Yamini Ravichandran

Bruno Goud

Jean-Baptiste Manneville
email: baptiste.manneville@curie.fr

The Golgi apparatus and cell polarity: roles of the cytoskeleton, the Golgi matrix and Golgi membranes

Keywords: trafficking, microtubules, actin, signaling, golgin, centrosome, forces

Membrane trafficking plays a crucial role in cell polarity by directing lipids and proteins to specific subcellular locations in the cell and sustaining a polarized state. The Golgi apparatus, the master organizer of membrane trafficking, can be subdivided into three layers that play different mechanical roles: a cytoskeletal layer, the so-called Golgi matrix and the Golgi membranes. First, the outer regions of the Golgi apparatus interact with cytoskeletal elements, mainly actin and microtubules, which shape, position and orient the organelle. Closer to the Golgi membranes, a matrix of long coiled-coiled proteins not only selectively captures transport intermediates but also participates in signaling events during polarization of membrane trafficking. Finally, the Golgi membranes themselves serve as active signaling platforms during cell polarity events. We review here the recent findings that link the Golgi apparatus to cell polarity, focusing on the roles of the cytoskeleton, the Golgi matrix and the Golgi membranes.

Introduction

The Golgi apparatus is the transformation and sorting factory of most proteins and plays a pivotal role in membrane trafficking. In the secretory pathway, the Golgi apparatus receives de novo synthesized molecules from the endoplasmic reticulum (ER), posttranslationally processes lipids and proteins, and sorts cargoes to their ultimate destination [START_REF] Boncompain | Transport and sorting in the Golgi complex: multiple mechanisms sort diverse cargo[END_REF][START_REF] Guo | Protein Sorting at the trans -Golgi Network[END_REF]. Cell polarity, the process by which a cell defines an oriented axis for instance to migrate, divide or differentiate, strongly depends on membrane trafficking [START_REF] Bryant | Editorial overview: Membrane traffic and cell polarity[END_REF]. Over the past three decades, evidence has accumulated showing that the structure, organization and positioning of the Golgi apparatus are implicated in maintaining a polarized cell state [START_REF] Guo | Protein Sorting at the trans -Golgi Network[END_REF][START_REF] Yadav | Golgi positioning[END_REF][START_REF] Zhu | Golgi as an MTOC: Making microtubules for its own good[END_REF][START_REF] Gurel | Connecting the cytoskeleton to the endoplasmic reticulum and Golgi[END_REF]. In polarized cells, cellular materials are transported along the polarity axis. This requires polarization of membrane trafficking from the Golgi apparatus. Conversely, the position of the Golgi inside the cell can dictate the directionality of membrane trafficking and the proper localization of polarity cues. This 'chicken-and-egg' problem is typical of feedback loops involved in symmetry breaking during establishment of cell polarity. In the case of Golgi-dependent membrane trafficking, the orientation of the Golgi apparatus in the direction of the polarity axis targets transport towards a given region of the cell, for example, towards the leading edge plasma membrane during cell migration (front-rear polarity), in the apical process of neural stem cells (radial polarity), towards the apical compartment of epithelial cells or towards the immunological synapse (Fig. 1). In all these examples and despite intensive research, it is still not clear whether and how external polarity cues are transduced inside the cell to polarize transport from the Golgi apparatus, and conversely, whether and how the Golgi apparatus could be driving cell polarization. One historical example is given by the small G protein CDC42. CDC42 was identified as an evolutionary conserved polarity protein in several organisms, from yeast to humans [START_REF]Cdc42 -The centre of polarity[END_REF]. In mammalian cells, beside its functions in cell protrusion formation and cell migration as a plasma membrane-associated protein, CDC42 also operates in intracellular vesicle trafficking [START_REF] Farhan | Cdc42 and Cellular Polarity: Emerging Roles at the Golgi[END_REF][START_REF] Osmani | Scrib Controls Cdc42 Localization and Activity to Promote Cell Polarization during Astrocyte Migration[END_REF]. Consistently, CDC42 not only localizes at the plasma membrane but also at the Golgi apparatus where it interacts with the Golgi matrix [START_REF] Farhan | Cdc42 and Cellular Polarity: Emerging Roles at the Golgi[END_REF], coat proteins [START_REF] Park | Coordinated regulation of bidirectional COPI transport at the Golgi by CDC42[END_REF][START_REF] Chen | Coatomer-bound Cdc42 regulates dynein recruitment to COPI vesicles[END_REF][START_REF] Wu | The γ-subunit of the coatomer complex binds Cdc42 to mediate transformation[END_REF], microtubule motors and the actin polymerization machinery [START_REF] Chen | Coatomer-bound Cdc42 regulates dynein recruitment to COPI vesicles[END_REF]. However the precise role of CDC42 at the Golgi apparatus, how the Golgi associated pool of CDC42 interacts with the plasma membrane-associated pool and whether these interactions impact on cell polarity remains to be determined [START_REF] Farhan | Cdc42 and Cellular Polarity: Emerging Roles at the Golgi[END_REF].

