FOXO REGULATES MICROTUBULE

DYNAMICS AND POLARITY TO PROMOTE

DENDRITE BRANCHING IN DROSOPHILA

SENSORY NEURONS

by JAMES COOPER SEARS

Submitted in partial fulfillment of the requirements

for the degree of Doctor of Philosophy

Dissertation Advisor: Dr. Heather Broihier

Department of Neurosciences

CASE WESTERN RESERVE UNIVERSITY

January, 2017 CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

we hereby approve the thesis/dissertation of

James Cooper Sears

candidate for the degree of Doctor of Philosophy*.

Committee Chair

Dr. David Katz

Committee Member

Dr. Heather Broihier

Committee Member

Dr. Jerry Silver

Committee Member

Dr. Helen Salz

Date of Defense

September 30th, 2016

*We also certify that written approval has been obtained

for any proprietary material contained therein. Dedication

To my family, thank you for your immeasurable love and support.

i Contents

List of Figures ...... v

Acknowledgements ...... vi

Abstract ...... viii

1 General Introduction 1

1.1 Summary ...... 1

1.2 The Drosophila Dendritic Arborization System ...... 2

1.3 Neurons are Highly Polarized Cells ...... 5

1.4 Microtubules are Polar Molecules ...... 7

1.5 Neurons and Microtubule Polarity are Inextricably Linked ...... 8

1.5.1 Microtubule Polarity in Neurons ...... 8

1.5.2 Microtubules are Crucial for Neurons at all Stages ...... 13

1.5.3 Neurological Disorders Linked to Microtubules ...... 14

1.6 Dendrite Morphology and Microtubules ...... 16

1.6.1 Dendrite Morphology and Functionality ...... 16

1.6.2 Molecular Motors and +TIPs ...... 18

1.6.3 Transcription Factors ...... 19

1.7 FoxO is a Transcription Factor With Complex Regulation and

Functions ...... 21

1.8 FoxO and Neurodevelopment ...... 26

ii 1.9 Focus of Thesis ...... 27

2 FoxO regulates microtubule dynamics and polarity to promote

dendrite branching in Drosophila sensory neurons 31

2.1 Abstract ...... 33

2.2 Introduction ...... 33

2.3 Results ...... 37

2.3.1 FoxO acts cell-autonomously to regulate class IV dendrite

morphology ...... 37

2.3.2 FoxO is expressed in da neurons and regulates class I-III

dendrite morphology ...... 39

2.3.3 FoxO promotes initiation and stabilization of new branches . 40

2.3.4 FoxO is sufficient to promote branch formation ...... 41

2.3.5 FoxO limits the distribution of stable microtubules in dendrites 43

2.3.6 FoxO is necessary for both anterograde polymerization and

dynamics of microtubules ...... 45

2.3.7 FoxO drives anterograde microtubule polymerization . . . . . 47

2.3.8 FoxO is necessary for proper nociceptive response ...... 49

2.4 Discussion ...... 50

2.5 Materials and methods ...... 55

2.6 Figures ...... 61

3 General Discussion 85

3.1 FoxO as a Microtubule Regulator ...... 85

3.2 FoxO and Neuronal Polarity ...... 91

3.3 FoxO and a Potential Link Between Microtubules and Actin . . . . . 93

iii 3.4 Upstream Regulation of FoxO ...... 95

3.5 FoxO and Neuronal Plasticity ...... 96

3.6 Closing Comments ...... 97

4 Appendix A: Visualizing the Dendritic Arborization System 100

5 Appendix B: Discussion Figures 103

5.1 Materials and Methods ...... 103

5.2 Figures ...... 104

Bibliography 112

iv List of Figures

1.1 Classes of the Dendritic Arborization System ...... 29

2.1 FoxO regulates class IV dendrite morphology ...... 61

2.2 FoxO acts cell-autonomously to regulate class IV dendrite morphology 63

2.3 FoxO is expressed in da neurons and regulates class I-III dendrite

morphology ...... 65

2.4 FoxO promotes initiation and stabilization of new branches . . . . . 67

2.5 FoxO is sufficient to promote branch formation ...... 69

2.6 FoxO limits the distribution of stable microtubules in dendrites . . . . 71

2.7 FoxO is necessary for anterograde polymerization and dynamics of

microtubules ...... 73

2.8 FoxO drives anterograde microtubule polymerization...... 75

2.9 FoxO is necessary for proper nociceptive response ...... 77

2.S1 FoxO acts cell-autonomously to regulate class IV dendrite morphology 79

2.S2 FoxO is sufficient to promote branch formation in class II neurons . . 81

2.S3 Genetic interaction between FoxO and Futsch in class IV ...... 83

5.1 Pavarotti regulates class IV dendrite morphology ...... 104

5.2 Knockdown of Rac1 suppresses increased branching in class I cells

overexpressing FoxO ...... 106

5.3 Constitutively-active Pak1 increases branching in class I ...... 108

5.4 A model for FoxO regulation of microtubules and dendrite morphology110

v Acknowledgements

The work presented here would not have been possible without the support of many people. I would like to first thank my advisor, Dr. Heather Broihier, for her mentorship, enthusiasm, and encouragement. Her focus on clear scientific communication has been integral to my growth as a scientist. I am also grateful for the freedom that she has allowed me to have in planning, designing, and analyzing experiments. Her guidance has been invaluable, and I am truly grateful.

I would also like to thank the members of my thesis committee, Dr. David

Katz, Dr. Jerry Silver, and Dr. Helen Salz. I am very appreciative of their excitement, feedback, and critical observations. Moreover, I appreciate their perspective and ability to help me see the larger picture of my research.

Thanks also go to past and present lab members. Boluwatito Abraham,

Reagan Brady, Chris Dejelo, Dallas Eckman, Kelsey Herrmann, Zach Hofstetter,

Kendall Hoover, Rebecca James, Tiffany Kearse, Nan Liu, Crystal Miller, Colleen

McLaughlin, Inna Nechipurenko, Jahci Perry-Richardson, Priya Tumuluru, and

Yi-Lan Weng: thank you for making the Broihier lab an energetic and intellectually stimulating place.

Special thanks also go to the Department of Neurosciences and other members of Case Western Reserve University. It is difficult to imagine a place more supportive of graduate student training. I would like to thank the members of the Neurosciences Administrative Office as well. Narlene Brown, Pam

Capasso, Katie Wervey: thank you for keeping me and the department on track. I would also like to thank Dr. Patty Conrad, Dr. Jocelyn McDonald, Maryanne

Pendergast, and Dr. Dan Wesson for their advice and guidance. Furthermore, I

vi am grateful for the opportunity to present my work to the Model Organism Group at Case Western. Also, I would like to thank the other students at Case Western for their kindness and inspiration; I am always impressed by your dedication and accomplishments.

Lastly, I would like to thank my friends and family. I could not have done this without your support. Most importantly, I would like to thank my wife, Carolina.

Her talents and support know no bounds, and I am a much better person because of her.

vii FoxO Regulates Microtubule Dynamics and Polarity to Promote Dendrite

Branching in Drosophila Sensory Neurons

Abstract

by

JAMES COOPER SEARS

The morphology of dendrites is a critical determinant of neuronal function.

Microtubules are crucial structural and functional components in dendrites, yet the molecular mechanisms and pathways that regulate dendrite development are unclear. Previous work from our lab showed that FoxO regulates microtubule dynamics in axons at the neuromuscular junction. Therefore, we tested if FoxO regulates microtubules and morphology in the dendritic arborization (da) system.

We found that FoxO is required for normal morphology in all four classes of da neurons. FoxO is necessary not only for branching, but also for initiation and maintenance of terminal branches. Furthermore, overexpression of FoxO is sufficient to promote increased branching in multiple cell types. Consistent with

findings in motor axons, FoxO limits the distribution of stable microtubules. When we tested for microtubule dynamics, we found that FoxO is necessary and sufficient to promote anterograde microtubule polymerization. Similar to other studies in the system, loss of branching seen in foxO nulls correlates with a decreased nociceptive response. Taken together, our results identify FoxO as a regulator of dendritic arborization and neuronal function. Furthermore, our data support the hypothesis that FoxO promotes dendrite branching by promoting

viii anterograde microtubule polymerization. This conclusion leads to testable hypotheses for how FoxO regulates microtubules and morphology of dendrites.

ix Chapter 1

General Introduction

1.1 Summary

A neuron’s morphology is essential for its functional connectivity with other cells and its receptivity to the surrounding environment. These morphologies are built upon a foundation of structural and functional subcellular components known as microtubules. Therefore, an important subject in neuroscience concerns how the regulation of microtubules determines neuronal morphology and function.

Microtubules are polarized macromolecules composed of a- and b-tubulin dimers. These dimers are assembled into rings of filaments. One end of the molecule, known as the plus-end, is notably more dynamic than the other, minus-end. Several proteins act specifically at either the plus-end or the minus-end to regulate microtubule polymerization and stability, and molecular motors use microtubules as tracks to move either toward the plus-end or toward the minus-end.

Neurons are highly polarized cells that, with few exceptions, contain axons and dendrites. Typically, these two compartments develop either from the cell body or a primary neurite. Intracellularly, the polarity of microtubules in axons is different from dendrites. In the axon, microtubule polarity is predominantly

1 plus-end-out, or away from the cell body. In the dendrite, microtubules are either predominantly plus-end-in, or a mixture of plus-end-in and plus-end-out. With few exceptions, this mixture is specific to dendrites, and begs the question of how microtubule polarity is controlled.

Due to the conservation of molecular function between invertebrates and vertebrates, Drosophila is a crucial model for the study of neurodevelopment and disease. Importantly, a recent study from our lab showed that the sole FoxO ortholog in Drosophila acts in motoneurons to regulate microtubule dynamics during development. Therefore, we investigated whether FoxO also directs dendrite development through microtubule regulation. To do so, we focused on the dendritic arborization (da) neurons, a group of sensory neurons located within the body wall of Drosophila larvae. Work in this system has demonstrated its power to explore the biology of dendrite development.

1.2 The Drosophila Dendritic Arborization System

Neurons in the da system elaborate processes into the body wall of Drosophila that are classified as dendrites (Rolls, 2011). For example, da dendrites have mixed or predominantly plus-end-in microtubule polarity (Hill et al., 2012; Rolls et al., 2007). They also have distinct morphology and intracellular components compared with axons (Rolls et al., 2007; Zheng et al., 2008). Lastly, though these dendrites are not post-synaptic, they are the inputs of the neuron. For example, pickpocket (ppk), a Degenerin/Epithelial Sodium Channel family member that is necessary for mechanical nociception, is located in the dendrites, but not the axon, of class IV neurons (Zheng et al., 2008; Zhong et al., 2010).

With the aid of genetic tools and transgenic fluorophores, investigators have

2 visualized and classified neurons in the da system (Grueber et al., 2002)(see

Appendix A for more details on genetic tools used to mark da neurons). The da system includes four classes (I-IV) of sensory neurons with increasing dendrite size and complexity (Fig. 1.1, Grueber et al., 2002). Cells in each class have predictable tiling patterns (Grueber et al., 2002). For example, class IV cells do not overlap with each other, but a class IV cell can overlap with class I, II, or III cells (Grueber et al., 2002). Importantly, cells in each class have stereotyped locations and morphologies that repeat in each abdominal hemisegment, making each da cell type identifiable (Grueber et al., 2002). Moreover, each class contains cells with their own characteristic, relatively consistent morphology and subcellular features. For example, class I cells are the smallest and least branched of the da neurons, and they have stable microtubules throughout their dendritic arbors (Grueber et al., 2002; Jinushi-Nakao et al., 2007). In contrast, class IV cells are the largest and most branched of the da neurons, and they display stable microtubules almost exclusively in the main branches of their dendritic arbors (Grueber et al., 2002).

Class IV da neurons are particularly notable for their size and growth during development (Grueber et al., 2002; Parrish et al., 2009). At 25 C, Drosophila eggs develop for approximately 24 hours (h) before larvae emerge. Larvae grow to approximately one hundred times their initial size as they develop through three instar stages. Larvae forage and grow as 1st and 2nd instars until around 72 h after egg laying (AEL), when they become 3rd instar larvae. At around 120 h AEL,

"wandering" 3rd instar larvae leave their food to find a suitable location to pupariate. Class IV cells cover the body wall of larvae (Grueber et al., 2002).

These cells must grow to match the size of the animal, since class IV cells are not

3 added in larvae (Parrish et al., 2009). Class IV cells will initially elaborate main dendrite branches, then rapidly grow smaller, higher order branches, until they have filled their coverage areas by around 40-48 h AEL (Parrish et al., 2009).

After these events, class IV cells continue to grow and scale with the size of the animal, and their dendrites remain highly dynamic during much of the 3rd instar stage (Parrish et al., 2009; Ori-McKenney et al., 2012; Ye et al., 2007). This overall growth causes class IV cells to be the largest and most elaborate of the da neurons, making them the standard for studying dendrite arborization in this system.

In addition, Class IV cells can be used to test for neuronal function. Class IV cells are nociceptive and respond to stimuli such as hard touch and noxious heat

(Zhong et al., 2010). Through use of calibrated Von Frey filaments and heat probes, functional capacity of class IV cells can be assessed (Hwang et al., 2007;

Tracey et al., 2003; Zhong et al., 2010). Importantly, complexity of class IV cells correlates with nociceptive response, demonstrating that proper neuronal function is tied to acquisition of highly branched morphology (Ferreira et al., 2014; Stewart et al., 2012).

Classes I, II, and III also have distinct morphologies, intracellular characteristics, and functions. Class I cells are the smallest and least branched of the da neurons and are thought to be proprioceptive (Grueber et al., 2002). As mentioned above, much of their dendritic arbors stain positive for stable microtubules (Jinushi-Nakao et al., 2007). Class II cells are relatively larger and more branched than class I cells and are the least studied (Grueber et al., 2002).

Class III cells are the second most branched of the da neurons and are responsible for light touch sensation (Grueber et al., 2002; Yan et al., 2013).

4 Class III cells have long, stable microtubule-rich main branches and numerous short, "spiky" terminal branches that do not stain for stable microtubules (Grueber et al., 2002). Taken together, the use of all four da neuron classes allows for not only careful study of dendrite development and function, but also identification of important factors effecting global and cell type specific morphologies.

1.3 Neurons are Highly Polarized Cells

Two different compartments highlight the polarized nature of the neuron (Rolls et al., 2007). In a typical neuron, dendrites receive information and the axon transmits information. Each compartment is also morphologically distinct.

Dendrites are typically shorter and their coverage is carefully tuned to meet the demands of their receptive field (Lefebvre et al., 2015). Axons are typically longer and more uniform in diameter and their structure is often more suited to delivering information to discrete targets.

In addition to morphological differences, axons and dendrites are distinct in their composition (Rolls et al., 2007). Membrane proteins necessary for excitability and targeting, such as ion channels, synaptic machinery, receptors, and adhesion molecules, are localized to their appropriate compartment. This organization allows for axons and dendrites to develop and function in response to different external cues. This distribution is defined broadly in two ways: microtubule polarity and selective filtering by the axon initial segment (AIS).

Microtubule polarity determines the directionality of molecular motors, which use microtubules as tracks to move and transport cargo in one of two directions

(Kapitein and Hoogenraad, 2011). These molecular motors include kinesins and dynein. Most kinesins move towards the plus-end, while dynein moves towards

5 the minus-end. Dendrites and axons have different patterns of microtubule orientation. The plus-end of microtubules can be oriented either away from the cell body (plus-end-out) or toward the cell body (plus-end-in). In axons, microtubules are predominantly plus-end-out, while in dendrites, microtubules can be either predominantly plus-end-in or a mixture of plus-end-in and plus-end-out. This is thought to allow for molecular motors to transport molecules to their correct compartment (Rolls, 2011). For example, kinesin molecules transport presynaptic vesicles into axons, while dynein is necessary for localization of dendrite specific cargo such as Golgi outposts and Pickpocket

(Barkus et al., 2008; Pack-Chung et al., 2007; Zheng et al., 2008). The AIS is located in the proximal axon, and work suggests that it acts as a selective filter for cytoplasmic transport into and out of the axon (Song et al., 2009). While the exact mechanism is still under investigation, it is predicted that multiple cytoskeletal processes both within and proximal to the AIS sort axon specific targets and assist in their delivery (van Beuningen and Hoogenraad, 2016). For example,

Ankyrin G links the AIS to microtubules through plus-end binding proteins, suggesting that it could indirectly regulate intracellular transport (Leterrier et al.,

2011; Leterrier et al., 2015).

Morphological and intracellular polarity changes can be observed during development and regrowth. Multiple short, dynamic processes are observed during the initiation of axo-dendritic polarity (Cheng and Poo, 2012). While these processes initially appear symmetrical, one process will stabilize and become the axon. After axon extension, dendritic processes develop and elaborate in accordance with intrinsic and extrinsic cues (Puram and Bonni, 2013).

Interestingly, severing the axon has been shown to mobilize a replacement from a

6 dendritic process (Stone et al., 2010). After axotomy, a dendrite process becomes highly dynamic, switches internal microtubule polarity to that of an axon, and extends (Stone et al., 2010). Severing a dendrite does not result in a similar change in dynamics or growth, indicating a context-dependent switch of microtubule polarity. These findings and others demonstrate the intrinsic differences between axons and dendrites, which, as discussed in later sections, are related to microtubule polarity.

1.4 Microtubules are Polar Molecules

Microtubules are a crucial component of the cytoskeleton that play important structural, functional, and kinetic roles in cell biology (Conde and Cáceres, 2009).

They are polarized macromolecules composed of a- and b-tubulin heterodimers assembled end-to-end. In mammals, at least 9 a-tubulin isotypes and 9 b-tubulin isotypes have been discovered (Chakraborti et al., 2016). Heterodimers are assembled into protofilaments that are joined together to form a tube approximately 25 nm in diameter. This organization imparts an intrinsic directionality. One end is defined as the plus-end, while the other end is defined as the minus-end. These ends can be used to describe the relative dynamics of the macromolecule. The plus-end, where b-tubulin is exposed, is notably more dynamic. It is here that rapid microtubule polymerization and disassembly typically occur. The minus-end, where a-tubulin is exposed, is more often the site of initial nucleation with the aid of g-tubulin.

The polarity of microtubules allows for regulation at different locations on the molecule. Plus-end tracking proteins (+TIPs) such as the CLIP family and the

End-binding (EB) proteins specifically bind the plus-end of microtubules,

7 influencing microtubule dynamics and directing microtubule polymerization

(Akhmanova and Steinmetz, 2008; Mattie et al., 2010). The

CAMSAP/Nezha/Patronin family member CAMSAP2, in comparison, has recently been shown to stabilize the minus-end of non-centrosomal microtubules and to be necessary for neuronal polarization (Yau et al., 2014). Therefore, it is proposed that CAMSAP2 may promote non-centrosomal microtubule polymerization (Yau et al., 2014).

As mentioned above, dynein and kinesins use microtubules as tracks to transport cargo either toward the minus-end or toward the plus-end (Kapitein and

Hoogenraad, 2015). This is particularly important in neurons for transporting molecules to their correct compartment (Kapitein and Hoogenraad, 2011; Rolls,

2011). Moreover, recent evidence shows that molecular motors also guide microtubule polymerization and determine neuronal morphology (Lu et al., 2013;

Mattie et al., 2010; Roossien et al., 2014). For example, kinesin-2 localizes to the plus-end of microtubules and maintains its plus-end-in or plus-end-out orientation. Furthermore, work shows that Kinesin-1 use multiple microtubule molecules in a process called microtubule sliding to generate the force needed to generate new neuronal processes (Lu et al., 2013).

