La censura como practica de control 85

While powerful methods exist to reconstruct and analyze dendritic morphology, quantitative characterization of dendritic developmental dynamics remains challenging as standard descriptions of dendritic architecture are static and do not incorporate an explicit representation of subcellular cytoskeletal compositions. To address this, we have developed novel forms of multi-

channel (e.g. actin/microtubule/cell membrane) digital reconstructions of dendritic morphology to

enable comprehensive statistical analyses of morphological changes and underlying molecular

control of arbor shape. Next generation multi-channel reconstruction of dendritic morphology is

performed using custom plugins on the Vaa3D platform to both qualitatively, as well as quantitatively, assess the data. In Figure 2-12, we show examples of CI and CIV next-generation multichannel reconstructions. While the traditional membrane marker for a neuron can be used to outline the overall architecture of that cell, there remains a knowledge gap of the precise cytoskeletal organization of distinct neuronal subtypes. Implementation of multi-channel reconstructions allows for a more detailed examination of the mechanism via which local molecular cues modulate the cytoskeleton to direct dendritic architecture. Utilizing this approach, we can quantitatively assess the distribution of cytoskeletal elements across the arbor. In wild- type da neurons, MTs are largely restricted to the major dendritic branches and are absent from the terminal branches, whereas F-actin is distributed throughout the arbor and terminal branches are exclusively comprised of F-actin (Fig. 2-12). Moreover, the F-actin signature displays an uneven distribution along an arbor, as seen by presence of F-actin rich islands along the arbor, and presence of higher F-actin signal at branch point, while the MT signal appears more uniform across the arbor with the signal intensity related to the tapering of the dendritic branch diameters as a function of the distance from the cell body (Fig. 2-12). We can utilize this technique to delineate

the F-actin and MT intensity maps in a mutant condition and compare to controls to discern the primary defects a gene may have on cytoskeletal organization. For example, comparisons of CIV knockdown of dmn to controls reveal that while the overall architecture is reduced in dmn RNAi, the predominant cytoskeletal defect lies in a severe reduction of the MT signature as compared to F-actin (Fig. 2-13).

The distribution and intensity levels of these cytoskeletal components along the dendritic arbor can be analyzed at the quantitative level via multichannel reconstructions. As an example, Fig. 2-14 compares the cytoskeletal organization of control vs. knockdown of the Kn effector molecule RpL36A. Comparisons of the MT and F-actin intensities as a function of the distance from the soma, reveal that with RpL36A disruption there is dramatic decrease in MT signal (Fig. 2-14O), whereas the F-actin signal is also reduced, but to a lesser extent (Fig. 2-14P), supporting a more critical role in modulating MT architecture. These analyses can likewise be extended to cytoskeletal distribution as a function of branch order (Fig. 2-14Q,R). Here, branch order is determined using a classical branch order calculation method, which is different from that used in reversed Strahler analyses, thereby accounting for the discrepancy in the number of branch orders compared to the previous graphs. These analyses demonstrate that while the first few branch orders of RpL36A CIV dendrites had only a modest reduction in the MT and F-actin, there is a severe reduction in MT and F-actin at higher order branches (Fig. 2-14Q,R). This novel method to illustrate alterations in cytoskeletal components occurring along the dendritic arbor will greatly facilitate the elucidation of local cytoskeletal events occurring at specific sites of interest on the arbor, such as branch points, primary branches, terminal branches.

Figure 2-12 Next generation multichannel reconstruction of da neurons.

a GFP-tagged membrane of Class IV da neuron, b RFP-tagged F-actin of Class IV da neuron c GFP-tagged membrane of Class I da neuron d RFP-tagged microtubule of Class I da neuron, e, f Two-channel next generation reconstruction of Class IV and Class I da neurons. The overall membrane structure is represented in transparent black, allowing the visualization of the internal cytoskeletal component (F-actin in Class IV, microtubule in Class I). The radius of the internal arbor represents the ratio of the area occupied by the cytoskeletal protein relative to the external structure. Color of the arbor represents quantity of the protein (red is high-quantity, blue is low- quantity), g, h Zoomed-in view of soma region (yellow dashed box) and a terminal (orange dashed box) of the Class IV reconstruction, i, j Zoomed-in view of soma region (yellow dashed box) and a terminal (orange dashed box) of the Class I reconstruction, k Multichannel plugin toolbox built in the Vaa3D system. (adapted from Nanda et al. 2016 (in press)).

Figure 2-13 Semi-automated reconstructions of multi-channel data reveal subcellular defects in cytoskeletal organization that manifest in disrupted dendritic morphology.

Reconstruction Software: A combination of TreesToolbox, and Vaa3d. Reconstructions from 3D confocal image stacks. The cytoskeletal intensity profile images are rendered using the Vaa3d rendering plugin. Shown here is a comparison between wild-type controls of class IV da neurons vs. RNAi knockdown of

dynamitin (dmn), a Dynein/Dynactin motor component. Conducted in collaboration with S. Nanda, G.A. Ascoli (George Mason University); H. Peng (Allen Brain Institute).

Figure 2-14 Multichannel reconstructions enable detailed analyses of both global and local changes in dendritic cytoskeletal organization.

(A-D) image stacks of the individual channels of WT and RNAi knockdown of

RpL36A. (E-H) skeletons of the reconstructions generated by a combination of TreesToolbox, Vaa3d and Neutube. (I-L) intensity maps of F-actin and MT generated by Vaa3d custom plugin. (M, N) show the relative subcellular distribution of F-actin and MT. (O-R) quantitative analyses of MT and F-actin distribution as a function of path distance from the soma and branch order. Conducted in collaboration with S. Nanda, G.A. Ascoli (George Mason University); H. Peng (Allen Brain Institute); H. Chen (University of Georgia).