We focus here on the machineries localized at the Golgi apparatus which have been shown or hypothesized to participate in establishing directional membrane trafficking during cell polarization in mammalian cells. The Golgi apparatus can be viewed structurally as a three-layered organelle constituted of membrane-enclosed Golgi cisternae, the so-called Golgi matrix and cytoskeletal elements. Because of its organization in cis, median and trans compartments, the Golgi apparatus possesses an intrinsic polarity. Intra-Golgi trafficking is in itself a polarized process, whether it is described in terms of a vesicular transport or a cisternal maturation model [START_REF] Glick | Models for Golgi traffic: A critical assessment[END_REF]. In mammalian cells, Golgi stacks are tethered laterally to form a Golgi ribbon typically found in tight association with the centrosome. Current models suggest that the assembly of the Golgi ribbon is an actin and microtubule (MT) dependent process. Maintenance of the Golgi architecture depends on the cytoskeleton and is coordinated at least in part by Rho and Rab GTPases [START_REF] Goud | Rab proteins as major determinants of the Golgi complex structure[END_REF][START_REF] Phuyal | Multifaceted Rho GTPase Signaling at the Endomembranes[END_REF]. In the following, we review recent work on the molecular players acting at the Golgi apparatus and relevant for the mechanical aspects of cell polarization, such as the generation of forces involved in Golgi positioning. For clarity, we have separated the description of the molecular mechanisms in three parts each corresponding to one structural component of the Golgi apparatusthe Golgi matrix, the Golgi-associated cytoskeleton and Golgi membranes even if these three components are linked and interact with one another.

Golgi matrix proteins and cell polarity

In mammalian cells, Golgi membranes are organized as an interconnected ribbon typically positioned adjacent to the centrosome in the perinuclear region. This proximity is usually disrupted by conditions that perturb Golgi organization. The functional significance of the proximity between the Golgi apparatus and the centrosome is not fully understood. Several studies have linked the spatial connection between the centrosome and the Golgi apparatus with directed protein transport or directional migration [START_REF] Hurtado | Disconnecting the Golgi ribbon from the centrosome prevents directional cell migration and ciliogenesis[END_REF][START_REF] Wu | Microtubule-Organizing Centers[END_REF][START_REF] Yadav | A primary role for golgi positioning in directed secretion, cell polarity, and wound healing[END_REF]. In front-rear cell polarity models, such as directed cell migration, centrosomal reorientation towards the leading edge is known to align the Golgi apparatus towards the leading edge (Fig. 1A).