1.5 Neurons and Microtubule Polarity are Inextricably Linked

1.5.1 Microtubule Polarity in Neurons

The earliest research describing trends in intracellular microtubule polarity was conducted in the early 1980s (Baas and Lin, 2011). By carefully promoting short-term microtubule assembly with a specialized buffer solution containing

8 pre-polymerized microtubule protein, investigators discovered that they could visualize patterns of "hooked" microtubule appendages (Heidemann and

McIntosh, 1980). These appendages, when viewed as cross-sections with electron microscopy, have patterns that correspond to the polarity of the anchoring microtubule filament (Heidemann and McIntosh, 1980). Clockwise hooks correspond to the plus-end of the microtubule facing the viewer, while counterclockwise hooks correspond to the minus-end of the microtubule facing the viewer (Baas and Lin, 2011). Therefore, great care had to be taken during experiments to ensure that the orientation of cross-sections was consistent (Baas and Lin, 2011). This in vitro technique granted investigators at least 90% accuracy in assessing microtubule polarity (Heidemann and McIntosh, 1980).

Follow-up studies using this hooking technique in culture found that the predominant polarity of microtubules in axons is plus-end-out (Baas et al., 1989;

Burton and Paige, 1981; Heidemann et al., 1981). Further studies in other systems confirmed these findings, and now it is generally accepted that the predominant direction of microtubules in axons is plus-end-out (Baas et al., 1987;

Baas et al., 1988; Baas and Ahmad, 1992; Topp et al., 1994; Viancour and

Forman, 1987). Characterization of polarity in dendrites would come years later, with fascinating and unexpected results.

It was first found in frog primary olfactory neurons and teleost retinal cone cells using the hooking technique that the predominant direction of microtubules in dendrites is plus-end-in (Burton, 1985; Troutt and Burnside, 1988a; Troutt and

Burnside, 1988b). A later study also observed plus-end-in-directed microtubules in cultured hippocampal neurons, frog mitral dendrites, and cultured rat sympathetic neurons (Baas et al., 1991). An important distinction, however, is

9 that microtubule polarity in these dendrites is mixed; there are both plus-end-in and plus-end-out microtubules (Baas et al., 1991). In support of these data, experiments using labeled microtubules also show that microtubule polarity is mixed in dendrites and predominantly plus-end-out in axons (Baas and Ahmad,

1992; Baas and Black, 1990; Brown et al., 1993; Wang et al., 1996). This uniformity in axons and non-uniformity in dendrites begged the question of what microtubule polarity might mean for these different compartments and their identity.

Despite these discoveries in culture, microtubule polarity in vivo remained an open question. With the use of EB1-GFP in the da system, researchers have been able to test for microtubule polarity in intact organisms. This

GFP-conjugated +TIP-binding protein allowed investigators to track the growing plus-ends of microtubules and describe microtubule dynamics (Rolls et al., 2007;

Stone et al., 2008). The direction of comet growth corresponds to the direction of microtubule polymerization. Therefore, comets moving in an anterograde direction, away from the cell body, mark plus-end-out microtubule polymerization, while comet moving in a retrograde direction, towards the cell body, mark plus-end-in microtubule polymerization. Investigators found that EB1-GFP

"comets" move in a predominantly retrograde direction in dendrites, indicating that microtubule polymerization in this context is mostly towards the cell body

(Rolls et al., 2007; Stone et al., 2008). These findings were seen by some at the time as a surprise and a possible departure from the expected mixed polarity observed by earlier studies (Baas and Lin, 2011).

Follow-up studies show two important findings. One, class I ddaE dendrites initially develop with mixed polarity before plus-end-in microtubules become more

10 and more predominate (Hill et al., 2012). Two, dendrites that regrow after injury display more mixed polarity before becoming predominantly plus-end-in (Song et al., 2012; Stone et al., 2014). These findings suggest the tantalizing possibility that plus-end-out microtubule polymerization is a highly regulated, cell morphology-determining feature during dendrite growth that is abrogated upon maturity. Plus-end-out and mixed microtubule polymerization may be a hallmark of developing and/or dynamic dendrites, while predominantly plus-end-in microtubule polymerization may be a hallmark of mature neurons.

Some of the first data to link plus-end-out growth with dendrite development came from studies of EB1-GFP comets in class IV ddaC neurons. The authors investigated microtubule polymerization at 96 h AEL, when longer primary branches are stable and terminal branches are still dynamic (Lee et al., 2011;

Parrish et al., 2009; Ye et al., 2007). Investigators observed that plus-end-out microtubule polymerization is more frequent in shorter, higher order branches

(Ori-McKenney et al., 2012). Importantly, it was observed that terminal branches are more likely to extend or remain stable when anterograde comets enter them

(Ori-McKenney et al., 2012). Moreover, the majority of terminal branches without any EB1 comets retracted (Ori-McKenney et al., 2012). These results suggest that plus-end-out microtubule polymerization promotes growth and stability of terminal arbors. Consistent with this finding, loss of the microtubule nucleator g-tubulin results in reduced dendrite size and complexity (Ori-McKenney et al.,

2012). Furthermore, this work shows that branching and microtubule dynamics correlate with levels of Golgi outposts, crucial secretory organelles found in dendrites, arguing that these compartments may play a role in dendrite development through microtubule regulation (Gardiol et al., 1999; Horton et al.,

11 2005; Horton and Ehlers, 2003; Ori-McKenney et al., 2012; Pierce et al., 2001; Ye et al., 2007). In addition, the authors found that multiple EB1-GFP comets can originate from Golgi outposts, indicating that Golgi outposts may be sites of acentrosomal microtubule nucleation (Ori-McKenney et al., 2012). Interestingly, the direction of microtubule polymerization also correlates with Golgi outposts, since all comets beginning from a given Golgi outpost move in the same direction

(Ori-McKenney et al., 2012).

A very recent study provides more evidence not only that Golgi outposts are crucial for microtubule polymerization direction, but also that plus-end-out microtubule polymerization is an important part of dendrite growth and branching

(Yalgin et al., 2015). The authors found that a class I-specific transcription factor,

Abrupt, limits branching by promoting Centrosomin (Cnn), a centrosome-associated protein that is crucial for microtubule spindle formation

(Dobbelaere et al., 2008; Hayward et al., 2014; Li et al., 2004; Sugimura et al.,

2004; Yalgin et al., 2015). Centrosomin limits branching by limiting plus-end-out microtubule polymerization and promoting net plus-end-in microtubule polymerization from Golgi outposts (Yalgin et al., 2015).

In order for microtubules to polymerize, they must first be nucleated. This can occur in many different circumstances in neurons. The centrosome is the most classic example, and it has been found that the centrosome is involved in polarized migration and initial growth of the axon (de Anda et al., 2005;

Etienne-Manneville, 2004; Lefcort and Bentley, 1989; Manneville and

Etienne-Manneville, 2006; Zmuda and Rivas, 1998). These data and developmental disorders associated with mutated centrosome-related proteins highlight the centrosome’s importance during neurodevelopment (Kuijpers and

12 Hoogenraad, 2011). However, beyond these events, the centrosome is not thought to play a crucial role in the neuron (Basto et al., 2006; Kuijpers and

Hoogenraad, 2011; Stiess et al., 2010). Rather, the majority of new microtubule polymerization is predicted to occur non-centrosomally as a consequence of microtubule severing or from de novo nucleation from g-tubulin (Jinushi-Nakao et al., 2007; Mao et al., 2014; Stone et al., 2012; Yu et al., 2008). As previously mentioned, studies have suggested that Golgi outposts are also sites of microtubule nucleation (Ori-McKenney et al., 2012; Yalgin et al., 2015). However, conflicting data exist concerning the role of Golgi outposts in microtubule dynamics (Nguyen et al., 2014).

The Golgi complex is a site of acentrosomal nucleation in fibroblasts, despite its location near the centrosome (Chabin-Brion et al., 2001; Efimov et al., 2007;

Miller et al., 2009). This nucleation, however, requires the centrosomal protein

AKAP450, g-tubulin, and CLASPs (Chabin-Brion et al., 2001; Efimov et al., 2007;

Hurtado et al., 2011; Miller et al., 2009; Rivero et al., 2009). In neurons, the Golgi complex is present as Golgi stacks in the cell body and Golgi outposts in dendrites (Gardiol et al., 1999; Horton et al., 2005; Pierce et al., 2001). Work indicates that Golgi outposts supply membrane for growing dendrite arbors and are necessary for dendrite growth (Horton et al., 2005; Ye et al., 2007).

1.5.2 Microtubules are Crucial for Neurons at all Stages

Initial growth of new neuronal processes and axonal branching requires the protrusive force of microtubules (Gallo, 2011). Recent evidence indicates that this is supplied by kinesin-powered microtubule sliding (Lu et al., 2013). In this process, molecular motors use multiple microtubule molecules to generate force

13 (Lu et al., 2013). Moreover, microtubules are required for both axon and dendrite growth and maintenance (Conde and Cáceres, 2009). The axon compartment requires microtubule stability for its establishment and microtubule dynamics for growth cone extension and targeting (Dent and Gertler, 2003; Gonzalez-Billault et al., 2001; Roossien et al., 2014; Witte et al., 2008). Microtubule stability and dynamics are also shown to promote axon growth after injury (Baas and Ahmad,

2013; Bradke et al., 2012; Chisholm, 2013; Hur et al., 2012). Functionally, microtubules are indispensable for allocating synaptic and intracellular components to their appropriate locations (Rolls, 2011). Microtubules also enter dendritic spines, indicating a possible role in synaptic plasticity (Gu et al., 2008;

Hu et al., 2008; Jaworski et al., 2009). Very recent work links microtubule polymerization with terminal branch stability and growth in dendrites

(Ori-McKenney et al., 2012; Yalgin et al., 2015). Lastly, microtubules and their regulation are critical determinants of dendrite arborization (Jinushi-Nakao et al.,

2007; Yalgin et al., 2015; Ye et al., 2011). Taken together, evidence supports the conclusion that microtubules are crucial for proper neurodevelopment and function.

1.5.3 Neurological Disorders Linked to Microtubules

Aberrations in proteins associated with microtubule function and stability have been implicated in several neurological disorders. Mutations in the molecular motor Dynein and associated proteins are linked to a number of diseases, including, but not limited to, spinal muscular atrophy, Charcot-Marie-Tooth disease, lissencephaly, pachygyria, and polymicrogyria (Lipka et al., 2013;

Millecamps and Julien, 2013). Lissencephaly-1 (LIS1), a dynein regulator, is

14 mutated in a large proportion of lissencephaly and Miller-Dieker syndrome cases

(Dobyns et al., 1993; Reiner et al., 1993). In addition, levels of the microtubule-associated protein Tau, which stabilizes microtubules in the axon, are thought to influence transport dynamics (Millecamps and Julien, 2013).

Therefore, when Tau is misregulated, it may lead to axon transport defects and taupathies (Millecamps and Julien, 2013). Moreover, hyperphosphorylated Tau causes neurofibrillary tangles associated with disease and may also lead to disrupted microtubule organization (Hardy, 2006; Patrick et al., 1999; Wagner et al., 1996).

While the normal function of many microtubule isotypes is unclear, mutations in these genes have been linked to disease (Chakraborti et al., 2016; Tischfield et al., 2011). These may manifest as a number of phenotypes caused by inherited or de novo mutations, resulting in disorders such as microcephaly, lissencephaly, polymicrogyria, progressive neurodegeneration, and intellectual disability (Tischfield et al., 2011). Even subtle changes have been linked with disease and are predicted to interfere with normal microtubule dynamics and interactions with associated proteins. As an example, substitutions of R402 in

TUBA1A, R402C and R402H, result in a phenotype similar to lissencephaly due to LIS1 mutations, implying a possible role for this residue with normal

LIS1/Dynein function (Kumar et al., 2010). Together, these data highlight the importance of microtubules in neurodevelopment and disease. Given the importance of microtubules and dendrite morphology in proper neurological function, it is important to consider how the two are related.

15 1.6 Dendrite Morphology and Microtubules

1.6.1 Dendrite Morphology and Functionality

Dendrites are localized, patterned, and sized to receive inputs from the environment or from other cells. This is particularly the case in somatosensory and visual systems, where the location of arbors represents a specific location in the body or a feature of the outside world (Lefebvre et al., 2015). In the da system, this is well represented by class IV neurons, which cover a large area and scale to cover the entire field of the body wall (Grueber et al., 2002; Parrish et al., 2009). This morphology is crucial for their function as nociceptors (Ferreira et al., 2014; Stewart et al., 2012; Tracey et al., 2003; Zhong et al., 2010). On the other hand, smaller dendritic arbors are sized for fewer inputs. For example, the midget bipolar cell has a relatively small dendritic arbor and receives inputs from only one cone cell (Kolb, 1970).

Studies of pyramidal cells from the neocortex and the hippocampus correlate dendritic morphology with firing patterns (Bilkey and Schwartzkroin, 1990;

Chagnac-Amitai et al., 1990; Mason and Larkman, 1990; Yang et al., 1996). In general, neurons with larger and more complex apical dendrite arbors are more likely to exhibit burst firing as opposed to tonic firing (Bastian and Nguyenkim,

2001; Mason and Larkman, 1990; Yang et al., 1996). Tonic firing describes a pattern of similarly spaced spikes, while burst firing describes a repeating pattern of two or more spikes at a short interval, followed by a longer interspike interval

(Krahe and Gabbiani, 2004). Interestingly, the bursting pattern is thought to more reliably transmit a signal and more likely to cause lasting changes, such as long-term potentiation and long-term depression (Birtoli and Ulrich, 2004;

16 Eggermont and Smith, 1996; Martinez-Conde et al., 2002; Swadlow and Gusev,

2001; Thomas et al., 1998; Yun et al., 2002). Computational studies have since sought to model these findings, and one particular work demonstrates how dendrite morphology may play a role in defining observed firing patterns (van

Elburg and van Ooyen, 2010). In their pyramidal cell model, they characterized how dendrite morphology is likely to result in tonic or bursting patterns. In one simulation, removing apical dendrites causes a switch in firing patterns from bursting to tonic. When they systematically analyzed smaller arbor sizes, they found that a balanced size, balanced length, and certain topologies are more likely to promote a bursting pattern. Cells that are too large or too small compared with certain ranges of symmetry are more likely to fire tonically.

Furthermore, asymmetric conformations lower the minimum and maximum sizes conducive to burst firing. Together, these data support the idea that dendrite morphology can have a profound impact on neuronal activity.

Several diseases and stress states correlate with changes in dendrite morphology, and some of these changes can also correlate with aberrations in

firing patterns (discussed in van Elburg and van Ooyen, 2010; Lefebvre et al.,

2015). Both chronic and short-term stress results in reduced dendrite complexity in pyramidal neurons (Brown et al., 2005; Cook and Wellman, 2004; Magariños et al., 1996; Sousa et al., 2000; Radley et al., 2004). It is argued, therefore, that reduced bursting may explain aspects of these diseases (van Elburg and van

Ooyen, 2010). In post-mortem studies, dendrites from patients who suffered from developmental disorders such as Fragile X, Down syndrome, Rett syndrome, and autism spectrum disorders have alterations in dendrite morphology (Dierssen and

Ramakers, 2006; Kulkarni and Firestein, 2012). Oftentimes, dendrites from these

17 patients are smaller and have reduced complexity (Dierssen and Ramakers,

2006; Kulkarni and Firestein, 2012). Moreover, reduced dendrite complexity is also found in patients who suffered from schizophrenia, Alzheimer’s, and stress disorders (Kulkarni and Firestein, 2012). Altogether, these data support the idea that dendrite development, maintenance, and morphology are highly important for healthy neuronal activity.

1.6.2 Molecular Motors and +TIPs

Molecular motors and +TIPs also play important roles in regulating dendrite morphology and microtubule polarity. For example, dynein and its cofactor NudeE are required for normal class IV dendrite morphology and axonal microtubule polarity (Arthur et al., 2015; Satoh et al., 2008; Zheng et al., 2008). Kinesin-2 and the +TIP proteins Apc, Apc2, and EB1 maintain uniform microtubule polymerization polarity in class I ddaE cells (Mattie et al., 2010). It is argued, therefore, that +TIPs may recruit Kinesin-2 to growing microtubules, where it can guide microtubule polymerization in the correct direction (Mattie et al., 2010).

Additionally, the molecular motor CHO1/MKLP1/KIF23 is also necessary for the maintenance of dendrites in sympathetic neurons (Sharp et al., 1997; Yu et al.,

2000). LIS1, mentioned above for its association with dynein and neurological disorders, is also necessary to promote dendrite growth and branching in mushroom body neurons (Liu et al., 2000; Smith et al., 2000). These results highlight the importance of molecular motors in directing microtubule polymerization, microtubule polarity, and neuronal morphology.

18 1.6.3 Transcription Factors

Transcription factors can have profound effects on dendrite morphology (Santiago and Bashaw, 2014 and Puram and Bonni, 2013). For example, the transcription factor hamlet prevents multidendritic morphology despite the presence of another transcription factor that has since been shown to promote dendrite branching

(Moore et al., 2002). Cut also promotes actin rich branching and is necessary for normal morphology in classes II-IV (Grueber et al., 2003; Jinushi-Nakao et al.,

2007). Moreover, Cut has been shown to regulate cellular secretion through the

COPII secretory pathway and can promote both Golgi outpost and endoplasmic reticulum outpost formation in the dendrite (Iyer et al., 2013). Additionally, Cut,

ACJ6, Drifter, and Lola are necessary for normal dendritic targeting of Drosophila olfactory neurons (Komiyama et al., 2003; Komiyama and Luo, 2007; Spletter et al., 2007). Spineless uniquely promotes larger dendrites in some situations and limits dendrite size in others, leading to the conclusion that it promotes arbor diversity in the da system (Kim et al., 2006). Lola also regulates the actin cytoskeleton to control dendrite morphology in all four classes of da neuron

(Ferreira et al., 2014). In C. elegans, MEC-3 and AHR-1 determine dendrite morphology in distinct cell types by promoting or repressing HPO-30, respectively

(Smith et al., 2013). In vertebrates, Neurogenin 2 determines the cellular identity and morphology of unipolar apical dendrites (Hand et al., 2005). Also in vertebrates, NeuroD, CREB, and CREST all promote dendrite growth in an activity-dependent manner downstream of calcium influx and calcium signaling

(Aizawa et al., 2004; Dijkhuizen and Ghosh, 2005; Gaudillière et al., 2004; Puram and Bonni, 2013). Sp4, interestingly, limits dendrite branching of cerebellar

19 granule neurons by repressing transcription of Neurotrophin 3 (Ramos et al.,

2009). Nevertheless, while these transcription factors demonstrate a number of ways in which dendrite morphology can be regulated, more focus will be devoted in this section to transcription factors that determine dendrite morphology through microtubule regulation.

Knot is specifically expressed in class IV neurons and is necessary for normal class IV morphology (Jinushi-Nakao et al., 2007). Loss of knot leads to a striking decrease in class IV dendrite branching, length, and coverage (Jinushi-Nakao et al., 2007). Consistently, gain of Knot in class I leads to gain in dendrite length and branching (Jinushi-Nakao et al., 2007). Furthermore, Knot can promote levels of Spastin, a microtubule-severing protein, indicating the possibility that

Knot determines morphology through Spastin regulation (Jinushi-Nakao et al.,

2007). Consistent with this, loss of spastin results in a loss of dendrite coverage in class IV cells (Jinushi-Nakao et al., 2007). Moreover, loss of spastin suppresses the gain of Knot phenotype in class IV (Jinushi-Nakao et al., 2007).

