parameters of growth cone motility is necessary to determine molecular, cellular, and biophysical mechanisms of axon pathfinding, and to formulate computational analyses of developing neuronal connectivity in the brain.
- growth cone
- optic axons
- optic tract
- Xenopus laevis
In order for the nervous system to function properly, accurate wiring of the brain must be established during embryonic development. Wiring of the brain depends in large part on axons extending from neuronal cell bodies and subsequently navigating through tissues to reach appropriate targets in the brain. Axon pathfinding is driven by specific and patterned motility behaviors expressed by growth cones at the terminal ends of the axons. Quantitatively deconstructing distinct motility parameters of growth cones will aid studies exploring the molecular and mechanical control of axonal pathfinding, as well as facilitate the development of computational analyses of growth cone motility. Here, we have applied morphometric analyses to determine values, and spatiotemporal patterns in those values, for six parameters of motility from a time‐lapse video of two growth cones of optic axons navigating through the optic tract of a living brain preparation from a young
During embryonic development of the visual system, optic neurons extend axons from the eye to the tectal midbrain, where they make synaptic connections essential for visual function. The ability of these optic axons to navigate and propel through the optic tract, and to eventually reach the tectum, is due to the growth cone of the axon. The growth cone is a highly motile structure located at the distal end of the axon that mediates its directional growth and extension by interacting with molecular and mechanical cues in the environment. The growth cone can be divided into three sub‐compartments, the peripheral (P), transitional (T), and central (C) domains (Figure 1). The P‐region of the growth cone contains a meshwork of actin filaments and long parallel bundles of actin filaments that underlie two types of protrusions (Figure 1). Lamellipodia are short and broad protrusions that are thought to function to generate force for the growth cone advance (Figure 1). Filopodia are long and finger‐like, and primarily sense the environment and guide the axon (Figure 1; ). A combination of actin treadmilling and retrograde actin flow allows for continual remodeling of the P‐region (and of the lamellipodia and filopodia within this region), required to generate growth cone motility. ATP‐actin is assembled into filaments in the distal P‐region and then transported rearward to the T‐region as polymeric F‐actin. In the T‐region, F‐actin is polymerized and recycled back to ATP‐actin and the cycle restarts. Actin is transported retrograde from the P region to the T‐region via a myosin motor driven process . The C‐region, which is proximal to the P‐region, is filled with a dense microtubule array and cellular organelles like mitochondria that support growth cone movement (Figure 1; ). The microtubule system within the C‐region affects cell motility by steering growth cone advance in response to guidance cues from the P‐region . The plus end of microtubules exhibits dynamic instability, cycling through periods of growth and shrinkage, allowing them to probe the intracellular space . Similar to actin, microtubules are involved in a transport mechanism involved in maintaining the axon and the growth cone. The majority of microtubules are found in the axon shaft and are stationary. However, in active regions like the growth cone, stable microtubules are tyrosinated to become dynamic .
As the growth cone progresses, the P‐region senses changes in the extracellular environment, and relays those cues to the C‐region. These cues can be either attractive or repulsive . Although the majority of microtubules end in the C‐region, single microtubules protrude into the filopodia of the P‐region, mediating interaction between the actin and microtubule cytoskeleton (Figure 1; ). Interactions between microtubules and actin in filopodia are necessary for growth cones to turn. Microtubule and actin interactions also occur in the T zone and C domain of the growth cone, where actin arcs in the T zone exert compressive forces on microtubules in the C domain, facilitating microtubule bundling and aiding in axon navigation (Figure 1; ). Previous and current studies from our laboratory show that molecules downstream of Cadherin and Wnt signaling ligands such as β‐catenin and APC, that regulate the actin and microtubule cytoskeleton, modulate optic axon growth cone morphology and motility in the optic tract as well as targeting and branching in the optic tectum [6, 7]. More generally, it is now clear that the actin and microtubule cytoskeleton of the two growth cone regions are dynamically related, and may influence each other via signaling molecules such as APC . The functional studies of APC
In order to gain a better understanding of the motility, and morphological dynamics of the growth cone, we quantitatively analyzed an
The length of each growth cone was determined by drawing a line extending along the axonal axis, from the base to the leading edge of the growth cone (thick vertical lines, Figure 3A). The base of the growth cone was defined as the first protrusion of the growth cone near the axon shaft (thick lines, Figure 3A; ). The leading edge of the growth cone was established as the tip of the growth cone, including all protrusions. Width of the growth cone was measured by creating two parallel lines to the length line, at the tips of the distal edges of the growth cone (including its protrusions) (thin vertical lines, Figure 3A). The perpendicular distance between these two parallel lines was measured as the maximal width of the growth cone (thick horizontal lines, Figure 3A; ). This was done for both growth cones for each frame of the time‐lapse sequence.
To measure the perimeter of the growth cones, the growth cone boundaries were traced using the polygon drawing tool in ImageJ (yellow outlines, Figure 3B). The base of the growth cone was used as the starting point, and the distal edges of the growth cone were traced until reaching the starting point. Similar to the measurement of growth cone length, the base of the growth cone was determined to be where the first protrusion of the growth cone near the axon shaft was located and the growth cone boundary contained all protrusions of the growth cone (Figure 3B). Filled area was calculated using the measurement tool in ImageJ.