Strikingly a number of proteins belonging to the Golgi matrix [START_REF] Ramirez | Golgins and GRASPs: Holding the Golgi together[END_REF][START_REF] Gillingham | Finding the Golgi: Golgin Coiled-Coil Proteins Show the Way[END_REF] are not only critical for maintaining the typical Golgi architecture and its positioning close to the centrosome, but also for cell polarity. For instance, Golgi reassembly and stack proteins (GRASPs) link Golgi stacks together. Depletion of GRASP55 or GRASP65 perturbs Golgi organization and function [START_REF] Zhang | GRASPs in Golgi structure and function[END_REF] and the phosphorylation of GRASP65 is required for both Golgi and centrosome reorientation during directed cell migration [START_REF] Bisel | ERK regulates Golgi and centrosome orientation towards the leading edge through GRASP65[END_REF]. Depletion of GRASP65 and GRASP55 also reduces the level of 51 integrin and consequently decreases adhesion, migration and invasion of HeLa cells and of the breast cancer cell line MDA-MB-231 [START_REF] Ahat | GRASP depletion-mediated Golgi destruction decreases cell adhesion and migration via the reduction of α5β1 integrin[END_REF]•.

Similarly, the Golgi matrix protein GM130, a GRASP65 binding partner, has been implicated in cell polarity. GM130 recruits and activates the kinase YSK1 which phosphorylates downstream cell polarity targets [START_REF] Preisinger | YSK1 is activated by the Golgi matrix protein GM130 and plays a role in cell migration through its substrate 14-3-3ζ[END_REF]. Consistently, expressing inactive YSK1 blocks both Golgi and centrosome reorientation during cell migration [START_REF] Preisinger | YSK1 is activated by the Golgi matrix protein GM130 and plays a role in cell migration through its substrate 14-3-3ζ[END_REF]. In addition, GM130 may also control cell migration through the activation of both YSK1 and CDC42 [START_REF] Preisinger | YSK1 is activated by the Golgi matrix protein GM130 and plays a role in cell migration through its substrate 14-3-3ζ[END_REF][START_REF] Kodani | A new function for an old organelle: Microtubule nucleation at the Golgi apparatus[END_REF][START_REF] Baschieri | Spatial control of Cdc42 signalling by a GM130-RasGRF complex regulates polarity and tumorigenesis[END_REF]. More recently, deletion of GM130 in Purkinje neurons has been shown to induce Golgi fragmentation and defects in Golgi positioning [START_REF] Liu | Loss of the golgin GM130 causes Golgi disruption, Purkinje neuron loss, and ataxia in mice[END_REF]••. In contrast, a study carried out in GM130 knock out (KO) retinal pigment epithelial (RPE-1) cells shows that the physical proximity between the centrosome and the Golgi apparatus is not necessary for protein transport, cell migration, or ciliogenesis [28]•.

While these results further strengthen the proposed role of GM130 in Golgi ribbon formation and in associating the Golgi apparatus to the centrosome by recruiting AKAP450 (A-kinase anchoring protein of 450 kDa, also known as AKAP350, AKAP9, or CG-NAP) [START_REF] Rivero | Microtubule nucleation at the cisside of the golgi apparatus requires AKAP450 and GM130[END_REF], they question whether a connection between the Golgi apparatus and the centrosome is required for cell polarity during directed migration (Fig. 1A) [START_REF] Hurtado | Disconnecting the Golgi ribbon from the centrosome prevents directional cell migration and ciliogenesis[END_REF].