Another transcription factor that regulates dendrite morphology is dendritic arbor reduction 1 (dar1). dar1 mutants show a striking loss of dendrites in all four classes of da neurons (Ye et al., 2011). Testing for cellular autonomy, the authors show that Dar1 acts in the neurons (Ye et al., 2011). The authors observed not only a loss of microtubule rich dendrite arbors with loss of dar1, but also a consistent gain of microtubule rich arbors with gain of Dar1 (Ye et al., 2011). They conclude, therefore, that Dar1 regulates dendrite morphology through microtubule regulation (Ye et al., 2011). This appears to be the case, since a recent study found that Dar1 regulates levels of several dynein genes (Wang et al., 2015).

A recently characterized transcription factor that determines dendrite

20 morphology is Abrupt. In the da system, Abrupt is expressed specifically in class I and limits dendrite branching and size (Li et al., 2004; Sugimura et al., 2004).

Interestingly, Abrupt promotes Cnn, which localizes to Golgi outposts (Yalgin et al., 2015). At Golgi outposts, Cnn limits plus-end-out microtubule polymerization and promotes net plus-end-in microtubule polymerization from

Golgi outposts (Yalgin et al., 2015). Loss of cnn leads to plus-end-out microtubule polymerization that is dependent on wee Augmin. Furthermore, they found that plus-end-out microtubule polymerization correlates with terminal branch extension (Yalgin et al., 2015). Taken together, these data indicate that Abrupt limits dendrite outgrowth and branching by limiting plus-end-out microtubule polymerization. This is consistent with the finding in class IV that plus-end-out microtubule polymerization in terminal dendrite branches correlates with branch stability and growth, while a lack of microtubule polymerization correlates with branch retraction (Ori-McKenney et al., 2012). These data are also consistent with the hypothesis that Golgi outposts are sites of acentrosomal microtubule nucleation (Ori-McKenney et al., 2012). Importantly, these data indicate that plus-end-out microtubule polymerization can promote dendrite branching and branch stability.

1.7 FoxO is a Transcription Factor With Complex Regulation and Functions

The first forkhead box (Fox) protein was discovered in Drosophila and named after the mutant phenotype, in which ectopic head regions replace embryonic foregut and hindgut structures (Weigel et al., 1989). The authors described Fox nuclear localization and predicted that, despite its dissimilarity with known DNA

21 binding proteins at the time, Fox regulates cellular activity at the transcriptional level (Weigel et al., 1989). Since then, it was found to bind DNA and act as a transcription factor (Carlsson and Mahlapuu, 2002). Also, more than one hundred

Fox family members within several subfamilies have been discovered in animals and fungi (Carlsson and Mahlapuu, 2002).

The word forkhead has since been used to describe the DNA binding domain observed in the Fox family, a "winged-helix" structure that contains many well-conserved regions (Carlsson and Mahlapuu, 2002; Clark et al., 1993; Weigel and Jäckle, 1990). The forkhead domain, composed of numerous helix-turn-helix domains, allows Fox proteins to bind DNA as monomers (Carlsson and

Mahlapuu, 2002; Jin et al., 1999). Most Fox proteins recognize a similar core consensus sequence located in an asymmetrical binding site, but members of the

Forkhead box, class O (FoxO) subfamily only partially recognize this sequence

(Carlsson and Mahlapuu, 2002; Furuyama et al., 2000; Kaufmann et al., 1995;

Overdier et al., 1994; Pierrou et al., 1994). Evidence points to a distinct domain at helix 3 in FoxO family members that may account for their divergence in specificity (Furuyama et al., 2000). Studies such as these have lead to conclusions that subtle changes in the forkhead subdomains and areas flanking the core consensus sequence are crucial for specific DNA binding (Jin et al.,

1999; Marsden et al., 1998; Overdier et al., 1994; Pierrou et al., 1994).

Like other transcription factors, the Fox family members contain nuclear localization sequences (NLSs) that target them to the nucleus (Carlsson and

Mahlapuu, 2002). The FoxO family members (FoxO1, FoxO3, FoxO4, and FoxO6 in mammals, foxO in Drosophila, daf-16 in C. elegans, and FoxO5 in zebrafish) are distinct in that their NLSs are regulated by signaling molecules (Carlsson and

22 Mahlapuu, 2002; Eijkelenboom and Burgering, 2013). This regulation determines whether FoxO is located in the nucleus, where it can act as a transcription factor, or in the cytoplasm, where it cannot act as a transcription factor. The most well-characterized example of this regulation is phosphorylation of FoxO by the

Serine/Threonine kinase AKT, also known as Protein Kinase B, or PKB.

Phosphorylation at three evolutionarily conserved sites causes FoxO to be preferentially located in the cytoplasm, where it is sequestered by 14-3-3 and targeted for degradation (Biggs et al., 1999; Brunet et al., 1999; Burgering and

Kops, 2002).

However, AKT is only one of several upstream regulators of FoxO

(Eijkelenboom and Burgering, 2013). Phosphorylation at different sites by JNK and MST1, both involved in stress signaling, have the opposite effect compared with AKT (Lehtinen et al., 2006). Phosphorylation by MST1 disrupts the

FoxO-14-3-3 interaction, freeing FoxO to enter the nucleus (Lehtinen et al., 2006).

Phosphorylation of FoxO by JNK also causes FoxO to translocate into the nucleus

(Essers et al., 2004; Oh et al., 2005; Wang et al., 2005). Moreover, acetylation, deacetylation, interactions with cofactors, and ubiquitination contribute to FoxO regulation and activity (Brunet et al., 2004; van der Horst and Burgering, 2007;

Frescas et al., 2005). Indirect regulation of FoxO signaling has also been shown, since some of the molecules that regulate FoxO also regulate cofactors, 14-3-3 binding affinity, and upstream signaling molecules (Bouras et al., 2005; Nemoto et al., 2005; Picard et al., 2004; Rodgers et al., 2005; Sunayama et al., 2005).

Since FoxO is regulated by such a variety of signaling molecules, it stands to reason that FoxO plays diverse roles. Indeed, FoxO family members are thought to regulate a complex combination of metabolism, stress response, cell survival,

23 apoptosis, cellular proliferation, tumor suppression, stem cell homeostasis, and longevity (van der Horst and Burgering, 2007). Great interest in FoxO came from lifespan studies in C. elegans. In this system, reducing insulin/insulin-like signaling leads to a significant increase in overall lifespan (Kenyon et al., 1993).

However, this increase is lost when the C. elegans ortholog of FoxO, daf-16, is also lost (Kenyon et al., 1993; Lin et al., 1997). This indicates that FoxO is necessary for increased lifespan in certain contexts (Kenyon et al., 1993; Lin et al., 1997; Ogg et al., 1997; Paradis and Ruvkun, 1998). Studies have indicated that this increased lifespan is due to metabolic regulation, since FoxO promotes a fasting state through gluconeogenesis and suppression of glycolysis (Barthel et al., 2001; van der Horst and Burgering, 2007; Nakae et al., 2001; Zhang et al.,

2006). Consistent with this conclusion, it has since been shown that caloric restriction leads to a longer lifespan in C. elegans (Schulz et al., 2007).

Furthermore, increasing glucose reduces lifespan through inhibition of FoxO, indicating that lowering caloric intake may increase lifespan (Lee et al., 2009).

Downstream, FoxO upregulates apoptotic factors such as Fas ligand, BIM, and BCL-6 (Brunet et al., 1999; Dijkers et al., 2000; Tang et al., 2002). FoxO also induces cell-cycle arrest through regulation of cyclin D and cyclin G2, as well as other cell-cycle proteins (Fernández de Mattos et al., 2004; Kops et al., 2002b;

Martínez-Gac et al., 2004; Medema et al., 2000; Schmidt et al., 2002; ). These conclusions complicate the interpretation of FoxO’s role in biology. Although

FoxO is necessary for increased lifespan, FoxO also promotes apoptosis and induces cell-cycle arrest (van der Horst and Burgering, 2007). In contrast, FoxO is inhibited by AKT, which suppresses apoptosis and promotes cell division

(van der Horst and Burgering, 2007). However, as it will be discussed, FoxO is

24 pro-survival in some cases.

FoxO can be pro-survival during stress response. Researchers observed that upon oxidative stress, FoxO translocates into the nucleus (Brunet et al., 2004;

Essers et al., 2004; Henderson and Johnson, 2001). FoxO upregulates antioxidants such as catalase and manganese superoxide dismutase (Kops et al.,

2002a; Nemoto and Finkel, 2002; ). FoxO induces a reversible quiescent state in stressful and metabolically challenging environments (Kops et al., 2002a; Kops et al., 2002b). Interestingly, this quiescent state protects cells from oxidative stress (Kops et al., 2002a). Furthermore, colon carcinoma cells are forced into quiescence by FoxO activation (Kops et al., 2002b). Taken together, these data indicate that FoxO can promote cell survival in normal cells and suppress growth in cancer cells.

Given the variety of phenotypes, it stands to reason that a balance between

FoxO’s opposing roles is critical. The importance of this balance can be observed in disease states (van der Horst and Burgering, 2007). For example, FoxO could have a role in diabetes, since loss of FoxO1 rescues diabetic phenotypes in insulin resistant mice, while gain of FoxO1 induces diabetes (Nakae et al., 2002).

Furthermore, FoxO is a tumor suppressor, since simultaneous loss of FoxO1,

FoxO3, and FoxO4 results in thymic lymphoma and haemangioma (Paik et al.,

2007). Also, in a Parkinson’s disease model, FoxO is activated by LRRK2 and enhances neurotoxicity (Kanao et al., 2010). Taken together, these data indicate that misregulation of FoxO can have profound consequences.

FoxO can also have different roles in the nervous system. In adults, FoxO promotes both the survival of neuronal stem cells and neurogenesis, while during development, FoxO causes apoptosis (Paik et al., 2009; Siegrist et al., 2010). In

25 addition, FoxO overexpression promotes neuronal death (Barthélémy et al., 2004;

Gilley et al., 2003; Srinivasan et al., 2005; Yuan et al., 2009). In response to stressors, however, FoxO3a can be neuroprotective (Mojsilovic-Petrovic et al.,

2009).

1.8 FoxO and Neurodevelopment

In mammals, FoxO1, FoxO3, and FoxO6 are all expressed in the central nervous system (Furuyama et al., 2000; Hoekman et al., 2006; Jacobs et al., 2003; de la

Torre-Ubieta et al., 2010). While different FoxO genes can act redundantly, such as in tumor suppression, there is some evidence that different FoxOs can play specific roles in nervous system development and function (van der Horst and

Burgering, 2007). FoxO6, for example, promotes spine morphogenesis and is necessary for memory consolidation (Salih et al., 2012). FoxO3 is active in programmed cell death signaling in sympathetic and motor neurons (Barthélémy et al., 2004; Gilley et al., 2003). FoxO1 forms a complex with SnoN1 and represses doublecortin, allowing granule neurons to branch and migrate normally

(Huynh et al., 2011).

Recently, it was shown that simultaneous knockdown of FoxO1, FoxO3, and

FoxO6 causes polarity defects in developing cerebellar granule neurons both in vitro and in vivo (de la Torre-Ubieta et al., 2010). Moreover, morphological defects are also present when FoxO1, FoxO3, and FoxO6 are simultaneously knocked down in pre-polarized cells in culture (Christensen et al., 2011). These data indicate that FoxO can determine neuronal polarity and may maintain coordinated growth after neuronal polarization.

Very recently, FoxO was found to regulate microtubules in the axons of

26 Drosophila motoneurons (Nechipurenko and Broihier, 2012). Loss of foxO results in motoneurons with smaller synaptic boutons, presynaptic organizing centers in axons (Nechipurenko and Broihier, 2012). Importantly, foxO null animals also have increased microtubule stability (Nechipurenko and Broihier, 2012). This was quantified by visualizing Futsch/MAP1B, a microtubule stabilizer and marker of stable microtubules Futsch/MAP1B (Halpain and Dehmelt, 2006; Hummel et al.,

2000; Roos et al., 2000). Numbers of Futsch/MAP1B loops are increased with loss of foxO, indicating increased microtubule stability (Nechipurenko and

Broihier, 2012). Verifying this conclusion, the authors also observed that pharmacological increase of microtubule stability also results in an increase in

Futsch loops in motoneurons (Nechipurenko and Broihier, 2012). These data argue that FoxO limits microtubule stability in motoneurons (Nechipurenko and

Broihier, 2012). Consistent with this finding, genetic loss of microtubule stability with a hypomorphic allele of Futsch, futschk68, rescues the foxO null phenotype

(Nechipurenko and Broihier, 2012).

Given these findings and the importance of microtubule dynamics in both axons and dendrites, we predicted that FoxO would also play a crucial role in dendrite development. We therefore took advantage of the tools available in

Drosophila and the da system to test if FoxO plays an in vivo role in determining dendrite morphology, microtubule polymerization, and microtubule stability.

1.9 Focus of Thesis

For my thesis work, I endeavored to determine a possible role for FoxO in dendrite development. Though previous work implicated FoxO in axonal microtubule organization and neuronal polarity, a role for FoxO in dendrite

27 arborization had not been established. I predicted that if loss and gain of FoxO result in differences in dendrite morphology, these phenotypes could be linked to microtubule regulation. To test this, I pioneered the use of the da system in our lab to visualize dendrite development. Moreover, through live and time-lapse imaging, I aimed to establish how FoxO might determine live properties of dendrite development and microtubule dynamics.

28 Figure 1.1

50 µm class I class II class III class IV

29 Fig 1.1. Classes of the dendritic arborization system. Traces of classes I-IV are listed from left to right. Class I is the smallest and least branched, while class IV is the largest and most branched. Class III is notable for its short, spiky terminal branches. The organization of this figure was inspired by Jinushi-Nakao et al.

(2007).

30 Chapter 2

FoxO regulates microtubule dynamics and polarity to promote dendrite branching in Drosophila sensory neurons

31 FoxO regulates microtubule dynamics and polarity to promote dendrite branching in Drosophila sensory neurons

James C. Sears and Heather T. Broihier

Department of Neurosciences, Case Western Reserve University, Cleveland, OH

44106, USA

Reprinted with permission from Developmental Biology, Copyright, 2016.

32 2.1 Abstract

The size and shape of dendrite arbors are defining features of neurons and critical determinants of neuronal function. The molecular mechanisms establishing arborization patterns during development are not well understood, though properly regulated microtubule (MT) dynamics and polarity are essential.

We previously found that FoxO regulates axonal MTs, raising the question of whether it also regulates dendritic MTs and morphology. Here we demonstrate that FoxO promotes dendrite branching in all classes of Drosophila dendritic arborization (da) neurons. FoxO is required both for initiating growth of new branches and for maintaining existing branches. To elucidate FoxO function, we characterized MT organization in both foxO null and overexpressing neurons. We

find that FoxO directs MT organization and dynamics in dendrites. Moreover, it is both necessary and sufficient for anterograde MT polymerization, which is known to promote dendrite branching. Lastly, FoxO promotes proper larval nociception, indicating a functional consequence of impaired da neuron morphology in foxO mutants. Together, our results indicate that FoxO regulates dendrite structure and function and suggest that FoxO-mediated pathways control MT dynamics and polarity.

2.2 Introduction

Dendrite architecture is established during development and lays the groundwork for neuronal connectivity and function. Dendrites acquire simple or complex morphologies depending on the degree of branching and growth of their arbors.

Regulation of dendrite branching and growth requires accurate integration of

33 cell-intrinsic and cell-extrinsic factors. On the cell-intrinsic side, cohorts of transcription factors direct the expression of downstream effector molecules that together impart cell-type specific morphologies. While a number of transcription factors have been implicated in dendrite morphogenesis, the remarkable morphological diversity of dendrite arbors suggests that others remain to be identified.

Dendritic arborization (da) neurons are sensory neurons that innervate the larval epidermis and are grouped into four classes (classes I-IV) based on the size and shape of their dendrite arbors (Corty et al., 2009; Grueber et al., 2002).

Work in this system has detailed cytoskeletal characteristics that distinguish dendrite morphologies of classes of da neurons (Grueber et al., 2003;

Jinushi-Nakao et al., 2007). For instance, simple class I arbors and complex class

IV arbors differ in the extent to which their dendrite branches are populated by stable microtubules (MTs). The MT-associated protein (MAP) Futsch/MAP1B, binds and stabilizes MTs (Halpain and Dehmelt, 2006; Hummel et al., 2000; Roos et al., 2000). In class I neurons, many branches contain Futsch, while in class IV neurons, Futsch is confined primarily to main branches (Grueber et al., 2002;

Jinushi-Nakao et al., 2007). Moreover, loss of Futsch increases branching of class I neurons (Yalgin et al., 2015). Together these data suggest that dynamic

MTs are particularly critical in generating the highly branched dendrite arbors in class IV neurons.

The stereotyped and superficial positions of da neurons, as well as the two-dimensional shapes of their dendrite arbors, have greatly facilitated in vivo live imaging of dendrite growth and cytoskeletal dynamics in this system (Rolls et al., 2007; Stone et al., 2008). Such studies have established that da neuron

34 dendrites have mixed MT polarity during developmental stages characterized by rapid dendrite growth and branching (Hill et al., 2012). In other words, MT polymers are a mixture of plus-end-out (anterograde polymerizing) and minus-end-out (retrograde polymerizing) filaments. MT polarity matures over the course of larval development to an almost entirely minus-end-out orientation (Hill et al., 2012). The presence of plus-end-out MTs during stages of extensive branching suggests that anterograde MT polymerization may play a role in generating dendrite arbors. This hypothesis is supported by recent studies demonstrating a function for anterograde MT polymerization in facilitating nascent branch formation and stabilization (Ori-McKenney et al., 2012; Yalgin et al., 2015).

Transcription factor-mediated pathways play leading roles in regulating cytoskeletal assembly and organization in da neurons (Lefebvre et al., 2015;

Santiago and Bashaw, 2014), suggesting that developmental competence for dendrite growth and branching is established by cell-intrinsic factors. Interestingly, a number of transcription factors selectively regulate either the MT or actin cytoskeleton in da dendrites. For example, Cut and Lola control actin organization while Abrupt, Dar1, and Knot regulate MTs (Ferreira et al., 2014; Jinushi-Nakao et al., 2007; Yalgin et al., 2015; Ye et al., 2011). Identifying the suite of transcription factors regulating da neuron dendritogenesis and defining the cytoskeletal features they regulate is key to deciphering how these factors collaborate to control neuronal morphology.

We set out to test whether the transcription factor FoxO regulates development of da neuron dendrites. FoxO proteins regulate neural stem cell homeostasis, neuronal polarity, neurite outgrowth, synaptic function, and memory consolidation

(Christensen et al., 2011; de la Torre-Ubieta et al., 2010; Paik et al., 2009;

35 Renault et al., 2009; Salih et al., 2012). In addition, we previously found that the sole FoxO ortholog in Drosophila regulates MT organization in presynaptic terminals of motor neurons (Nechipurenko and Broihier, 2012). Together, these studies demonstrate that FoxO proteins are evolutionarily conserved regulators of neuronal structure and function. However, a role for FoxO proteins in dendrite arborization during neurodevelopment has not been investigated.