The number of filopodia and lamellipodia in each image was measured using ImageJ as well (thin lines- filopodia, thick lines - lamellipodia, in Figure 3C). Criteria for identifying filopodia and lamellipodia were based on a previous review studying cellular protrusions
To avoid researcher‐dependent bias in morphometric measurements, five different researchers performed the measurements for length, width, perimeter, and area on the two growth cones at each time point, using the protocols described above. Their values were averaged to obtain final measurements for these size parameters for the growth cones at each time point. All measurements (length, width, area, perimeter, and number of filopodia and lamellipodia) were initially plotted against time in a scatter plot. However, to better display the changes in the data, and to depict the changes in the growth cones as they progressed from ventral, to mid, to finally, the dorsal optic tract, we subdivided the time‐lapse video into three time bins. The time‐lapse video was composed of 119 frames at 3‐min intervals, spanning a total time of 357 min. Therefore, first time bin encompassed 3–117 min (39 images), the second 120–237 min (39 images), and the third 240–357 min (39 images). Averages were calculated for the morphometric measurements for each of the three time groups for both growth cones, and then averages of those averages were determined over the two growth cones. These average growth cone parameters were plotted on bar graphs to determine if there were any differences between their values during the three time bins (Figures 4–6).
3.1. Quantitative analysis shows morphological changes in growth cones
3.1.1. Growth cone length increases, while width decreases over time
The lengths and widths of the growth cones were measured using specific criteria described in Section 2. Measurements were taken for both growth cones in each of the 119 frames of the time‐lapse video. The time‐lapse video was broken up into three equal time bins, and the average length and width for the growth cones were calculated for each of the time bins and plotted on bar graphs (Figure 4). Trend lines were added to the graphs. The results revealed that as the growth cones progressed through the optic tract, on average, their length increased, and their width decreased (Figure 4). However, the length of the growth cones increased a smaller amount than their width decreased during their navigation through the optic tract (Figure 4).
The mean length for growth cone one was initially 45.9 μm (
The mean width for growth cone one was initially 16.1 μm (
3.1.2. Growth cone perimeter increases, while area decreases over time
The perimeter and area of the growth cones were measured using the techniques described in Section 2. Measurements were taken for both growth cones in each of the 119 frames. Again, the time‐lapse video was decomposed into three equal time bins and average growth cone perimeter and area were calculated for each of the time bins and plotted as bar graphs with trend lines (Figure 4). The results revealed that, on average, the growth cone perimeter increased, and the area decreased as the optic axons progressed through the optic tract (Figure 5). In addition, the growth cone perimeter increased more than the growth cone area decreased as the optic axons navigated through the optic tract in a living brain preparation (Figure 5).
The mean perimeter of growth cone one for time bin one was approximately 112 μm (
The mean area of growth cone one for time bin one was 392 μm2 (
3.1.3. Filopodial protrusions increase, and lamellipodial protrusions decrease over time
To further decompose growth cone motility in the optic tract, the number of filopodial and lamellipodial protrusions in the growth cones was measured using criteria described in Section 2. The number of protrusions was calculated for both growth cones in each of the 119 frames of the time‐lapse sequence. The average number of filopodia and lamellipodia for the growth cones for each of the time bins were calculated and plotted as bar graphs with trend lines (Figure 6). The results revealed that the mean number of filopodial protrusions increased, and the mean number of lamellipodial protrusions decreased, as the growth cones navigated through the optic tract toward the optic tectum (Figure 6). However, the mean number of filopodia per growth cone increased much more than the mean number of lamellipodia decreased during the time the optic axons extended through the optic tract (Figure 6).
The mean number of filopodia in growth cone one during time bin one (117 min) or the ventral optic tract was 4.4 (
The mean number of lamellipodia of growth cone one for time bin one was 2.4 (
4.1. Changes in optic axonal growth cone morphologies in the optic tract
This quantitative analysis of growth cone motility of the
4.2. Previous quantitative analysis of growth cones of optic axons
Previous study quantified morphologies of growth cone of optic axons in the optic tract of brains from
4.3. Limitations and future directions for measurements of growth cones
In this quantitative analysis of growth cone morphology, researchers measured dimensions and protrusions of growth cones of optic axons manually outlining and delimiting boundaries of growth cones themselves (based on set criteria). One concern with having human researchers perform morphometric analyses is the potential variability in their delimitation of growth cone boundaries, and accordingly, the lack of reproducibility in their measurements. To circumvent this issue, we had five different researchers who make the same morphometric measurements on the two growth cones in each frame of the time‐lapse sequence. We then averaged the values obtained by the different researchers to calculate our final values for size measurements of growth cone morphologies. Another approach to ensure reproducibility in quantitative analysis of growth cone morphology would be to have an automated computer program performing the measurements. However, before applying an automated approach, several issues would need to be resolved. First, the growth cones would need to be resolved with computer vision in a three‐dimensional brain (Figure 3). Most automated algorithms work well on growth cones imaged
In addition, in this study, we measured morphometric parameters for a relatively small number of growth cone of optic axons based on a time‐lapse video captured of two fluorescently‐labeled growth cones navigating in the optic tract of a single living brain preparation. Therefore, it is possible that our measurements are not representative of growth cones of optic axons in living brains generally. Instead, our growth cone measurements may be biased by the experimental conditions of this brain preparation. For example, the pressure exerted by the cover slip on the living brain preparation can alter the morphology of the growth cones as they navigate through the optic tract. To expand and generalize these morphometric measurements, we would need to make measurements on additional GFP expressing growth cones in different living brain preparations. An appropriate sample number would be 10–15 growth cones in five different living brain preparations. This would allow us to determine whether our morphometric measurements are generally representative of growth cones of optic axons from
Limitations notwithstanding, the detailed measurements that we made of growth cone parameters advance our understanding of the dynamics of optic axon pathfinding in the optic tract of
We thank Sonia Witte for making the time‐lapse video of GFP‐labeled optic axons in a living brain preparation from a
Funding for this project was provided by the Masters in Medical Health Sciences program in the College of Osteopathic Medicine at Touro University California. Publication made possible in part by support from the Berkeley Research Impact Initative (BRII) sponsored by the UC Berkeley Library.
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