Golgi-associated cytoskeletal elements

The actin and microtubule network and their associated molecular motors play a key role in maintaining Golgi architecture and positioning during cell polarization by generating forces and mechanical tension [START_REF] Egea | Actin acting at the golgi[END_REF][START_REF] Sanders | Nucleation and dynamics of Golgi-derived microtubules[END_REF][START_REF] Allan | Motoring around the Golgi[END_REF]. In particular, the microtubule minusend directed motor dynein has been shown both to anchor microtubule plus-ends at the plasma membrane and to concentrate at the Golgi apparatus. During directed cell migration activation of CDC42 at the leading edge plasma membrane recruits and anchors dynein at the cell cortex via the Par polarity complex [START_REF] Etienne-Manneville | Integrin-mediated activation of Cdc42 controls cell polarity in migrating astrocytes through PKCζ[END_REF][START_REF] Etienne-Manneville | Cell polarity: Par6, aPKC and cytoskeletal crosstalk[END_REF]. Dynein in turn pulls on astral microtubules to reorient the centrosome towards the leading edge [START_REF] Etienne-Manneville | Integrin-mediated activation of Cdc42 controls cell polarity in migrating astrocytes through PKCζ[END_REF][START_REF] Palazzo | Cdc42, dynein, and dynactin regulate MTOC reorientation independent of Rho-regulated microtubule stabilization[END_REF][START_REF] Manneville | Dlg1 binds GKAP to control dynein association with microtubules, centrosome positioning, and cell polarity[END_REF][START_REF] Manneville | Positioning centrosomes and spindle poles: looking at the periphery to find the centre[END_REF]. The Golgi apparatus probably reorients via the same mechanism through its mechanical link with the centrosome. Dynein is also found at the cis-Golgi where it associates with the actin cytoskeleton and coat proteins [START_REF] Chen | Coatomer-bound Cdc42 regulates dynein recruitment to COPI vesicles[END_REF]. Together with results showing the role of the CDC42/COPI interaction in directed intra-Golgi trafficking [START_REF] Park | Coordinated regulation of bidirectional COPI transport at the Golgi by CDC42[END_REF], these observations suggest that Golgi-localized dynein could also participate in redirecting membrane trafficking during establishment of cell polarity. In addition to this physical link between the dynein motor and the Golgi apparatus, recent studies have mostly focused on the role of Golgi-nucleated microtubules and on actin-generated tension to link the Golgi apparatus with cell polarity.

The Golgi apparatus as a polarized non-centrosomal microtubule organizing center

The Golgi apparatus is a site that can nucleate and stabilize non-centrosomal microtubules [START_REF] Zhu | Golgi as an MTOC: Making microtubules for its own good[END_REF][START_REF] Sanders | Nucleation and dynamics of Golgi-derived microtubules[END_REF][START_REF] Chabin-Brion | The Golgi complex is a microtubule-organizing organelle[END_REF][START_REF] Rios | The centrosome -Golgi apparatus nexus[END_REF]. Microtubule nucleating and/or stabilizing factors accumulate at Golgi membranes and act as molecular scaffolds. Golgi-derived microtubule arrays are polarized and can therefore induce cell asymmetry facilitating polarized transport of post-Golgi cargoes in a specific direction [START_REF] Hurtado | Disconnecting the Golgi ribbon from the centrosome prevents directional cell migration and ciliogenesis[END_REF][START_REF] Vinogradova | Concerted effort of centrosomal and golgiderived microtubules is required for proper golgi complex assembly but not for maintenance[END_REF][START_REF] Vinogradova | Microtubule network asymmetry in motile cells: Role of Golgi-derived array[END_REF] during cell migration and differentiation [START_REF] Ori-Mckenney | Golgi Outposts Shape Dendrite Morphology by Functioning as Sites of Acentrosomal Microtubule Nucleation in Neurons[END_REF][START_REF] Oddoux | Microtubules that form the stationary lattice of muscle fibers are dynamic and nucleated at golgi elements[END_REF][START_REF] Yalgin | Centrosomin represses dendrite branching by orienting microtubule nucleation[END_REF][START_REF] Zhu | Microtubules Negatively Regulate Insulin Secretion in Pancreatic β Cells[END_REF]. Recently better characterization of the molecular machineries associated both at the plus and minus-ends of Golgi-derived microtubules involved in their nucleation, dynamics, stabilization and regulation has led to a model clarifying the role of these microtubules in the polarization of membrane trafficking (Fig. 2).