In this study, we demonstrate that Drosophila FoxO regulates dendrite development of da neurons. We find that FoxO is expressed in da neurons, and loss of FoxO results in decreased dendrite branching in all da neuron classes. To understand how FoxO promotes dendrite branching, we undertook a time-lapse analysis and demonstrate that FoxO stimulates initiation of new branch growth and also stabilizes existing branches. We hypothesized that these morphological defects result from aberrant MT organization. In line with this hypothesis, analyses of foxO loss-of-function (LOF) and overexpressing neurons demonstrate that FoxO regulates MT dynamics. Specifically, we find that FoxO promotes overall MT dynamics as well as anterograde MT growth. Taken with our previous study of FoxO function in motoneurons, these findings indicate that FoxO regulates MT organization in both motor axons and sensory dendrites. Lastly, we examined whether FoxO is required for da neuron function. Class IV da neurons are nociceptive, sensing noxious heat and mechanical stimuli (Hwang et al.,

2007; Tracey et al., 2003). We find that nociceptive responses are attenuated in foxO mutant larvae, indicating that FoxO is required for both structure and function of da neurons. Together, these findings extend in vivo functions of neuronal FoxO proteins to include dendrite arborization and suggest that regulating MT dynamics is a core neuronal function of FoxO family members.

36 2.3 Results

2.3.1 FoxO acts cell-autonomously to regulate class IV dendrite morphology

Our previous work established that FoxO organizes presynaptic MTs at the neuromuscular junction (NMJ) (Nechipurenko and Broihier, 2012). Because MT organization and dynamics are central to dendrite growth and branching, we hypothesized that FoxO regulates dendrite morphology. Class IV da cells are the largest and most elaborate of the da neurons, providing an ideal cell type in which to explore a possible function for FoxO in dendrite morphology. Dendrite outgrowth of class IV cells begins late in embryogenesis and continues through early larval stages, when it is characterized by a rapid growth as the arbor covers its receptive field. Following this phase, dendrite growth transitions to a phase of scaling growth in third instar larvae where growth of dendrite arbors and overall animal growth are synchronized (Parrish et al., 2009).

We examined dendrite growth and branching in early (72 h AEL; After Egg

Laying) and late (120 h AEL) third instar larvae in ddaC, a well-characterized

Class IV cell (Grueber et al., 2002). We labeled membranes of foxO nulls

(foxOD94) (Slack et al., 2011) and controls with membrane-targeted GFP via a class IV Gal4 driver to permit morphological analyses. Consistent with previous reports (Colombani et al., 2005), we do not detect a difference in overall body size between foxO mutants and controls. We find that at 72 h AEL, foxOD94 animals are 2.0 0.14 mm long (n = 12) and control animals are 2.0 0.15 mm ± ± long (n = 20). At 120 h AEL, foxOD94 animals are 3.2 0.07 mm long (n = 38) and ± control animals are 3.2 0.06 mm long (n = 39). We first assessed ddaC ±

37 branching at 72 h AEL. We find that loss of FoxO results in a 46.4% reduction in branch number, and a 27.7% reduction in overall dendrite length (Fig. 2.1A-D).

We utilized Sholl analysis to quantify branching as a function of distance from the soma (Sholl, 1953). We find that relative to controls, foxO nulls display decreased branching at both proximal and medial regions of the arbor (Fig. 2.S1A).

Decreased dendrite branching in foxO mutants leads to large regions of noninnervated epidermis within the area covered by individual class IV cells. We developed an ImageJ macro to first overlay a grid of 250 µm2 squares on dendrite arbors, and then analyze internal coverage as reflected by squares with/without a dendrite branch (Jinushi-Nakao et al., 2007; Stewart et al., 2012). We find that foxO nulls display a 2.2-fold increase in the proportion of empty squares relative to controls (Fig. 2.1E-G), consistent with decreased dendrite branching.

Together, these analyses argue that FoxO regulates the early, rapid phase of dendrite outgrowth and branching.

We next examined if the decrease in dendrite branching observed at 72 h AEL persists until 120 h AEL, the late third instar stage. At 120 h AEL, we find a 33.2% reduction in branch number (Fig. 2.1H-J) and a 28.7% reduction in overall dendrite length in foxO nulls (Fig. 2.1K). We again utilized Sholl analysis to quantify branching as a function of distance from the soma, and find reductions in branching throughout the arbor in foxO nulls relative to controls (Fig. 2.S1B). We next quantified internal coverage and find that foxO nulls display a 1.7-fold increase in the proportion of empty squares relative to controls (Fig. 2.1L-N).

Together, these findings indicate that loss of FoxO results in a sustained decrease in dendrite branching and a corresponding increase in epidermal area lacking innervation.

38 To assess cell autonomy, we undertook a clonal analysis of class IV ddaC using MARCM (Lee and Luo, 1999; Grueber et al., 2002). At 120 h AEL, foxO null ddaC clones display a 29.7% reduction in branch number relative to control cells (Fig. 2.2A-C), consistent with the phenotype observed in foxO nulls. foxO null clones also display a 24.4% reduction in total dendrite length at this stage

(Fig. 2.2D). Sholl analysis reveals a similarly shaped arbor as observed in foxO null animals (Fig. 2.S1C). We again tested internal coverage using an overlaid grid and find that foxO null ddaC clones display a 1.6-fold increase in the proportion of empty squares relative to controls at 120h AEL (Fig. 2.2E-G).

Because neither dendrite length nor branching of ddaC are more severely disrupted in foxO null animals than in foxO mutant clones (p > 0.05 for both), we conclude that FoxO acts cell-autonomously in class IV ddaC neurons to promote dendrite branching and growth.

2.3.2 FoxO is expressed in da neurons and regulates class I-III dendrite morphology

Our MARCM analysis implies that FoxO protein is expressed in class IV da neurons. In line with a cell-autonomous function, FoxO is expressed in ddaC neurons (Fig. 2.3A), as assessed with an anti-FoxO antibody (Nechipurenko and

Broihier, 2012). We further find that FoxO is expressed in class I-III da neurons

(Fig. 2.3B-D). The widespread expression of FoxO in da neurons raised the possibility that FoxO regulates morphology of multiple da neuron classes. To analyze morphology in class I-III cells, we labeled them using a class I-III Gal4 driver and membrane-targeted GFP. Class I cells have the simplest dendrite arbors of da neurons (Grueber et al., 2002). To test if FoxO Is necessary for

39 branching in these cells, we asked if dendrite morphology of two distinct class I cells, ddaE and vpda, is aberrant in foxO nulls. Compared with control class I ddaE cells, foxO nulls display a 19.9% reduction in branch number and a 15.1% reduction in length (Fig. 2.3E-H). In class I vpda cells, foxO nulls display a 32.3% reduction in branch number and an 18.3% reduction in length (Fig. 2.3I-L). Thus,

FoxO promotes length and branching in neurons with simple dendrite arbors.

To test if FoxO is also required in cells with intermediate-sized dendrite arbors, we analyzed both class II and III cells. An analysis of the class II cell ldaA reveals a 40.0% reduction in branch number and a 34.4% reduction in length in foxO nulls relative to controls (Fig. 2.3M-P). Finally, relative to control class III vdad cells, foxO null cells display a 25.6% reduction in branch number, and a trending, but not significant, 10.7% reduction in length (Fig. 2.3Q-T). These analyses demonstrate that FoxO promotes branching in cells of all da neurons classes, indicating that FoxO is broadly required for proper da neuron morphology.

2.3.3 FoxO promotes initiation and stabilization of new branches

We wondered whether FoxO acts to promote new branch growth, to stabilize existing branches, or both. To explore relative functions for FoxO in branch formation and stabilization, we undertook a time-lapse analysis of the class IV ddaC cell. We analyzed the class IV ddaC neuron at 96 h AEL because these cells are highly branched and dynamic at this time point (Lee et al., 2011;

Ori-McKenney et al., 2012; Parrish et al., 2009). We imaged individual ddaC neurons once, removed the animals and returned them to food, then 2 h later, re-imaged the same cells to assess branch gain and loss within a 2 h window

(Fig. 2.4A-D). We find that control ddaC cells gain 46.6 3.6 branches on ±

40 average, while foxO mutants gain 24.4 2.9 branches over this time period, ± indicating decreased branch initiation in foxO mutants (Fig. 2.4E). Over the same period, control cells lose 27.4 3.0 branches for a net gain of 19.3 5.3 ± ± branches, while foxO mutants lose 21.8 3.6 branches for a net gain of only 2.6 ± 1.8 branches (Fig. 2.4F-G). Thus, foxO mutant cells lose almost as many ± branches as they gain in the two-hour interval.

We also calculated gained and lost branches as fractions of the total number of dynamic branches present in each genotype in the two-hour window. By this measure, controls exhibit a significantly greater fraction of gained branches than foxO mutants, whereas foxO mutants display a greater fraction of lost branches

(Fig. 2.4H). If these relatively short-term changes in branch loss and growth are summed over development, they are predicted to result in the significantly smaller arbors observed in foxO mutant animals. Together, these data indicate that FoxO serves to both initiate new branch growth as well as to stabilize existing branches.

2.3.4 FoxO is sufficient to promote branch formation

The preceding loss-of-function analysis indicates that FoxO is necessary for dendrite branching. To test if FoxO is also sufficient for branching, we tested if its overexpression drives increased branching. We began by investigating whether

FoxO overexpression increases branching in class I cells, because these cells are simple with comparatively fewer branches. Thus, an increase in branching might be more apparent in class I cells than in highly branched class IV cells. Indeed,

FoxO overexpression leads to dramatically increased branching in two distinct class I cells: ddaE and vpda (Fig. 2.5A-D). Specifically, we find a 2.5-fold increase in branch number in ddaE and a 2.3-fold increase in vpda (Fig. 2.5E) in

41 FoxO overexpressing neurons relative to controls. Interestingly, FoxO overexpression in these cells does not alter the overall branching patterns of primary and secondary branches, but rather drives the formation of ectopic short, spiky branches. The main branches in FoxO overexpressing cells are slightly shorter than in controls, leading to an overall reduction in total dendrite length in spite of the elevated branch number in these cells (Fig. 2.5F). We next assessed whether FoxO overexpression also results in increased branching in slightly more complex class II da neurons. We find that FoxO overexpression leads to a 1.3-fold increase in branch number in the class II ldaA neuron and an overall reduction in dendrite length (Fig. 2.S2A-D). The short, ectopic branches observed in class II are very similar in appearance to those observed with FoxO overexpression in class I. Thus, FoxO overexpression promotes dendrite branching, but not dendrite length, in neurons with simple dendrite arbors.

We next wanted to determine if FoxO overexpression increases branch number in neurons with more complex dendrite arbors. For this analysis, we again turned to the class IV ddaC cell. Similar to our findings in class I and II cells, FoxO overexpression in ddaC generates ectopic short, spiky branches (Fig.

2.5G-H). We quantified branch number in these cells and find a 1.2-fold increase in branch number in class IV cells ddaC relative to controls (Fig. 2.5I). Again, as in class I and II cells, the main branches in FoxO overexpressing neurons are shorter than in controls, leading to an overall reduction in dendrite length (Fig.

2.5J). The increase in short ectopic branches, coupled with the decrease in main branch length, gives these cells a compact, bushy appearance. Because we utilized class-specific drivers to overexpress FoxO in these experiments, they support the conclusion that FoxO cell-autonomously promotes dendrite

42 branching. Furthermore, our analyses of dendrite morphology in foxO LOF and overexpression backgrounds indicate that foxO is necessary and sufficient for dendrite branch formation in multiple classes of sensory neurons.

2.3.5 FoxO limits the distribution of stable microtubules in dendrites

How does loss of FoxO alter dendrite morphology? To shed light on the cellular mechanism by which FoxO promotes dendrite branching, we characterized the

MT cytoskeleton in foxO mutants. We examined MTs because our prior work demonstrated that loss of FoxO alters MT stability and organization at the NMJ

(Nechipurenko and Broihier, 2012). Thus, a straightforward hypothesis is that

FoxO-dependent pathways regulate MT stability in dendrites. To examine this possibility, we labeled dendrites with Futsch/MAP1B, a MT-associated protein that stabilizes MTs and is itself a marker of the stable MT population (Halpain and

Dehmelt, 2006; Hummel et al., 2000; Roos et al., 2000).

We first assessed class I ddaE neurons to ask if FoxO regulates the distribution of stable MTs in these cells. We began with these cells because of their simple morphology and stereotyped pattern of Futsch staining

(Jinushi-Nakao et al., 2007). We find that in controls, while primary ddaE branches are strongly Futsch-positive, secondary branches typically have much weaker Futsch (Fig. 2.6A). Strikingly, in foxO nulls, we frequently find strong

Futsch expression extending well into secondary ddaE branches (arrows in Fig.

2.6B). We quantified the proportion of secondary branches with continuous

Futsch, and find a 1.6-fold increase in this proportion in foxO nulls relative to controls (Fig. 2.6C). Thus, loss of FoxO results in an increased distribution of

Futsch in ddaE.

43 To ask if FoxO is also sufficient to limit stable MTs in class I ddaE neurons, we tested the effect of FoxO overexpression on the distribution of Futsch. FoxO overexpression in ddaE results in a clear decrease in Futsch intensity throughout the arbor (Fig. 2.6D-E). We find that the intensity of Futsch staining is decreased in primary branches as well as in higher order branches. For purposes of quantification, we focused on Futsch expression in terminal branches greater than 20 µm in length. We wanted to exclude the short, spiky branches present only in the FoxO overexpressing cells to ensure that any change in

Futsch-positive branches was not solely the result of the presence of these short branches. We observe a 1.5-fold reduction in Futsch-positive branches in FoxO overexpressing neurons (Fig. 2.6F). Thus, while loss of FoxO leads to an expanded Futsch distribution in ddaE dendrites, FoxO overexpression results in a reduced Futsch distribution.

We went on to analyze the more complex distribution of Futsch in foxO null class IV ddaC neurons. In controls, the primary branches of these cells contain

Futsch, while higher order branches are generally Futsch-negative (Fig. 2.6G,

Grueber et al., 2003). We noticed that Futsch appeared to extend farther into higher order branches in foxO nulls relative to wild type (Fig. 2.6G-H). We quantified branches with Futsch and find a 1.6-fold increase the proportion of

Futsch-positive branches in foxO nulls relative to controls (Fig. 2.6I). This difference is pronounced in tertiary and terminal branches, which lack Futsch in controls, but are frequently Futsch-positive in foxO mutants (arrowheads in Fig.

2.6G-H). Thus, loss of FoxO results in an expanded distribution of Futsch, a stable

MT marker, arguing that FoxO normally limits MT stability in class IV da neurons.

Together, these results raise the possibility that the observed morphological

44 phenotypes in foxO mutants reflect alterations in underlying MT organization.

To test if increased MT stability underlies the morphological defects in foxO mutants, we examined whether otherwise decreasing MT stabilization rescues dendrite length and/or branching in foxO mutants. To this end, we analyzed genetic interactions between FoxO and Futsch. Because Futsch stabilizes MTs, we tested if decreasing MT stability by removing one copy of Futsch counteracts the loss of FoxO in class IV ddaC neurons. Relative to control dendrites, we find a

39.9% reduction in branching and a 38.3% reduction in length in foxO nulls (Fig.

2.S3A-B, E-F). We find that futsch dominantly suppresses deficits in branching and length observed in ddaC cells in foxO nulls (Fig. 2.S3A-F). Branch number is increased 1.3-fold in futschk68/+;;foxOD94 relative to foxOD94 alone, while length is increased 1.2-fold. This partial rescue is notable given that in our hands, futsch heterozygosity on its own significantly decreases both length and branching in ddaC (Fig. 2.S3E-F). Thus, we conclude that FoxO activity is normally balanced by Futsch activity in ddaC. The genetic interaction between foxO and futsch argues that elevated MT stability in foxO nulls contributes to the observed morphological defects. Moreover, we interpret our finding that both increased MT stability (foxO nulls) and decreased MT stability (futsch heterozygotes) result in decreased branching to suggest that MT stability and dynamics must be precisely balanced to support proper branch formation and maintenance.

2.3.6 FoxO is necessary for both anterograde polymerization and dynamics of microtubules

The alterations to Futsch distribution in foxO LOF and foxO overexpression backgrounds are consistent with altered underlying MT dynamics. To test this

45 hypothesis, we utilized EB1-GFP to visualize plus-end MT growth in vivo. EB1 binds the plus end of MTs, and an EB1-GFP fusion protein is widely used to track plus-end MT growth. When EB1-GFP binds to the growing plus-end of a MT, it is visualized as an EB1-GFP comet (Baas and Lin, 2011; Rolls et al., 2007; Stone et al., 2008). EB1-GFP comet number reveals the amount of MT growth, whereas comet direction (anterograde or retrograde) indicates MT orientation.

Developmental analyses of EB1-GFP dynamics have shown that da neurons gradually acquire minus-end-out polarity (Hill et al., 2012). During embryonic stages, dendrites contain roughly equal numbers of plus-end-out and minus-end-out MTs. This distribution gradually resolves to almost entirely minus-end-out polarity by the end of larval stages.

To investigate if FoxO regulates MT dynamics, we undertook a live EB1-GFP analysis in class IV ddaC neurons. We began by analyzing 96 h AEL larvae both because MTs are dynamic at this stage and because the larvae are amenable to live imaging (see Section 2.5). In controls, we find 45.4 7.2 comets/mm ± dendrite, in line with published reports (Fig. 2.7A, C, Stewart et al., 2012). In contrast, in foxO mutants, we find 22.5 3.5 comets/mm dendrite, or a 2.0-fold ± decrease in total comet number (Fig. 2.7B-C). Thus, at 96 h AEL, MTs are less dynamic in foxO mutant ddaC dendrites, consistent with the expanded distribution of Futsch in this background (Fig. 2.6G-I). Unexpectedly, we also find a marked

9.6-fold reduction in the percentage of anterograde comets in foxO nulls relative to controls. While 4.8% of the comets are anterograde in controls, only 0.5% of the comets are anterograde in foxO nulls (Fig. 2.7A-B, D; Supplemental Movie 1).

These data suggest that FoxO normally promotes anterograde polymerization of

MTs.

46 Supplementary material related to this article can be found online at http://dx.doi.org/10.1016/j.ydbio.2016.08.018.

To further test this hypothesis, we analyzed EB1-GFP comets in ddaC cells at an earlier developmental time point when a higher proportion of MTs are expected to have anterograde orientation. Thus, we adapted our live imaging protocol for younger, 72 h AEL larvae. At this stage, we do not detect a difference in overall comet number in foxO nulls relative to controls (Fig. 2.7E-G), arguing that FoxO does not regulate overall MT dynamics at 72 h AEL. In contrast, we

find a 4.0-fold decrease in the percentage of anterograde comets (Fig. 2.7E-F, H).

In control animals, 8.3% of the comets move anterogradely, while only 2.1% of the comets in foxO nulls are anterograde. Together, these data indicate that FoxO promotes overall MT polymerization (anterograde and retrograde) at 96 h AEL, while it is necessary for normal levels of anterograde MT polymerization at both

72 h and 96 h AEL.

2.3.7 FoxO drives anterograde microtubule polymerization

While the loss of plus-end-out, anterograde polymerizing, MTs in foxO mutant dendrites was unexpected, it is consistent with recent studies that have revealed a link between plus-end-out MTs and dendrite branching (Ori-McKenney et al.,

2012; Yalgin et al., 2015). These studies demonstrate that anterograde polymerizing MTs are important for nascent dendrite branch growth and/or stability. Does decreased dendrite branching in foxO nulls result, at least in part, from reduced anterograde MT polymerization? To investigate whether FoxO regulates anterograde MT polymerization to promote dendrite branching, we investigated the effect of FoxO overexpression on MT polymerization. Because

47 FoxO overexpression drives dendrite branching (Fig. 2.5), we predicted that anterograde MT polymerization would be increased in this background.