First, the identification of the cis-Golgi localized protein AKAP450 as a key player in Golgi-derived microtubule nucleation transformed the field of Golgi-derived microtubules [START_REF] Schmidt | AKAP350, a Multiply Spliced Protein Kinase A-anchoring Protein Associated with Centrosomes[END_REF][START_REF] Takahashi | Characterization of a Novel Giant Scaffolding Protein, CG-NAP, That Anchors Multiple Signaling Enzymes to Centrosome and the Golgi Apparatus[END_REF]. AKAP450 recruits two γ-TuRC-binding homologous proteins namely CEP215 and myomegalin (MMG) which in turn recruit γ-TuRC (Fig. 2A) [START_REF] Choi | CDK5RAP2 stimulates microtubule nucleation by the γ-tubulin ring complex[END_REF][START_REF] Roubin | Myomegalin is necessary for the formation of centrosomal and Golgiderived microtubules[END_REF][START_REF] Wang | Conserved motif of CDK5RAP2 mediates its localization to centrosomes and the Golgi complex[END_REF][START_REF] Wang | A newly identified myomegalin isoform functions in Golgi microtubule organization and ER-Golgi transport[END_REF]. Simultaneously several studies showed that recruitment of cytoplasmic linkerassociated proteins (CLASPs) to the trans-Golgi by the golgin GCC185 was also essential for the nucleation and organization of Golgi-derived microtubules [START_REF] Miller | Golgi-derived CLASP-dependent microtubules control Golgi organization and polarized trafficking in motile cells[END_REF][START_REF] Efimov | Asymmetric CLASP-Dependent Nucleation of Noncentrosomal Microtubules at the trans-Golgi Network[END_REF]. CLASPs are microtubule plus-end tracking proteins (+TIPs) that stabilize microtubules [START_REF] Mimori-Kiyosue | CLASP1 and CLASP2 bind to EB1 and regulate microtubule plus-end dynamics at the cell cortex[END_REF] (Fig. 2B). Both AKAP450 and CLASPs associate with the microtubule latticebinding protein MTCL1, which promotes microtubule association with the Golgi apparatus [START_REF] Sato | MTCL1 crosslinks and stabilizes non-centrosomal microtubules on the Golgi membrane[END_REF]. Therefore, the initial models of Golgi-derived microtubules involved tethering of microtubules regulatory proteins at both cis-and trans-Golgi compartments. How these differently localized groups of proteins could collaborate in the same pathway to generate polarized microtubule arrays was unclear, especially in the absence of microtubule stabilizing proteins essential for anchoring microtubule minusends to Golgi membranes.

Depletion of the calmodulin-regulated spectrin-associated protein CAMSAP2 in mammalian RPE-1 cells leads to the loss of most non-centrosomal microtubules [START_REF] Jiang | Microtubule Minus-End Stabilization by Polymerization-Driven CAMSAP Deposition[END_REF], suggesting that CAMSAP2 participates in microtubule stabilization at Golgi membranes. Subsequently, CAMSAP2 was shown to be essential for tethering, but not for nucleation, of non-centrosomal microtubules at the Golgi apparatus [START_REF] Wu | Molecular Pathway of Microtubule Organization at the Golgi Apparatus[END_REF]••. AKAP450 is thought to play a dual function by organizing Golgi microtubules at the cis-Golgi, initially by anchoring CAMSAP2-bound microtubule minus-ends, and then by enhancing microtubule nucleation through -TURC recruitment (Fig. 2B,C). Through their roles in organizing Golgi-anchored microtubules, AKAP450 and CAMSAP2 contribute to Golgi reorientation during cell polarization and migration. Interestingly, Golgi-anchored microtubules also appear to participate in Golgi fragmentation during Golgi reorientation, probably by exerting pulling forces on Golgi membranes [START_REF] Wu | Molecular Pathway of Microtubule Organization at the Golgi Apparatus[END_REF]••. Similar mechanisms may be at play in other polarity models. For instance, noncentrosomal microtubules control cell polarity in endothelial cells migrating in 2D and 3D models and during vessel development in Zebrafish [58]•. Interestingly, another CAMSAP family member, CAMSAP3, has been involved in apico-basal polarity in epithelial cells (Fig. 1B) [59]. Here CAMSAP3 tethers microtubule minus-ends to the apical cortex, resulting in pulling forces which may orient the microtubule array in the apico-basal direction and lead to the polarized intracellular organization and positioning organelles typical of epithelial cells.

Associated with CAMSAP2, the end binding proteins (EBs) EB1, EB2 and EB3 which form the core components of microtubule plus-end tracking protein (+TIPs) complexes, have been implicated in tethering microtubules to the Golgi apparatus, in Golgi morphology and reorientation during directed cell migration. The current model for EB-dependent polarized organization of microtubules at the Golgi apparatus involves the interaction between AKAP450 and MMG. MMG recruits EBs along microtubules to induce dispersion of Golgi stacks via plus-end tracking. MMG also recruits CAMSAP2 in an EB-dependent manner at microtubule minus-ends to favor Golgi compaction probably via dynein-mediated transport [START_REF] Yang | EB1 and EB3 regulate microtubule minus end organization and Golgi morphology[END_REF]• (Fig. 2C).

Linking actin and the Golgi apparatus

The Golgi apparatus is a hub for a wide array of actin regulatory proteins. CDC42, WHAMM, WAVE, Arp2/3 complex, cortactin, cofilin, profilin II and several myosins (II, VI, 18, 1b) localize at the Golgi apparatus and the trans-Golgi network (TGN) [START_REF] Egea | Actin acting at the golgi[END_REF]. In addition to the evident role of microtubules, the actin cytoskeleton is also emerging as a key factor in the assembly and maintenance of the Golgi architecture, in Golgi mechanics and in Golgi-dependent membrane trafficking [START_REF] Egea | Actin acting at the golgi[END_REF]61,[START_REF] Lázaro-Diéguez | Actin filaments are involved in the maintenance of Golgi cisternae morphology and intra-Golgi pH[END_REF]. Golgi reorientation during cell migration depends on Rho-associated protein kinase (ROCK), a main regulator of acto-myosin contractility [START_REF] Brasch | Nuclear position relative to the Golgi body and nuclear orientation are differentially responsive indicators of cell polarized motility[END_REF]. Aside from the Arp2/3 complex which generates branched actin networks, three actin nucleators belonging to the formin family have been linked to the Golgi apparatus, mDia1, INF2 and FMNL1 isoform γ [START_REF] Gurel | Connecting the cytoskeleton to the endoplasmic reticulum and Golgi[END_REF][START_REF] Zilberman | Involvement of the Rho-mDia1 pathway in the regulation of Golgi complex architecture and dynamics[END_REF]. In addition, recent work shows that the formin family members FMNL2 and -3, CDC42 effectors known to regulate cell edge protrusion during migration and invasion, localize and function at the Golgi apparatus [START_REF] Kage | FMNL2 and -3 regulate Golgi architecture and anterograde transport downstream of Cdc42[END_REF]••. Consistent with the role of CDC42 in regulating anterograde transport through the Golgi apparatus via cargo sorting and carrier formation [START_REF] Park | Coordinated regulation of bidirectional COPI transport at the Golgi by CDC42[END_REF], FMNL2/3 depletion also affects anterograde trafficking from the Golgi apparatus to the plasma membrane [START_REF] Kage | FMNL2 and -3 regulate Golgi architecture and anterograde transport downstream of Cdc42[END_REF]••. Such a link between FMNL2/3 and the actin-dependent functions of CDC42 could be of particular importance during polarization of membrane trafficking (Fig. 3A).