To test this hypothesis, we investigated whether FoxO overexpression in the class IV ddaC cell alters MT dynamics at 96 h AEL. We do not detect a difference in total comet number between foxO overexpressing neurons and controls at 96 h

AEL (Fig. 2.8A-C), indicating that FoxO is not sufficient to alter overall MT dynamics. However, FoxO overexpression results in a 2.8-fold increase in the percentage of anterograde comets at 96 h AEL: 18.4% of comets are anterograde in FoxO overexpressing neurons, relative to 6.7% of comets in controls. (Fig. 2.8A-B, D; Supplemental Movie 2). In wild-type animals, comets in short, nascent branches are more frequently anterograde, while comets in long, main branches are more frequently retrograde (Ori-McKenney et al., 2012). To interrogate the relationship between anterograde comets and branching in FoxO overexpressors, we asked if the excess anterograde comets are found in higher-order branches, or rather in main branches. In controls, 74.5% (n=51) of anterograde comets are in thin, higher-order branches, consistent with the established link between anterograde comets and nascent branches

(Ori-McKenney et al., 2012). Similarly, 79.3% (n=82) of anterograde comets in

FoxO overexpressing neurons are in higher-order branches. Thus, the excess anterograde comets in FoxO overexpressing neurons arise in higher-order branches—and are thus spatially positioned to contribute to increased branching.

Supplementary material related to this article can be found online at http://dx.doi.org/10.1016/j.ydbio.2016.08.018.

We next asked if FoxO overexpression increases the percentage of anterograde MT polymerization at 72 h AEL. Similar to 96 h AEL, we do not detect

48 a difference in total comet number in FoxO overexpressing neurons relative to controls at 72 h AEL (Fig. 2.8E-G). However, FoxO overexpression in ddaC leads to a 2.7-fold increase in the proportion of anterograde comets at 72 h AEL. In

FoxO overexpressing neurons, 19.9% of comets are anterograde, relative to 7.4% of comets in controls (Fig. 2.8E-F, H). Together, these analyses demonstrate that

FoxO is sufficient to promote anterograde polymerization of MTs in dendrites.

2.3.8 FoxO is necessary for proper nociceptive response

Class IV neurons are nociceptive, responding to both noxious heat and strong touch stimuli, and elicit a stereotyped 360 rolling behavior when activated

(Hwang et al., 2007; Tracey et al., 2003). Reduced class IV cell complexity correlates with reduced nociceptive responses (Ferreira et al., 2014; Stewart et al., 2012). We therefore hypothesized that foxO null animals would have impaired responses to noxious touch stimuli. To quantify overall crawling behavior, we recorded the behavior of wandering 3rd instar larvae over a

15-minute period and analyzed total distance traveled. We find that foxO nulls and controls crawl similar distances, indicating that loss of FoxO does not result in a gross deficit in movement (Fig. 2.9A-C). To test for nociception, we calibrated

50 mN Von Frey filaments and stimulated larvae once on hemisegment 4, 5, or 6

(Tracey et al., 2003; Zhong et al., 2010). Animals were scored for whether or not they rolled 360 at least once in response to a single stimulus. We find that control animals respond 90.0% of the time, in line with previous studies (Tracey et al., 2003). In contrast, foxO mutants respond only 56.7% of the time (Fig.

2.9D). Animals otherwise paused upon stimulation, similar to reports of light touch sensation. Therefore, reduced dendrite complexity seen in foxO nulls

49 correlates with a reduced nociceptive response.

2.4 Discussion

Here we demonstrate a role for FoxO in arborization of sensory neuron dendrites during development. Both loss-of-function and overexpression analyses indicate that FoxO broadly promotes dendrite branching in da neurons. A time-lapse analysis provides insight into FoxO function and indicates that FoxO promotes initiation and stabilization of new branches. Moreover, we find that FoxO limits the distribution of Futsch/MAP1B in multiple classes of da neuron dendrites, indicating an expansion of the stable MT pool. Moreover, analysis of dynamic

MTs in foxO LOF and overexpressing neurons indicates that FoxO promotes anterograde polymerization of MTs. Lastly, loss of FoxO leads to a reduced larval nociceptive response, arguing that FoxO is also necessary for function of class IV da neurons. We conclude that FoxO is necessary and sufficient for dendrite branching, at least in part, by promoting anterograde MT polymerization.

Anterograde MT growth and dendrite branching

Mature da neurons contain largely minus-end-out, retrograde polymerizing, MTs

(Hill et al., 2012; Rolls and Jegla, 2015; Stone et al., 2008). In contrast, during development as da dendrites grow and branch, their MTs have mixed polarity (Hill et al., 2012). The presence of anterograde polymerizing MTs during dendrite extension suggests that this MT population is linked to growth/branching.

Consistent with this hypothesis, differences in MT polarity are observed in different types of branches in class IV neurons (Ori-McKenney et al., 2012).

50 These authors found that longer, established branches have mostly retrograde comets, while shorter, nascent branches have mostly anterograde comets.

Moreover, following dendrite severing, nascent dendrites initially contain both retrograde and anterograde polymerizing MTs, which resolves to the mature pattern of minus-end-out (Song et al., 2012; Stone et al., 2014).

Further analyses support a direct link between anterograde polymerizing MTs and dendrite branching. Ori-McKenney et al. (2012) find a striking difference between stable and retracting terminal branches with respect to anterograde MT growth. They demonstrate that the majority of stable branches contain anterograde EB1 comets, while the majority of retracting branches do not contain comets. If anterograde MT polymerization is involved in branching, then one might expect the relatively simple class I cells to have a mechanism to limit anterograde polymerization. Indeed, Yalgin et al. (2015) have recently demonstrated that the class I-specific transcription factor Abrupt limits branching in class I neurons by promoting Centrosomin expression. They find that

Centrosomin represses dendrite branching by orienting MT nucleation to repress anterograde polymerization. Centrosomin is proposed to execute this function by tethering MT nucleation events to one face of Golgi outposts and biasing the direction of MT growth away from dendrite tips.

In the present study, we demonstrate that FoxO promotes branching in all classes of da neurons. We also find that FoxO is necessary and sufficient for anterograde MT polymerization. Based on the established role of anterograde polymerizing MTs in branching, we propose that FoxO drives branching, at least in part, by regulating MT orientation. Moreover, the link between MT polarity and dendrite maturity suggests that by stimulating plus-end-out MTs, FoxO promotes

51 a more immature, dynamic MT environment that is well suited for branching.

Our genetic analyses in foxO LOF and overexpression backgrounds indicate that FoxO drives anterograde MT polymerization. Our results also indicate that this is unlikely to be the only function of FoxO in MT regulation. Several lines of evidence also indicate that FoxO promotes MT dynamics. First, we find that the distribution of Futsch/MAP1B is expanded in dendrites of both class I and class

IV neurons in foxO nulls. Second, the reduced length and branching observed in ddaC in foxO nulls are partially suppressed by removing one copy of futsch.

Third, we find an approximate two-fold reduction in EB1 comets in foxO nulls at

96 h AEL. These LOF analyses indicate that foxO plays a role in regulating overall dynamics.

Moreover, it will be important to determine if the actin cytoskeleton is altered in foxO LOF or overexpression backgrounds. The ectopic short, spiky branches observed with FoxO overexpression are Futsch-negative and resemble the actin-rich branches in class III dendrites (Jinushi-Nakao et al., 2007; Nagel et al.,

2012). We propose that the presence of these actin-rich branches in FoxO overexpressing neurons is indirectly caused by alterations to the MT network. It is alternately possible that FoxO more directly regulates the actin cytoskeleton.

Identification of FoxO’s transcriptional targets will clarify the mechanism(s) through which FoxO controls these interrelated cytoskeletal components.

FoxOs in neurodevelopment

FoxO family members have recently emerged as key regulators of neuronal processes such as neural stem cell homeostasis, neuronal polarity, neurite outgrowth, synaptic function, and memory consolidation (Christensen et al.,

52 2011; de la Torre-Ubieta et al., 2010; Paik et al., 2009; Renault et al., 2009; Salih et al., 2012). Of particular interest, simultaneous RNAi-mediated knockdown of

FoxO1, 3 and 6 interferes with neuronal polarization in hippocampal and cerebellar neurons (de la Torre-Ubieta et al., 2010). Pak1, a kinase known to regulate neuronal MT dynamics and neuronal polarization (Jacobs et al., 2007), was shown to be a critical for this function of FoxO. Based on this link between mammalian FoxOs and Pak1, we tested if Pak1 might be a FoxO effector in da neurons. However, RNAi-mediated knockdown of Pak1 does not yield phenotypes consistent with an essential role for Pak1 downstream of FoxO in regulating da neuron arborization (JCS and HTB, data not shown).

FoxO family members serve key functions in neuronal development and function subsequent to initial polarization. Knockdown of mammalian FoxOs after neurons have polarized reveals defects in axon and dendrite outgrowth in vitro

(Christensen et al., 2011). Arguing that FoxO function in neurite outgrowth is evolutionarily conserved, the C. elegans foxO homolog, daf-16, is likewise required for axon outgrowth of the AIY interneuron (Christensen et al., 2011). We previously examined the role of Drosophila FoxO in motoneurons and found that

FoxO is required for proper MT architecture in presynaptic terminals at the NMJ, though we did not find defects in initial axon outgrowth or guidance

(Nechipurenko and Broihier, 2012). Genetic and molecular analyses argued that

MT stability at the NMJ is enhanced in foxO LOF and attenuated in foxO overexpressing neurons. These findings are in good agreement with the present study and together indicate that Drosophila FoxO limits MT stability in both axons and dendrites in multiple neuronal populations.

Loss of mammalian FoxO6 results in decreased spine density in hippocampal

53 neurons both in vitro and in vivo (Salih et al., 2012). Spines are actin-rich protrusions on dendrites that house postsynaptic components of excitatory synapses in the mammalian CNS. Intriguingly, MT entry into spines is linked to aspects of spine development and function, including density and morphology

(Gu et al., 2008; Hu et al., 2008; Jaworski et al., 2009), raising the possibility that aberrant MT behavior could underlie spine defects in FoxO6 mutants. It will be important to investigate whether loss of mammalian FoxO family members results in defects in neuronal MT dynamics or polarity.

The pathways upstream of FoxO proteins in neurons are not well understood.

FoxOs can be regulated by post-translational modifications including phosphorylation, acetylation, and ubiquitylation, which together direct their subcellular localization and transcriptional activity (Calnan and Brunet, 2008). Akt kinase phosphorylates FoxO and inhibits its transcriptional activity by retaining it in the cytoplasm (Huang and Tindall, 2007). Thus, if an Akt-FoxO axis is central to FoxO function in da neurons, loss of Akt is predicted to result in increased branching similar to overexpression of FoxO (Fig. 2.5). However, loss of Akt results in strongly reduced dendrite growth and branching (Parrish et al., 2009), suggesting that Akt is not a critical regulator of FoxO function in da neuron dendrites. Thus, upstream regulation of FoxO in da neurons is likely distinct from

FoxO regulation in motoneurons, which appears to depend on Akt-dependent inhibition (Nechipurenko and Broihier, 2012).

In the future, it will be important to define effector(s) of FoxO in da neurons.

FoxO can now be considered a member of a small group of transcription factors, including Abrupt, Dar1, and Knot, that regulate dendrite morphology via MT dynamics in da neurons (Jinushi-Nakao et al., 2007; Li et al., 2004; Sugimura

54 et al., 2004; Ye et al., 2011). Critical transcriptional targets of Abrupt, Dar1, and

Knot have recently been identified that mediate the MT regulatory functions of these proteins (Jinushi-Nakao et al., 2007; Wang et al., 2015; Yalgin et al., 2015;

Ye et al., 2011). Of these transcription factors, Knot is most similar to FoxO in that it drives branching (Jinushi-Nakao et al., 2007). However, FoxO is expressed in, and promotes branching of, all da neuron classes, These results suggest that

FoxO does not differentially regulate the neuronal subtype fate of a particular da neuron class, but rather promotes branching of all da neuron subtypes.

Based on the reciprocal changes we observe in the proportion of plus-end-out

MTs in foxO LOF and overexpressing neurons, we predict that FoxO’s downstream transcriptional targets include proteins regulating MT polarity in dendrites. Possible targets include Kinesin-2 subunits, EB1, and APC, as

RNAi-mediated knockdown of these proteins results in shifts in MT polarity similar to phenotypes described here for FoxO overexpression (Mattie et al., 2010).

Further investigation of the molecular mechanism by which FoxO directs MT polarity will elucidate cell-intrinsic programs controlling dendrite branching during neurodevelopment.

2.5 Materials and methods

Fly stocks, alleles, and driver lines

We used 477GAL4, UAS-mCD8-GFP; 477-Gal4, UAS-mCD8RFP; 477-Gal4,

UAS-EB1-GFP; and 2-21-Gal4, UAS-mCD8-GFP for visualization of class IV morphology, class IV EB1 comets, and class I morphology (gifts from Melissa

Rolls [Pennsylvania State University, University Park, PA, US]). We used foxOD94

55 as a foxO genetic null allele (a gift from Linda Partridge [University College

London, London, England, UK]). For MARCM, we used hsFLP, 109(2)80-Gal4,

UAS-mCD8-GFP, and FRT82b, TubP-Gal80 from the Bloomington Stock Center

(BDSC 8862, BDSC 8768, BDSC 5135). For visualization of classes I-III we used

C161-Gal4 (BDSC 27893). For overexpression of FoxO, we used UAS-FoxOWT

(listed as FoxO WT#1; a gift from Robert Tjian [University of California, Berkeley,

Berkeley, CA, US]) in class I and II and UAS-FoxOWTf19-5 (listed as FoxO WT#2; a gift from Marc Tatar [Brown University, Providence, RI, US]) in class IV. For control RNAi we used Vienna Drosophila RNAi Center lines 25271

(gamma-tubulin 37C RNAi, listed as control RNAi#1) and 33320 (Rtnl2 RNAi, listed as control RNAi#2) (Chen et al., 2012; Hill et al., 2012). For FoxO/Futsch interaction, we used Oregon R, futschk68 ;a gift from Christian Klämbt (University of Muenster, Muenster, Germany; Hummel et al., 2000), futschk68;; foxOD94, and ppk-CD4-GFP (BDSC 35842). For this study, we generated recombinants

FRT82b, foxOD94 from FRT82b, Sb (a gift from Jocelyn McDonald [Kansas State

University, Manhattan, KS, US]), and C161-Gal4, foxOD94 from stocks listed above. Recombinants were generated via standard genetic techniques.

Aging, imaging, and analysis

Size and age of larvae were controlled by length. Classification of h AEL was determined by the rostral to caudal length of larvae. Around 2 mm larvae were counted as 72 h AEL, or early 3rd instar larvae. Around 3 mm larvae were counted as 96 h AEL. Around 4 mm larvae were counted as 120 h AEL, or late

3rd instar larvae.

Images were taken using either a Zeiss Axioplan 2 widefield microscope with

56 Colibri.2 LED light system, a Zeiss LSM 510 confocal system, or a Leica SP8 confocal system. For native CD8-GFP and CD4-GFP fluorescence, larvae were

flattened beneath a coverslip in 60% glycerol with pressure applied to the caudal end of the animal, such that the guts were pressed out to reduce background

fluorescence. For stained preps, larval filets were fixed in 4% PFA for approximately 25 min, then stained with chicken anti-GFP primary antibody

(Abcam, ab15769) at 1:1000 and labeled with goat anti-chicken 488 secondary antibody at 1:750 (Invitrogen, A-11039). Widefield or confocal z-stacks were converted to 2D projections with Zeiss extended focus and maximum projection, respectively. Projections of larger cells that required multiple image fields were stitched together with either Adobe Photoshop, or the ImageJ FIJI plugins

Pairwise Stitching or Grid/Collection Stitching (Preibisch et al., 2009). For clarity in figures, background fluorescence outside the plane of focus of marked cells was at times reduced. Images were traced with a Wacom graphics pad and either

Adobe Illustrator or ImageJ. Traces were then analyzed for branch points and length in NeuronStudio (Wearne et al., 2005), while Sholl was analyzed with the

FIJI analysis tool Sholl Analysis (Ferreira et al., 2014). Classes with smaller cells were analyzed for length in ImageJ, and branch points were counted in ImageJ with the Cell Counter plugin. Overlays and analysis of 250 µm2 squares to determine internal coverage of class IV cells was accomplished with an ImageJ macro of our own design. The macro defines a grid of Regions of Interest (ROI) based on a defined selection around the cell. The macro then checks each ROI for the presence of the neuron (displayed in green) and tallies it. Afterwards, the macro checks each ROI for the absence of a neuron (displayed in magenta), but does not count ROI outside the defined selection around the cell (displayed in

57 white). The macro will be available at http://imagej.net/User:JamesSears.

For clonal analysis, we followed established heat shock protocols and timings

(Grueber et al., 2002; Shrestha and Grueber, 2011). Briefly, crosses were allowed to lay over a 3-h period onto molasses filled, yeast covered caps at 25 C.

Caps were removed and placed at 25 C for an additional 4-5 h. Each cap was then sealed onto another cap with Parafilm, then placed under a floating foam device and sufficient weight to submerge the caps in a 38 C water bath for a one hour period of heat shock. Caps were removed from the water bath and then returned to 25 C until larvae had developed to the desired stage.

For time-lapse imaging, 96 h AEL larvae were measured and mounted, intact, in 60% glycerol under a coverslip. To prevent damage to the animals, layers of tape were placed between the slide and the coverslip as spacers. Native GFP

fluorescence in class IV ddaC cells was imaged with a Zeiss LSM 510 confocal system. Then the larvae were washed in 1 x PBS, dried, and allowed to roam freely with food for two hours until the next imaging period.

For EB1-GFP comet imaging, 72 h and 96 h AEL larvae were measured and mounted, intact, in 80% glycerol under a coverslip. To prevent damage to the animals, layers of tape were placed between the slide and the coverslip as spacers. Extra care was taken with 72 h AEL larvae, whose smaller size and shape make imaging throughout the ddaC arbor more challenging. Comets were imaged on a Zeiss Axioplan 2 with a Colibri.2 LED light system, a 100x 1.3 NA oil immersion objective, an 800 ms exposure time, and 25% light strength at

2-second intervals. Length in focus was determined in imageJ, and comet direction was counted with the ImageJ plugin Cell Counter. Comets were counted in both higher-order and main branches. Kymographs were generated with the

58 ImageJ FIJI plugin KymoResliceWide.

For antibody staining for Futsch and FoxO, larval filets were fixed in 4% PFA for 25 min, dorsal muscles were removed, and preparations were stained. To mark neuronal membranes with HRP, fluorescently conjugated goat anti-HRP-594 was used at 1:500 (Jackson ImmunoResearch Laboratories,

Inc.,123-585-021). To stain for FoxO, guinea pig anti-FoxO (Nechipurenko and

Broihier, 2012) was used at 1:20 with goat anti-guinea pig 488 secondary antibody at 1:300 (Invitrogen, A-11073). To stain for Futsch, the primary antibody

22C10 (Developmental Studies Hybridoma Bank) was used at 1:8 or 1:10 depending on the aliquot, with goat anti-mouse 568 secondary antibody at 1:300

(Invitrogen, A-11031). For continuous Futsch staining, the first 20 µm of 2 collaterals was assessed for any breaks in Futsch staining.

Behavior

For behavior we modified a larval learning paradigm in order to assess free movement of animals (Gerber et al., 2013). At least one day prior to imaging,

Petri dishes were prepared, each with a thin layer of 1% agarose. Wandering third instar larvae were placed in the middle of the Petri dishes, given 10 min to acclimate, then recorded for 15 min. Movies were converted to 1 Hz, and then analyzed with the FIJI plugin Manual Tracking. For nociceptive responses, we calibrated 30 mN and 50 mN von Frey filaments from 6 lb test, 0.23 mm diameter,

Omniflex monofilament fishing line (Tracey et al., 2003; Zhong et al., 2010).

Larvae were stimulated with a single, quick depression on the dorsal side, until the von Frey filament visibly bent. If at least one 360 roll was observed, it was counted as a positive response. Each larva was stimulated only one time, and if a

59 stimulus glanced the animal, it was not counted.

Statistical analysis

Statistical analysis was performed in GraphPad Prism. When two groups were compared, unpaired, two-tailed t-tests with Welch’s correction were performed.

When more than two groups were compared, one-way ANOVA was performed with multiple comparisons between each group with Tukey’s correction. For categorical data, two-tailed Fisher’s exact tests were performed. For significance,

* denotes p < 0.05, ** denotes P < 0.01, and *** denotes p < 0.001. For trending,

# denotes p < 0.10. No significant difference is n.s.

Acknowledgments

We are grateful to Melissa Rolls (Pennsylvania State University, University Park,

PA, US), for her support and guidance. We thank Melissa Rolls, Jocelyn

McDonald (Kansas State University, Manhattan, KS, US), Linda Partridge

(University College London, London, England, UK), Robert Tjian (University of

California, Berkeley, Berkeley, CA, US), the Bloomington Drosophila Stock

Center, and the Vienna Drosophila RNAi Center for fly strains. We thank the

Developmental Studies Hybridoma Bank for antibodies, the ImageJ community for insight and inspiration, Nan Liu and Priya Tumuluru for technical assistance, the Case Western Reserve University Neurosciences/Genetics Imaging facility for providing confocal microscopes and support, and members of the Broihier lab for helpful discussion and comments on the manuscript. This work was supported by

NIH T32AG00271 to JCS and NIH R56NS055245 and R21NS090369 to HTB.

60 2.6 Figures

FigureFigure 2.11

72 h AEL control foxOΔ94 E F A B

C D control foxOΔ94 s t d 500 ) G 0.25 8 *** mm

400 vere h poin

( 0.20 o c 6 c h n *

t 300 t 0.15 ra

** ng

b 4 e e 200 l

t 0.10 i e ion no r t t i r 100 r 2 nd 0.05 e nd opo e

d 8 6 8 6 8 6 r

0 d 0 0.00 p # control foxOΔ94 control foxOΔ94 control foxOΔ94 120 h AEL control foxOΔ94 H I

J 800 L M s t e

t 600 i r *** nd h poin 400 e c n

d N # ra 200 b

6 8 d 0.4 0 *** control foxOΔ94 vere 0.3 K o c )

20 t 0.2 mm ( 15 h ion no t t *** r 0.1 ng 10 e opo l r

e 6 8 p t i 5 0.0 r control foxOΔ94 nd 6 8 e 0 d control foxOΔ94 control foxOΔ94

61 Fig. 2.1. FoxO regulates class IV dendrite morphology. (A, B, H, I)

Representative z-projections of class IV ddaC neurons marked with mCD8-GFP driven by 477-GAL4 at the indicated larval ages and backgrounds. (C)

Quantification of dendrite branch point numbers at 72 h AEL in control animals:

390.6 32.8, n=8 cells; foxOD94 animals: 209.5 30.7, n=6 cells. (D) ± ± Quantification of dendrite length at 72 h AEL in control animals: 6.78 0.48 mm, ± n=8; foxOD94 animals: 4.91 0.50 mm, n=6 cells. (E, F, L, M) Representative ± analysis of internal coverage of ddaC cells with 250 µm2 squares of the indicated ages and backgrounds. Green squares mark areas covered by the dendritic arbor and soma, while magenta squares mark areas not covered. (G) Quantification of the proportion of squares not covered by the dendrite and soma at 72 h AEL in control animals: 0.10 0.01, n=8 cells; foxOD94 animals: 0.21 0.01, n=6 cells. ± ± (J) Quantification of dendrite branch point numbers at 120 h AEL in control animals: 678.5 26.2, n=6 cells; foxOD94 animals: 453.3 35.0, n=8 cells. (K) ± ± Quantification of dendrite length at 120 h AEL in control animals: 15.48 0.44 ± mm, n=6 cells; foxOD94 animals: 11.04 0.54 mm, n=8 cells. (N) Quantification of ± the proportion of squares not covered by the dendrite and soma at 120 h AEL in control animals: 0.19 0.02, n=6 cells; foxOD94 animals: 0.33 0.01, n=8 cells. ± ± Scale bars: 50 µm. Error bars are mean s.e.m., *, p < 0.05, **, p < 0.01, ***, p < ± 0.001.

62 FigureFigure 2.22

A E control clone

control clone B F

clone 94 Δ foxO

foxOΔ94 clone C D G d ) 0.4 800 20 mm vere ( *

o 0.3 h

600 c t 15 * t

** ng

400 e 0.2 l 10 ion no t 200 5 r 0.1 opo

6 5 r 6 5 6 5 dendrite 0 0 p 0.0 control foxOΔ94 control foxOΔ94 control foxOΔ94 # dendrite branch points clones clones clones clones clones clones

63 Fig. 2.2. FoxO acts cell-autonomously to regulate class IV dendrite morphology.

(A-B) Representative z-projections of class IV ddaC MARCM clones at 120 h AEL of the indicated backgrounds marked with mCD8-GFP driven by 109(2)80-GAL4.

(C) Quantification of dendrite branch point numbers in control clones: 598.7 ± 29.5, n=6 cells; foxOD94 clones: 420.8 42.5, n=5 cells. (D) Quantification of ± dendrite length in control clones: 16.62 0.73 mm, n=6 cells; foxOD94 clones: ± 12.56 1.28 mm, n=5 cells. (E-F) Representative analysis of internal coverage ± of ddaC cells with 250 µm2 squares of the indicated backgrounds. Green squares mark areas covered by the dendritic arbor and soma, while magenta squares mark areas not covered. (G) Quantification of the proportion of squares not covered by the dendrite and soma in control clones: 0.17 0.02, n=6 cells; ± foxOD94 clones: 0.27 0.03, n=5 cells. Scale bars: 50 µm. Error bars are mean ± s.e.m., *, p < 0.05, **, p < 0.01. ±

64 Figure 3 Figure 2.3

class IV class I class II class III A B C D control 94 Δ

foxO FOXO HRP FOXO class I ddaE class I vpda control foxOΔ94 control foxOΔ94 E F I J

G H )

) K L 2.0 2.0 25 mm ( mm 40 ( s 1.5 t h ** t

20 h ** 1.5 e t t

*** i 30 r *** ng

15 ng 1.0 e

e 1.0 l nd h poin

l 20 e e c

10 e t i t n # dendrite i 0.5 d r r 0.5 10 branch points 5 # ra nd nd 10 10 b 7 8 7 8 10 10 e 0 e 0.0 0 0.0 d control foxOΔ94 d control foxOΔ94 control foxOΔ94 control foxOΔ94 class II ldaA class III vdaD control foxOΔ94 control foxOΔ94 M N Q R )

S T ) 150 4 600 6 O P # s mm s t mm t (

3 ( e e t h t i t h i 100 4 r 400 t r **

ng *** nd 2 ng nd h poin *** h poin e e e c c e l l n n e d 200 d 50 2 t e i t 1 # # i ra r ra r b b nd

11 11 11 11 10 10 nd 10 10 0 e 0 0 0 e 94 Δ94 d Δ94 Δ94 Δ control foxO control foxO control foxO d control foxO

65 Fig 2.3. FoxO is expressed in da neurons and regulates class I-III dendrite morphology. (A-D) FoxO staining (green) of FoxO positive controls and foxOD94 class I-IV cells, counterstained for HRP (red). Scale bar: 5 µm. (E, F, I, J, M, N)

Representative z-projections of class I and II cells of the indicated cell type and backgrounds, marked with mCD8-GFP driven by C161-GAL4. (G) Quantification of branch point numbers in class I ddaE cells in control animals: 20.6 0.6, n=10 ± cells; foxOD94 animals: 16.5 0.6, n = 10 cells. (H) Quantification of dendrite ± length in class I ddaE in control animals: 1.55 0.04 mm, n = 10 cells; foxOD94 ± animals: 1.31 0.06 mm, n = 10 cells. (K) Quantification of branch point ± numbers in class I vpda cells in control animals: 36.6 1.3, n=7 cells; foxOD94 ± animals: 24.8 1.0, n=8 cells. (L) Quantification of dendrite length in class I vpda ± in control animals: 1.62 0.07 mm, n=7 cells; foxOD94 animals: 1.32 0.03 mm, ± ± n=8 cells. (O) Quantification of branch point numbers in class II ldaA cells in control animals: 105.4 7.2, n=11 cells; foxOD94 animals: 63.2 3.2, n=11 cells. ± ± (P) Quantification of dendrite length in class II ldaA in control animals: 2.76 ± 0.10 mm, n=11 cells; foxOD94 animals: 1.81 0.04 mm, n=11 cells. (Q-R) ± Representative traces of class III vdaD cells of the indicated backgrounds, marked with mCD8-GFP driven by C161-GAL4. (S) Quantification of branch point numbers in class III vdaD cells in control animals: 458.7 29.1, n=10 cells; ± foxOD94 animals: 341.4 10.1, n=10 cells. (T) Quantification of dendrite length in ± class III vdaD in control animals: 5.12 0.26 mm, n=10 cells; foxOD94 animals: ± 4.57 0.14 mm, n=10 cells. Scale bars in E, I, M, and Q: 50 µm. Error bars are ± mean s.e.m., #, p < 0.1, **, p < 0.01, ***, p < 0.001. ±

66 FigureFigure 2.44

control foxOΔ94 A B 0 hours

C D 2 hours

lost terminal branches after two hours lost terminal branches gained terminal branches after two hours gained terminal branches 1.2 E F G H *

d 1.0 l e t 25 a in s

40 l branches a in

a 0.8 lo

g 60

20 n i

30 erm t 0.6 *

15 erm

40 t in

f 20 e *** 10 0.4 ng branches l branches branches a l 20 a h

a 10 * 0.2 in

c 5

in t

8 8 e 8 8 8 8 8 8 n 0.0 erm 0 0 proportion o 0 t erm Δ94 Δ94 Δ94 t control foxOΔ94 control foxO control foxO control foxO

67 Fig. 2.4. FoxO promotes initiation and stabilization of new branches. (A-D)

Representative images of class IV ddaC cells within intact, 96 h AEL animals, marked with mCD8-GFP driven by 477-GAL4, in the indicated backgrounds and time points. Filled, magenta arrows indicate lost terminal branches after a two-hour period, while notched, green arrows indicate new terminal branches. (E)

Quantification of gained branch points after a two-hour period, controls: 46.6 ± 3.6, n=8 cells; foxOD94 animals: 24.4 2.9, n=8 cells. (F) Quantification of lost ± branch point after a two-hour period, controls: 27.4 3.0, n=8; foxOD94 animals: ± 21.8 3.6, n=8 cells. (G) Quantification of net branches after a two-hour period, ± controls: 19.3 5.3, n=8 cells; foxOD94 animals: 2.6 1.8, n=8 cells. (H) ± ± Quantification of the proportion of gained branches compared with lost branches over a two-hour period, gained branches in controls: 0.63 0.04, n=8 cells; lost ± branches in controls: 0.37 0.04, n=8 cells; gained branches in foxOD94 animals: ± 0.54 0.02, n=8 cells; lost branches in foxOD94 animals: 0.46 0.02, n=8 cells. ± ± Scale bar: 50 µm. Error bars are mean s.e.m., *, p < 0.05, ***, p < 0.001. ±

68 Figure 2.5 Figure 5 class I ddaE class I vpda control FoxO overexpression control FoxO overexpression A B C D

E vpda F s t 120 ** 2.0 vpda ddaE ** ** h poin 90 ddaE

c 1.5

n *** ra

b 60 1.0 e t i r 30 0.5 nd e

d 6 7 7 7

6 7 7 7 dendrite length (mm) # 0 0.0 control FoxO control FoxO control FoxO control FoxO overexpression overexpression overexpression overexpression

class IV ddaC I s G t 1000 800 * h poin c n 600 ra b

e 400 t i r control

nd 200 e 6 7 d 0 # control FoxO overexpression J H ) 20 mm ( 15 h *** t

ng 10 e l e t i

r 5

nd 6 7 e 0 d control FoxO

FoxO overexpression overexpression

69 Fig. 2.5. FoxO is sufficient to promote branch formation. (A-D) Representative z-projections of class I ddaE and vpda cells of the indicated backgrounds, marked with mCD8-GFP driven by 2-21-GAL4. (E) Quantification of class I branch point numbers in animals expressing control RNAi #2 in ddaE: 22.7 1.6, n=6 cells; ± control RNAi #2 in vpda: 39.7 3.1, n=7 cells; FoxO WT #1 in ddaE: 56.9 5.3, ± ± n=7 cells; FoxO WT #1 in vpda: 90.3 11.4, n=7 cells. (F) Quantification of class ± I dendrite length in animals expressing control RNAi #2 in ddaE: 1.40 0.04 mm, ± n=6 cells; control RNAi #2 in vpda: 1.52 0.02 mm, n=7 cells; FoxO WT #1 in ± ddaE: 1.11 0.07 mm, n=7 cells; FoxO WT #1 in vpda: 1.27 0.05 mm, n=7 ± ± cells. (G-H) Representative z-projections of class IV ddaC cells of the indicated backgrounds, marked with mCD8-GFP driven by 477-GAL4. Magenta boxes in A and B are magnified in side panels. (I) Quantification of class IV ddaC branch point numbers in animals expressing control RNAi #1: 649.0 28.6, n=6 cells; ± FoxO WT #2: 749.7 35.4, n=7 cells. (J) Quantification of class IV ddaC ± dendrite length in animals expressing control RNAi #1: 17.12 0.37 mm, n=6 ± cells; FoxO WT #2: 13.08 0.61 mm, n=7 cells. Scale bars: 50 µm. Error bars ± are mean s.e.m., *, p < 0.05, **, p < 0.01, ***, p < 0.001. ±

70 FigureFigure 6 2.6

membrane Futsch merge membrane Futsch merge C A B

0.8 class I ddaE **

94 0.6 Δ 2˚ collaterals

0.4 on control foxO i t

r 0.2 Futsch staining with continuous

opo 108 102 r 0.0 p control foxOΔ94

D E F class I ddaE class I ddaE ve i

t 1.0 i s 0 µm

2 0.8 >

h po ***

es 0.6 sc h t c

n 0.4 control ra ion Fu t l b 0.2 r a

in 0.0 77 36 opo r control FoxO p FoxO overexpression erm t overexpression

membrane Futsch merge G

control I s e

h class IV ddaC c

n 0.25 ra ** b 0.20 ve i t i H s 0.15 h po 0.10 sc t class IV ddaC 0.05 ion Fu t

r 624 419 0.00 Δ94 opo 94 control foxO r Δ p foxO

71 Fig. 2.6. FoxO limits the distribution of stable microtubules in dendrites. (A, B, D,

E) Representative z-projections of class I ddaE cells of the indicated backgrounds, marked with mCD8-GFP, in green, driven by C161-Gal4 (A-B) or

2-21-GAL4 (D-E), counterstained for Futsch, in magenta. Arrows in A and B mark examples of continuous Futsch staining at 2 collaterals, while arrows in D and E mark examples of terminal branches with or without Futsch staining. (C)

Quantification of the proportion of 2 collaterals with continuous Futsch staining in control animals: 37.0% of 108 collaterals from 9 cells; in foxOD94 animals: 58.8% of 102 collaterals from 11 cells. (F) Quantification of the proportion of Futsch positive, greater than 20 µm terminal branches in animals expressing control

RNAi #1: 89.6% of 77 branches from 6 cells; FoxO WT #1: 61.1% of 36 branches from 6 cells. (G-H) Representative z-projections of class IV ddaC cells of the indicated backgrounds, marked with mCD8-GFP, in green, driven by 477-GAL4, counterstained for Futsch, in magenta. Arrows in G and H mark Futsch staining in terminal or near terminal branches. (I) Quantification the proportion of Futsch positive branches in control animals: 13.0% of 624 branches from 6 cells; foxOD94 animals: 20.5% of 419 branches from 7 cells. Scale bars: 10 µm. Comparisons made with two-tailed Fisher’s exact tests, **, p < 0.01, ***, p < 0.001.

72 Figure 7 2.7

96 h AEL 72 h AEL A control E control

cell body

B foxOΔ94 F foxOΔ94

C 96 h AEL D 96 h AEL G 72 h AEL H 72 h AEL

e

s s 0.10 e d u u d 40 n.s.

c 60 c ra o o ra 0.06 f f 0.08 og og 30 s in in s t er t er t 0.06

40 t

0.04 n n a me mm mm a me 20

* o o 0.04 c c

ion ion 20 t per per t

0.02 r *

r 10 s ** s

t t 0.02 219 opo

opo 8 12 r

me 11 16 209 me 168 142 r 0

0 0.00 p 0.00 o o Δ94 p 94 Δ94 94 c control foxO control foxOΔ c control foxO control foxOΔ

73 Fig. 2.7. FoxO is necessary for anterograde polymerization and dynamics of microtubules. (A, B, E, F) Representative kymographs from ddaC cells from live, intact larvae of the indicated ages and backgrounds expressing EB1-GFP driven by 477-GAL4. Retrograde EB1 comets move down and to the left, anterograde comets down and to the right (purple arrowheads). (C) Quantification of comets per mm in focus at 96 h AEL in control animals: 45.4 7.2, n=11 movies; foxOD94 ± animals: 22.5 3.5, n=16 movies. (D) Quantification of the proportion of ± anterograde comets at 96 h AEL in control animals: 10 of 209, 4.8%; foxOD94 animals: 1 of 219, 0.5%. (G) Quantification of EB1 comets per mm in focus at 72 h AEL in control animals: 30.4 2.6, n=8 movies; foxOD94 animals: 33.3 3.9, ± ± n=12 movies. (H) Quantification of the proportion of anterograde comets at 72 h

AEL in control animals: 14 of 168, 8.3%; foxOD94 animals: 3 of 142, 2.1%. Vertical scale bar: 20 s; horizontal scale bar: 5 µm. Comparisons in D and H made with two-tailed Fisher’s exact tests. Error bars are mean s.e.m., n.s., not ± significantly different; *, p < 0.05, **, p < 0.01.

74 Figure 8 Figure 2.8

96 h AEL 72 h AEL A control E control

cell body

B FoxO overexpression F FoxO overexpression

C D G H 96 h AEL 96 h AEL 72 h AEL 72 h AEL

s 0.25 s s 0.20 s t u n.s.

80 u *** t e c c n.s.

o 60 *** o f m 0.20 f

me

o 0.15 60 o c in on in c

i

ion t

e 0.15 t r e

40 r d d mm a 0.10 mm 40

r ra

opo 0.10 opo er r er r og og p r p p p 20 e s 20 0.05 s t er t

t 0.05 t n n a a me

31 18 823 488 me 24 31 367 607

o 0 0.00 0.00 o 0 c control FoxO O/E control FoxO O/E c control FoxO O/E control FoxO O/E

75 Fig. 2.8. FoxO drives anterograde microtubule polymerization. (A, B, E, F)

Representative kymographs from ddaC cells from live, intact larvae of the indicated ages and backgrounds expressing EB1-GFP driven by 477-GAL4.

Retrograde EB1 comets move down and to the left, anterograde comets down and to the right (purple arrowheads). (C) Quantification of comets per mm in focus at 96 h AEL in animals expressing control RNAi #1: 63.4 6.0, n=31 ± movies; FoxO WT #2: 65.3 8.1, n=18 movies. (D) Quantification of the ± proportion of anterograde comets at 96 h AEL in animals expressing control RNAi

#1: 55 of 823, 6.7%; FoxO WT #2: 90 of 488, 18.4%. (G) Quantification of comets per mm in focus at 72 h AEL in animals expressing control RNAi #1: 51.7

4.0, n=24 movies; FoxO WT #2: 52.4 3.8, n=31 movies. (H) Quantification of ± ± the proportion of anterograde comets at 72 h AEL in animals expressing control

RNAi #1: 27 of 367, 7.4%; FoxO WT #2: 121 of 607, 19.9%. Vertical scale bar:

20 s; horizontal scale bar: 5 µm. Comparisons in D and H made with two-tailed

Fisher’s exact tests. Error bars are mean s.e.m., n.s., not significantly different; ± ***, p < 0.001.

76 Figure 9 Figure 2.9 A B

control foxOΔ94 C D n

wandering 3rd instar io 50 mN stimulus es t t 60 r nu n.s. 1.0 i opo r m

p 0.8 15 se

r 40 0.6 ** ve pon o

d res

0.4 e 20 ll ve i t 0.2 p ave r t

ce 30 8 8 i 40

0 c 0.0 m

c control foxOΔ94 control foxOΔ94 no

77 Fig. 2.9. FoxO is necessary for proper nociceptive response. (A, B)

Representative traces of wandering 3rd instar larvae of the indicated backgrounds and their movement over a 15-min period. Scale bar: 1 cm. (C)

Quantification of movement over a 15-minute period by controls: 43.0 3.9 cm, ± n=8 animals; foxOD94 animals: 50.5 3.9 cm, n=8 animals. (D) Quantification of ± the proportion of nociceptive response of animals given a 50 mN Von Frey

filament stimulation, analyzed with two-tailed Fisher’s exact test, of control animals: 36 of 40, 90.0%; foxOD94 animals: 17 of 30, 56.7%. Error bars are mean

s.e.m., n.s., not significantly different; **, p < 0.01. ±

78 Figure 2.S1 Figure S1 A 50 72 h AEL

40 control s foxOΔ94 on i

t 30 sec r 20 e t n i

# 10

0 0 100 200 300 distance from cell body (µm) B 80 120 h AEL

control s 60 foxOΔ94 ion t 40 ersec t in

# 20

0 0 200 400 distance from cell body (µm) C 80 120 h AEL control clones s 60 foxOΔ94 clones on i t

sec 40 r e t n i

# 20

0 0 200 400 distance from cell body (µm)

79 Fig. 2.S1. FoxO acts cell-autonomously to regulate class IV dendrite morphology.

(A-C) Class IV ddaC Sholl analysis of controls or control MARCM clones (blue with circles) and foxOD94 animals or foxOD94 MARCM clones (black with squares) at the indicated ages, displaying the numbers of dendrite intersections at 10 µm intervals from the cell body. Cells in A and B are marked with mCD8-GFP driven by 477-GAL4, while cells in C are marked with mCD8-GFP driven by

109(2)80-GAL4. In A, n=8 control cells from 72 h AEL animals, n=6 foxOD94 cells from 72 h AEL animals. In B, n=6 cells from 120 h AEL animals, n=8 foxOD94 cells from 120 h AEL animals. In C, n=6 control clones from 120 h AEL animals, n=5 foxOD94 clones from 120 h AEL animals.

80 Figure S2 Figure 2.S2

class II ldaA 150 ** control FoxO overexpression C s t

e 100 A B t i r nd h poin e c n d 50 # ra b 11 6 0 control FoxO overexpression 4 D ) 3 e t i

mm *** r ( 2 h nd t e d ng

e 1 l 11 6 0 control FoxO overexpression

81 Fig. 2.S2. FoxO is sufficient to promote branch formation in class II neurons.

(A-B) Representative z-projections of class II IdaA cells of the indicated backgrounds marked with mCD8-GFP driven by C161-GAL4. (C) Quantification of the number of dendrite branch points in control animals: 105.4 7.2, n=11 ± cells; in animals expressing FoxO WT #1: 135.3 4.5 mm, n=6 cells. (D) ± Quantification of the total dendrite length in control animals: 2.76 0.10 mm, ± n=11 cells; in animals expressing FoxO WT #1: 2.22 0.09 mm, n=6 cells. Scale ± bar: 50 µm. Error bars are mean s.e.m., **, p < 0.01, ***, p < 0.001. ±

82 FigureFigure 2.S3 S3

A control

E B

s n.s. t 1250 * 1000

h poin * c

n * 750 ** ra 94 Δ

b *** e t

i 500 r foxO nd

e 250 d

# 8 8 6 5 0 control foxOΔ94 futschk68 /+ futschk68 /+ ;;foxOΔ94 F * C 30

) *** ** ** mm 94 ( Δ

h ***

t 20 *** ng foxO e l e /+;; t i

r 10 k68 nd e d

futsch 8 8 6 5 0 control foxOΔ94 futschk68 /+ futschk68 /+ ;;foxOΔ94 D

/+ k68 futsch

83 Fig. 2.S3. Genetic interaction between FoxO and Futsch in class IV. (A-D)

Representative z-stacks of class IV ddaC cells of the indicated background, marked with CD4-GFP driven by the ppk promoter. (E) Quantification of the number of dendrite branch points in control animals: 926.3 37.4, n=8 cells; ± foxOD94 animals: 556.3 37.6, n=8 cells; futschk68/+;;foxOD94 animals: 708.5 ± ± 28.3, n=6 cells; futschk68/+ animals: 736.4 46.5, n=5 cells. (F) Quantification of ± the total dendrite length in control animals: 26.18 0.42 mm, n=8 cells; foxOD94 ± animals: 16.14 0.71 mm, n=8 cells; futschk68/+;;foxOD94 animals: 19.64 0.41 ± ± mm, n=6 cells; futschk68 /+ animals: 22.40 0.82 mm, n=5 cells. Scale bar: 50 ± µm. Error bars are mean s.e.m., n.s., not significantly different; *, p < 0.05, **, p ± < 0.01, ***, p < 0.001.

84 Chapter 3

General Discussion

3.1 FoxO as a Microtubule Regulator

FoxO was recently shown to regulate microtubule dynamics at the neuromuscular junction (Nechipurenko and Broihier, 2012). In motoneurons, FoxO promotes a dynamic microtubule network by limiting microtubule stability (Nechipurenko and

Broihier, 2012). This network, in turn, determines synaptic organization and morphology (Nechipurenko and Broihier, 2012). We therefore used the da system to test if FoxO regulates dendrite morphology and microtubule dynamics. We found that FoxO is necessary for branching in all four classes of da neurons.

Using time-lapse analysis, we observed that FoxO promotes branch point initiation and terminal branch stabilization. Furthermore, overexpression experiments show that FoxO is sufficient to promote branching in multiple classes. FoxO also regulates microtubule stability in dendrites, since stable microtubule staining is expanded in foxO nulls, while overexpression of FoxO results in a reduced stable microtubule distribution. Testing for microtubule dynamics, we observed that FoxO is necessary and sufficient for anterograde polymerization of microtubules. Taken together, these data argue that FoxO is necessary for dendrite branching and normal microtubule dynamics.

85 How might FoxO regulate microtubules in the da system? Our findings suggest promotion of anterograde microtubule polymerization is one likely reason. Indeed, Ori-McKenney et al. (2012) showed that terminal branches with anterograde EB1 comet are more likely to grow or be stable (Ori-McKenney et al.,

2012). Furthermore, terminal branches lacking anterograde comets are more likely to retract (Ori-McKenney et al., 2012). In addition, a recent study by Yalgin et al. (2015) showed that anterograde comets correlate with branch extension.

Our finding that FoxO promotes branching and anterograde comets is consistent with these conclusions.

Work from Ori-McKenney et al. (2012) and Yalgin et al. (2015) indicates that

Golgi outposts regulate the orientation of microtubule polymerization. The Golgi complex is a site of acentrosomal nucleation in fibroblasts, despite their location near the centrosome (Chabin-Brion et al., 2001; Efimov et al., 2007; Miller et al.,

2009). Acentrosomal nucleation at the Golgi complex requires the centrosomal protein AKAP450, g-tubulin, and CLASPs, which capture and stabilize growing plus-ends (Akhmanova and Steinmetz, 2008; Chabin-Brion et al., 2001; Efimov et al., 2007; Hurtado et al., 2011; Miller et al., 2009; Rivero et al., 2009). In neurons, the Golgi complex is present as Golgi stacks in the cell body and Golgi outposts in dendrites (Gardiol et al., 1999; Horton et al., 2005; Pierce et al.,

2001). Work indicates that Golgi outposts supply membrane for growing dendrite arbors and are necessary for dendrite growth (Horton et al., 2005; Ye et al.,

2007). However, a role for nucleation at Golgi outposts had yet to be shown in dendrites. Recent work shows that EB1-GFP comets frequently nucleate from

Golgi outposts and comets that emanate from a Golgi outpost move in the same direction (Ori-McKenney et al., 2012; Yalgin et al., 2015). Furthermore, both

86 g-tubulin and CP309, a Drosophila homolog of AKAP450, are necessary for this nucleation (Ori-McKenney et al., 2012). Yalgin et al. (2015) recently showed that microtubule polymerization direction is regulated in Golgi outposts in class I da neurons. The authors found that the transcription factor Abrupt limits dendrite branching and anterograde microtubule polymerization by promoting Centrosomin

(cnn), a centrosome-associated protein that is crucial for spindle formation

(Dobbelaere et al., 2008; Hayward et al., 2014; Yalgin et al., 2015). Centrosomin localizes to Golgi outposts, where it represses anterograde comets from Golgi outposts and promotes net retrograde comet movement (Yalgin et al., 2015). Loss of cnn results in a gain in dendrite branches and increased anterograde comets.

Interestingly, loss of wee Augmin, an Augmin subunit required for chromosome alignment in female meiosis, suppresses anterograde comets and increased terminal branches in cnn mutants (Meireles et al., 2009; Yalgin et al., 2015).

These findings demonstrate a new role for Golgi outposts in microtubule organization. It is tempting to speculate, therefore, that FoxO may regulate key components of this process. For example, FoxO may repress cnn or promote wee

Augmin. Alternatively, FoxO may promote other acentrosomal nucleation machinery, such as g-tubulin. It will be of interest to discover if FoxO promotes anterograde microtubule polymerization in these ways.

Plus-tip-binding proteins (+TIPs) have also been shown to orient microtubule polymerization (Mattie et al., 2010). In da neurons, the majority of retrograde comets continue to travel towards the cell body after passing through a branch point. In contrast, only a very small proportion of these exits the branch point in an anterograde direction. Using EB1-GFP, the authors found that the plus-ends of polymerizing microtubules track with stable microtubules. Therefore, they tested

87 for regulators of directional growth. They found that loss of either the Apc

(adenomatous polyposis coli, not to be confused with Cdh1-APC), Apc2, or

Kinesin-2 strikingly increases the proportion of anterograde microtubule polymerization. Moreover, overexpression of EB1-GFP also results in an increase in anterograde microtubule polymerization. Many +TIPS including APC associate with the C terminus of EB1, and kinesins have been shown to localize to the plus-end and associate with APC (Akhmanova and Steinmetz, 2008; Siegrist and

Doe, 2005; Jimbo et al., 2002). Therefore, Mattie et al. (2010) tested if Apc1,

Apc2, Kinesin-2, and EB1 could physically interact. Using yeast two-hybrid, they found that Apc could interact with Apc2, the kinesin-2 subunit Kap3, and EB1.

Therefore, they presented a model in which Apc, Apc2, Kinesin-2, and EB1 form a complex that steers growing microtubules. Our data show that FoxO overexpression also greatly increases the proportion of anterograde microtubule polymerization, suggesting that FoxO may be regulating microtubules through regulation of +TIPs and kinesins. It stands to reason, therefore, that FoxO could be promoting anterograde microtubule polymerization by suppressing Apc, Apc2, or Kinesin-2, or by promoting EB1. It will be important, therefore, to test if these molecules are downstream of FoxO.

Concurrent work from our lab suggests another possibility. McLaughlin et al.

(2016) found that FoxO regulates levels of Pavarotti/MKLP1 (Pav) to promote microtubule dynamics at the NMJ. Pav, a member of the Kinesin-6 family, was recently shown to act as a brake for kinesin-1-dependent microtubule sliding (del

Castillo et al., 2015). Kinesin-1-dependent microtubule sliding is critical for growth of neuronal processes in young neurons, but is downregulated in older neurons

(Lu et al., 2013). Loss of Pav leads to mistargeting and overgrowth of axons (del

88 Castillo et al., 2015). Taken together, these data indicate that Pav prevents uncontrolled growth due to microtubule sliding (del Castillo et al., 2015).

McLaughlin et al. (2016) found that Pav staining is increased in foxO mutants, indicating that FoxO normally suppresses levels of Pav. Moreover, FoxO is necessary for activity-dependent synaptic growth plasticity, since activity-dependent growth of nascent boutons is suppressed in foxO mutants compared with controls. Consistent with a role for Pav downstream of FoxO, gain of Pav suppresses activity-dependent growth of nascent boutons. Furthermore, loss of Pav suppresses defects in activity-dependent growth of nascent boutons observed with loss of FoxO. Taken together, these data show a role for Pav downstream of FoxO in presynaptic organization.

Could FoxO be regulating microtubules through Pav in the da system?

Preliminary experiments are consistent with this hypothesis. Since FoxO suppresses Pav in motoneurons (McLaughlin et al., 2016), we predicted that knockdown of Pav would result in increased branching and overall length, the opposite phenotype as loss of foxO. In pav RNAi experiments, we find this to be the case. Knockdown of Pav specifically in class IV results in a 29.2% increase in branch points (p<0.01) (Fig. 3.1A-C). Furthermore, knockdown of Pav results in a

1.16 fold increase in length (p<0.01)(Fig. 3.1D). While these results are promising, it will be important to test for a FoxO-Pav interaction in the da system.

For example, loss of Pav would be expected to rescue loss of foxO phenotypes, while gain of Pav would be expected to suppress FoxO overexpression phenotypes. It will be interesting to test, also, for changes in microtubule stability and microtubule polymerization orientation with gain or loss of Pav in the da system.

89 Our findings indicate that FoxO could also be determining dendrite morphology by limiting microtubule stability. Indeed, we find that loss of the microtubule stabilizer Futsch partially rescues the loss of branching phenotype we observe in loss of foxO mutants. This suggests that dendrites in foxO animals contain overly stable microtubules. Furthermore, recent work showed that loss of

Futsch results in an increase in branching in class I (Yalgin et al., 2015). This is consistent with the conclusion that microtubule stability limits dendrite branching.

The activity of microtubule-severing proteins may explain this change in branching. For example, microtubule-severing proteins Spastin and Kat-60L1 are necessary for dendrite branching (Jinushi-Nakao et al., 2007; Stewart et al.,

2012). Work shows that microtubules, when associated with microtubules stabilizers MAP2 and Tau, can be protected from katanin-mediated severing

(Qiang et al., 2006). Furthermore, axons depleted of Tau are more likely to branch (Yu et al., 2008). It is tempting to speculate, therefore, that foxO may promote branching by downregulating microtubule stabilizers or upregulating microtubule-severing proteins.

Post-translational modifications of microtubules mark their relative stability.

For example acetylation and detyrosination of a-tubulin are markers of stable microtubules (Janke and Bulinski, 2011). Microtubules with tyrosinated tubulin are enriched in dendrites and mark dynamic microtubules (Fukushima et al.,

2009). Interestingly, acetylated and detyrosinated microtubules are more likely to be severed by spastin (Sudo and Baas, 2010; Roll-Mecak and Vale, 2008). A link between this severing and our FoxO results is unclear. Loss of foxO results in expanded acetylated microtubules in motoneurons (Nechipurenko and Broihier,

2012). Nevertheless, tyrosinated tubulin is associated with binding of CAP-Gly

90 domain containing +TIPS (Erck et al., 2005; Peris et al., 2006). Therefore, it stands to reason that FoxO may promote branching by regulating levels of tyrosinated tubulin.

3.2 FoxO and Neuronal Polarity

FoxO is also implicated in axo-dendritic polarity (de la Torre-Ubieta et al., 2010).

Normally, cultured cerebellar granule neurons isolated from P6 rats polarize and grow one long, axon-like process and several shorter, dendrite-like processes.

These dendrite-like processes stain more strongly for the dendrite marker MAP2 than axon-like processes, while axon-like processes stain more strongly for the axon marker Tau1 than the dendrite-like processes. However, simultaneous knockdown of FoxO1, FoxO3, and FoxO6 causes them to become nonpolarized.

In this case, these neurons have multiple morphologically similar processes that contain both Tau1 and MAP2. Therefore, FoxO is necessary for these cells to polarize. Furthermore, simultaneous loss of FoxO1, FoxO3, and FoxO6 in cerebellar granule cells in vivo results in aberrations in polarity (de la Torre-Ubieta et al., 2010). The proportion of granule cells associated with their parallel fibers is reduced, while the processes near the soma are longer than control animals.

Interestingly, similar defects are sustained in older animals (de la Torre-Ubieta et al., 2010). Moreover, after cultured neurons are given two days to polarize, simultaneous knockdown of FoxO1, FoxO3, and FoxO6 results in growth defects

(Christensen et al., 2011). Axon-like processes are shorter and dendrite-like processes are longer compared with controls, indicating that FoxO is necessary for coordinated growth of axons and dendrites (Christensen et al., 2011).

Could FoxO be regulating axo-dendritic polarity in sensory neurons? While

91 possible, data so far is not consistent with this hypothesis. Since FoxO overexpression increases plus-end-out microtubule polymerization, we predicted that FoxO overexpression might cause axonal components to be mislocalized to dendrites. Therefore, we tested for localization of Bruchpilot, a marker of presynaptic active zones (Wagh et al., 2006). However, Bruchpilot is not observed in dendrites of Class IV cells overexpressing FoxO (data not shown).

Nevertheless, this does not rule out that FoxO could be involved in cellular trafficking. The possibility exists that foxO null animals have mislocalized proteins in the da system.

Interestingly, de la Torre-Ubieta et al. (2010) discovered many potential FoxO targets. They found that knockdown of FoxO in cerebellar granule neurons reduces the expression of several polarity genes, such as Par6, Pak1, R-Ras,

Cdh1-APC, and CRMP2. Since they found that Pak1 expression is the most strongly reduced, they tested if FoxO regulates it. Consistent with this hypothesis, knockdown of FoxO in cultured granule neurons results in reduced Pak1 protein levels. Moreover, Pak1 levels correlate with FoxO levels over the course of granule neuron polarization. Taken together, these results suggest that Pak1 is upregulated by FoxO during neuronal polarization. They therefore tested for a

FoxO-Pak1 interaction and found that knockdown of either FoxO or Pak1 significantly increases the number of nonpolarized neurons. Furthermore, loss of both is not additive, and Pak1 expression rescues loss of FoxO phenotypes in vitro and in vivo. Taken together, these data demonstrate that a FoxO-Pak1 pathway regulates neuronal polarity.

92 3.3 FoxO and a Potential Link Between Microtubules and Actin

Pak1 pathways are involved in both actin and microtubule regulation. For example, Pak1 stimulates F-actin assembly through a LIM kinase-cofilin pathway

(Edwards et al., 1999). Furthermore, Pak1 is activated by the Rho GTPases Rac1 and CDC42, also resulting in the assembly of actin (Edwards et al., 1999). In addition, Pak1 phosphorylates and inhibits the microtubule-destabilizing protein

Stathmin, allowing for microtubule assembly (Wittmann et al., 2004). Given its role downstream of FoxO in neuronal polarity, it stands to reason that a

FoxO-Pak1 pathway may determine morphology in da neurons through actin and microtubule regulation.

The Rho GTPase Rac1 is a cytoskeletal regulator involved in actin assembly and dendrite morphogenesis (Jaffe and Hall, 2005; Puram and Bonni, 2013). For example, Rac1 is required for branching in da neurons (Lee et al., 2003).

Interestingly, FoxO overexpression in class I results in morphologies highly reminiscent of class III da neurons and gain of Cut phenotypes in class I (Fig. 2.5;

Grueber et al., 2002; Jinushi-Nakao et al., 2007). In all these cases, short, spiky,

Futsch-negative terminal branches are present in high abundance (Fig. 2.6;

Grueber et al., 2002; Jinushi-Nakao et al., 2007). It has been argued, therefore, that these branches are actin rich, and stable microtubule poor (Grueber et al.,

2002; Jinushi-Nakao et al., 2007). Therefore, I wanted to test two hypotheses.

One, I predicted that the FoxO overexpression phenotype in class I would depend on Rac1 activity. Two, I predicted that expression of a constitutively-active Pak1 would result in increased branching, similar to FoxO overexpression.

To ask if the gain of FoxO phenotype depends on Rac1, I tested if loss of

93 Rac1 suppresses increased branching caused by gain of FoxO. As observed before, FoxO overexpression results in a significant increase in numbers of branch points in class I (Fig. 5.2A-B, D). However, Rac1 knockdown with two separate RNAi lines completely suppresses this phenotype (p > 0.05 compared with controls)(Fig. 5.2C-D). This suggests the possibility that mobilization of the actin cytoskeleton is necessary for FoxO to promote dendrite branching.

If a FoxO-Pak1 pathway exists in the da system, then Pak1 would be predicted to promote dendrite branching. Therefore, I tested if gain of constitutively-active

Pak1 (CA Pak1) in class I increases dendrite branch points. Similar to gain of

FoxO, CA Pak1 results in a striking increase in branch points (2.8-fold increase; p

< 0.001)(Fig. 5.3). However, some morphological differences exist. As noted by the arrows in Figure 5.3, CA Pak1 results in thicker segments in some locations.

This phenotype is not observed with FoxO overexpression. These thicker segments could indicate a different mechanism or a stronger activation of the pathway. Nevertheless, this phenotype suggests that Pak1 could be downstream of FoxO in the da system.

Taken together, this data is consistent with the hypothesis that a FoxO-Pak1 pathway may regulate dendrite branching through actin regulation. Nevertheless, it will be important to test further for a FoxO-Pak1 interaction. It would be predicted, therefore, that loss of Pak1 would suppress phenotypes seen with

FoxO overexpression. Furthermore, loss of both Pak1 and FoxO would be expected to have a similar phenotype as loss of FoxO alone. While loss of Pak1 with different RNAi lines did not result in a consistent phenotype in class IV, loss-of-function pak1 alleles should be tested. Alternatively, a

FoxO-Pak1-Stathmin pathway is a tantalizing possibility that may explain how

94 FoxO regulates microtubule dynamics. Indeed, the sole Stathmin member in

Drosophila is broadly expressed in the developing nervous system, is necessary for normal nervous system development, and has been shown to regulate stability and trafficking at the NMJ (Chauvin and Sobel, 2015; Graf et al., 2011; Ozon et al., 2002). Taken together, Pak1 may provide an important link between FoxO, cytoskeletal regulation, and dendrite morphology.

3.4 Upstream Regulation of FoxO

In neurons, upstream regulators of FoxO are not well understood. FoxO localization can be regulated by phosphorylation, acetylation, and ubiquitylation

(Eijkelenboom and Burgering, 2013). These modifications determine whether

FoxO is located in the nucleus or sequestered by 14-3-3 in the cytoplasm

(Eijkelenboom and Burgering, 2013). FoxO’s transcriptional activity is inhibited by

Akt phosphorylation, which sequesters FoxO in the cytoplasm (Biggs et al., 1999;

Brunet et al., 1999; Burgering and Kops, 2002). Given our findings, an Akt-FoxO pathway would be predicted to inhibit branching and length. Loss of Akt would result in an increase in branching and length, while gain of Akt would result in a loss of branching and length. However, work is not consistent with these hypotheses. Loss of Akt results in reduced dendrite growth, while gain of Akt results in an increase in dendrite growth (Parrish et al., 2009). Therefore, regulation of FoxO in the da system is likely through a different pathway.

In the motoneuron, regulation of FoxO was shown to be Akt-dependent

(Nechipurenko and Broihier, 2012). Furthermore, recent work from our lab showed that Toll-6 regulates FoxO through SARM and Akt (McLaughlin et al.,

2016). These findings suggest that FoxO in da neurons is regulated

95 independently of these pathways. However, loss of Toll-6 also results in a 40% reduction in activated JNK (pJNK) in this system (McLaughlin et al., 2016). This indicates that Toll-6 normally promotes JNK activation (McLaughlin et al., 2016).

In response to stress in other systems, JNK activates FoxO by causing it to enter the nucleus (Essers et al., 2004; Oh et al., 2005; Wang et al., 2005). Moreover, in

Drosophila Toll-6 is neuroprotective in motoneurons and instructs both axon and dendrite targeting in the olfactory system (McIlroy et al., 2013; Ward et al., 2015).

SARM1, in addition, interacts with syndecan-2 to regulate dendritic arborization in cultured hippocampal neurons (Chen et al., 2011). Interestingly, this pathway acts through MKK4-JNK (Chen et al., 2011). Therefore, it would be interesting if this pathway regulates FoxO through JNK in the da system.

3.5 FoxO and Neuronal Plasticity

Our results show that FoxO is necessary for proper nociceptive response. foxO null animals are less responsive to noxious mechanical stimuli, likely due to their reduced class IV complexity. Indeed, previous studies show that reduced class IV cell complexity correlates with reduced nociceptive responses (Ferreira et al.,

2014; Stewart et al., 2012). However, FoxO may be necessary for other mechanisms required for neuronal activity in class IV.

Work from our lab shows that FoxO is involved in presynaptic organization and activity-dependent structural plasticity (McLaughlin et al., 2016; Nechipurenko and Broihier, 2012). Moreover, FoxO6 has been shown to promote spine morphogenesis and is necessary for memory consolidation (Salih et al., 2012). It is tempting to speculate, therefore, that FoxO may also be involved in presynaptic organization, activity-dependent plasticity, and dendritic plasticity in da neurons.

96 Fortunately, class IV cells provide a useful opportunity to test these hypotheses.

Drosophila has emerged as a model for studying the biology of nociception

(Babcock and Galko, 2009; Im and Galko, 2012). Using UV radiation, Drosophila can be tested for factors associated with allodynia, a pain response to normally subthreshold stimuli, and hyperalgesia, an exaggerated response to noxious thermal stimuli. Babcock et al. (2009) showed that allodynia requires the activity of the tumor necrosis factor (TNF) homolog Eiger from the surrounding epithelial cells and the TNF receptor Wengen from sensory neurons. Interestingly, work suggests that Hedgehog signaling is necessary for both allodynia and hyperalgesia, and Hedgehog is produced by class IV neurons following tissue damage (Babcock et al., 2011; Im et al., 2015). Ion channels that respond noxious stimuli are thought to be regulated by these pathways (Babcock et al.,

2011; Im et al., 2015). However, a role for FoxO has not been established in these processes. It will be interesting to test, therefore, if FoxO plays a role in dendritic or axonal plasticity in response to pain stimuli.

3.6 Closing Comments

In this thesis, I have described a new role for FoxO during dendrite arborization.

FoxO is necessary and sufficient for dendrite branching. FoxO is also is necessary for branch point initiation and terminal branch stability. Moreover, FoxO limits the distribution of stable microtubules in dendrites, consistent with FoxO’s role at the NMJ. FoxO is also necessary and sufficient to promote plus-end-out microtubule polymerization, consistent with FoxO’s role in dendrite branching.

This finding raises a number of possibilities for downstream targets of FoxO.

FoxO may be regulating microtubule stabilizing proteins, microtubule severing

97 proteins, +TIPs, molecular motors, polarity molecules, and acentrosomal nucleation machinery. Future work could expand our knowledge of neurodevelopment by identifying the upstream regulators and downstream effectors of FoxO in this system.

As a model for FoxO regulation of both dendrite branching and microtubule dynamics, I propose that FoxO is promoting branch extension and branch stability by promoting the presence of microtubules in shorter dendritic branches (Figure

5.4A). This could occur through increased plus-end-out microtubule polymerization (Figure 5.4B), through downregulation of +TIPs, downregulation of kinesin-2, or through upregulation of EB1. Alternatively, FoxO could regulate levels of Golgi outpost proteins that control the direction of microtubule polymerization. Moreover, FoxO could be promoting a more dynamic, less stable microtubule state more conducive for microtubule severing, followed by minus-end stabilization and plus-end-out microtubule polymerization (Figure

5.4C). Furthermore, FoxO may limit MKLP1 expression, thereby allowing kinesin-1-associated microtubule sliding to provide protrusive force for arbor extension (Figure 5.4D). In this case, it is plausible that plus-end-out microtubules within the branch would allow kinesin-1 to slide plus-end-in microtubules in the anterograde direction. However, it is tempting to speculate not only that minus-end-directed motors may play a role in more stable arbors, but also that other proteins and modifications may move filaments in plus-end-out bundles in an anterograde direction. With loss of foxO, reduced microtubule dynamics would be expected to result in reduced branch initiation (Figure 5.4E). In addition, reduced microtubule polymerization in branches would be expected to result in reduced branch stability, resulting in branch retraction (Figure 5.4F). Lastly,

98 increased microtubule stability may prevent microtubule polymerization and severing or may serve as a substrate to guide microtubule polymerization in the plus-end-in direction, rather than the plus-end-out direction. Taken together, this model argues that FoxO promotes branch initiation and stability through plus-end-out microtubule polymerization, which by itself may stabilize and extend dendrite branches. Furthermore, these plus-end-out microtubules may serve as a foundation for further microtubule dynamics that stabilize and extend dendrite branches.

99 Chapter 4

Appendix A: Visualizing the Dendritic Arborization System

Study of da dendrite development would not be possible without genetic and microscopy tools. Simply marking all neurons would not allow for clear and careful analysis of specific cell types. This is especially the case with class IV neurons. Owing to its extensive size and complicated morphology, it would be very challenging to accurately define cellular morphology. Fortunately, genetic tools have been developed to mark specific subtypes of cells.

The GAL4/UAS system has been adopted from yeast biology to allow for tissue specific expression of intended molecules (Brand and Perrimon, 1993).

GAL4 is a transcription activator protein that recognizes Upstream Activation

Sequences (UAS), and subsequently activates downstream gene transcription

(Ptashne, 1988). Despite its absence in the Drosophila genome normally, GAL4, when expressed in a tissue specific manner, is able to activate transcription downstream of GAL4-binding sites (Fischer et al., 1988). GAL4 inserted in tissue specific domains of the genome can be paired with UAS lines to express molecules of interest within those tissues (Brand and Perrimon, 1993). For example, in the da system, 477-GAL4 will cause selective expression of genes

100 downstream of an UAS in class IV, 2-21-GAL4 in class I, C161-GAL4 in classes

I-III, and 109(2)80-GAL4 in classes I-IV. Therefore, using GAL4/UAS, specific cells can be marked with GFP and made to overexpress genes of interest, to name just two applications. Importantly, since this system is not normally present in Drosophila, it has little to no off-target effects (Fischer et al., 1988). Moreover, the system can be paired with other genetic tools.

Mosaic Analysis with a Repressible Cell Marker (MARCM) is one such tool that expands upon the use of the GAL4/UAS system (Lee and Luo, 1999). It is useful not only for labeling a subset of cells, but also for assessing cellular autonomy (Lee and Luo, 1999). Experiments for cellular autonomy test whether phenotypes are due to gene activation within a specific cell type. As a background to this technique, GAL4/UAS-activation of a marker such as GFP is repressed by constitutive expression of GAL80, which binds GAL4 and interferes with its ability to bind to an UAS (Ma and Ptashne, 1987; Lee and Luo, 1999).

Using a site-specific, inducible recombinase called flippase (FLP), recombination events can be triggered to occur at known flippase recognition target sites (FRTs) during mitosis (Golic and Lindquist, 1989). This recombination effectively switches the regions of the chromosomes distal to the FRT, resulting in two genetically different daughter cells. One cell contains two homologous chromosomes containing GAL80, and the other cell contains two homologous chromosomes without GAL80. The cell with two copies of GAL80 will continue to have GAL4/UAS marker repression, but the cell without GAL80 will be allowed to express the GAL4/UAS marker. Moreover, if one homologous chromosome with

FRT has a mutation, the other GAL80 and a normal allele, recombination will result in a daughter cell that is, in addition to being marked, homozygous for the

101 mutation. Therefore, marked cells can be null for a gene, while the unmarked cells will have at least one wild-type copy of the gene. In this way, MARCM can be used to assess cellular autonomy of morphology-associated genes.

In addition to marking the surface of cells, GFP can also be used to mark proteins within cells. Of special note are +TIP-binding proteins, such as the end-binding (EB) proteins EB1 and EB3. These proteins associate and track with growing plus-end of microtubules (Mimori-Kiyosue et al., 2000; Schuyler and

Pellman, 2001; Stepanova et al., 2003). By conjugating these +TIP-binding proteins with GFP, they can be used to visualize the growth of microtubules live

(Mimori-Kiyosue et al., 2000; Rolls et al., 2007; Stepanova et al., 2003; Stone et al., 2008). In particular, the amount and direction (and therefore polarity) of microtubule polymerization can be assessed with these chimeric proteins. Some of the first work using EB3-GFP in cultured neurons repeated earlier findings using the hooking technique, validating both the utility of EB3-GFP and previous results (Stepanova et al., 2003). Importantly, using EB1-GFP, pioneering researchers were able to capture live dynamics of microtubules in vivo in the da system (Rolls et al., 2007; Stone et al., 2008).

102 Chapter 5

Appendix B: Discussion Figures

5.1 Materials and Methods

Imaging and immunolabeling experiments were conducted as described in

Chapter 2. 2-21-Gal4, UAS-mCD8-GFP and UAS-dcr2; ppk-Gal4,

UAS-mCD8-GFP were used to mark and drive expression in class I and class IV, respectively (gifts from Melissa Rolls [Pennsylvania State University, University

Park, PA, US]). To overexpress FoxO, UAS-FoxOwt was used (listed as FoxO WT

#1; a gift from Robert Tjian [University of California, Berkeley, Berkeley, CA, US]).

For knockdown of pav, BSC#35649 was used. For knockdown of Rac1,

BSC#34910 (rac1 RNAi #1) and BSC#28985 (rac1 RNAi #2) were used. For control RNAi, Vienna Drosophila RNAi Center lines 25271 was used

(gamma-tubulin 37C RNAi, listed as control RNAi #1). For expression of constitutively-active Pak1, BSC#8804 was used. Branch point analysis was conducted in ImageJ. Statistical analysis was performed in GraphPad Prism.

When two groups were compared, unpaired, two-tailed t-tests with Welch’s correction were performed. When more than two groups were compared, one-way ANOVA was performed with multiple comparisons between each group with Tukey’s correction. For significance, * is p < 0.05, ** is p < 0.01, and *** is p <

0.001. No significant difference is n.s.

103 5.2 Figures

Figure 5.1

control pavarotti RNAi

control pavarotti RNAi

104 Fig. 5.1. Pavarotti regulates class IV dendrite morphology. (A, B) Representative z-projections of class IV ddaC neurons marked with mCD8-GFP driven by ppk-Gal4. (C) Quantification of dendrite branch point numbers in animals expressing control RNAi #1: 669.8 36.84, n=6 cells; animals expressing pav ± RNAi: 865.7 28.89, n=7 cells. (D) Quantification of dendrite length in animals ± expressing control RNAi #1: 19.68 0.51 mm, n=6 cells; animals expressing pav ± RNAi: 22.88 0.73 mm, n=7 cells. (E) Class IV ddaC Sholl analysis of animals ± expressing control RNAi #1 (blue with circles) or pav RNAi (black with squares).

The scale bar is 50 µm. Error bars are mean s.e.m., **, p < 0.01. ±

105 Figure 5.2

control 221 > FoxO WT A B

221 > FoxO WT & rac1 RNAi D *** 80 *** s C t *** 60 h poin c n ns ra 40 b e t i ns r ns 20 nd e d # 0 16 5 9 6 l 1 2

contro

221 > FoxO WT

221 > FoxO WT221 & rac1 > FoxO RNAi WT # & rac1 RNAi #

106 Fig. 5.2. Knockdown of Rac1 suppresses increased branching in class I cells overexpressing FoxO. (A-C) Representative z-projections of class I ddaE neurons marked with mCD8-GFP driven by 2-21-Gal4. (D) Quantification of dendrite branch point numbers in control animals: 26.3 1.0, n=16; animals expressing ± FoxO WT #1: 61.2 6.5, n=5; animals expressing FoxO WT #1 and rac1 RNAi ± #1: 19.11 5.9, n=9; animals expressing FoxO WT #1 and rac1 RNAi #2: 21.7 ± ± 4.1, n=6 . The scale bar is 50 µm. Error bars are mean s.e.m., ***, p < 0.001. ± No significant difference is n.s.

107 Figure 5.3

control constitutively-active Pak1 A B

C 100 *** 80

60

40

20

# dendrite branch points branch dendrite # 8 9 0 control CA Pak

108 Fig. 5.3. Constitutively-active Pak1 increases branching in class I. (A, B)

Representative z-projections of class I ddaE neurons marked with mCD8-GFP driven by 2-21-Gal4. Purple arrows in B mark thicker sections of arbor that are seen in this cross. (C) Quantification of dendrite branch point numbers of class I ddaE neurons in control animals: 27.1 0.5, n=8; in animals expressing ± constitutively-active Pak1: 77.0 5.5, n=9. The scale bar is 50 µm. Error bars ± are mean s.e.m., ***, p < 0.001. ±

109 Figure 5.4

A wild-type microtubules stabilizing branches

B wild-type plus-end-out microtubule polymerization

C wild-type instability, severing, and 110 polymerization

D wild-type microtubule sliding and extension

E foxO null loss of branch initiation

F foxO null loss of branch maintenance Fig. 5.4. A model for FoxO regulation of microtubules and dendrite morphology.

The black arrow points towards the cell body. New microtubule filaments and recently polymerized microtubule filaments are displayed in purple, molecular motors are displayed as green circles, and plus-ends are marked with blue squares.

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