Deciphering the link between actin driven migration and Golgi apparatus reorientation is key to understanding how both processes are coupled in space and time during cell polarization. Golgi phosphoprotein 3 (GOLPH3) is one such pivotal link required for Golgi to plasma membrane trafficking that bridges the Golgi apparatus to the actin cytoskeleton [START_REF] Farber-Katz | DNA damage triggers golgi dispersal via DNA-PK and GOLPH3[END_REF][68][69][70]. GOLPH3 is known to bind to phosphatidylinositol-4phosphate (PtdIns(4)P), a lipid enriched in trans-Golgi membranes. Most importantly, GOLPH3 binds the unconventional myosin, myosin 18A (MYO18A), which links the Golgi apparatus to F-actin. The GOLPH3/MYO18A/F-actin pathway is thought to exert a tensile force on Golgi cisternae and to participate in Golgi reorientation during cell polarization [71]• [72,73] (Fig. 3B). However the role of GOLPH3 as one of the main Golgi-associated actor driving polarization of membrane trafficking has been recently questioned by the finding that MYO18A does not display any motor activity [74]••.

Interactions between actin and Golgi-derived microtubules

The actin and microtubule cytoskeletons interactions occur at several subcellular locations, for instance at focal adhesions at the plasma membrane (see [75,76] for a recent review) or at the nuclear envelope [77]. Not surprisingly, these interactions are also observed at the Golgi apparatus. A distinct connection between Golgi membranes, actin filaments and Golgi-derived microtubules has been recently proposed. The formin protein FHDC1/IFN1 is thought to coordinate actin and microtubule dynamics during Golgi ribbon formation, and to establish intrinsic Golgi polarity [78]•.

Golgi membranes

Golgi membranes are located at the crossroads between the anterograde secretory route and the retrograde route. Golgi lipids and membrane proteins are thus ideally situated to be involved in a large number of signaling pathways, among which is signaling involved in cell polarity. Polarity proteins such as CDC42 localize at the Golgi apparatus, although their function there is still not clear. Other Golgi-localized GTPases have been recently shown to mediate trafficking events potentially involved in cell polarization, such as Arf1 in response to cell-matrix adhesion cues [79], Arl5 during amino acids-stimulated retrograde trafficking [80] or Rab6 in targeting secretion to focal adhesions [81]. We focus below on the less studied role of Golgi lipids and lipid metabolism in polarization processes.

Golgi lipids: new roles for PtdIns(4)P

PtdIns(4)P initiates the recruitment of the GOLPH3/MYO18A/F-actin machinery at Golgi membranes to shape the Golgi ribbon during cell polarization. Recently, two studies point to new roles for PtdIns(4)P and GOLPH3 in membrane trafficking and cell polarity. First, elegant in vitro experiments with liposomes and purified proteins confirm that PtdIns(4)P is required for GOLPH3 binding to membranes and demonstrate that GOLPH3 binding to PtdIns(4)P-containing membranes induces membrane curvature and tubulation in a PtdIns(4)P-dependent manner [82]•. Second, a developmental biology study has demonstrated a new role for PtdIns(4)P during neurogenesis [83]••.

A lipid signaling pathway involving Phosphatidylinositol transfer proteins (PITPs), PtdIns(4)P, GOLPH3 and ceramide transfer protein (CERT) at the Golgi apparatus appears to regulate apically directed membrane trafficking in neural stem cells during neocortex development in mice. CERT also plays an important role in Golgi positioning in these cells via a PtdIns(4)P-dependent mechanism [83]•• (Fig. 3B).

Lipid metabolism and mechanosensitivity

Cell polarity is often triggered by mechanical cues induced by cell-cell or cell-matrix adhesion. Such mechanical cues have recently been shown to impact on the organization and mechanical properties of the Golgi apparatus [79],[84]•.

Mechanotransduction events at the Golgi apparatus may influence cell polarity. For instance, contractile forces induced by adhesion to the extracellular matrix were shown to modulate lipid metabolism through a pathway involving the sterol regulatory element binding protein (SREBP), a regulator of lipogenesis, and the Lipin-1 phosphatidate phosphatase that converts phosphatidic acid (PA) to diacylglycerol (DAG) [84]•. Since the rigidity of the Golgi apparatus also correlates with the level of acto-myosin contractility [61],[84]•, the physical properties of the Golgi apparatus may regulate the binding and/or activity of some of the components of this metabolic pathway. For instance, the level of DAG could influence membrane curvature [START_REF] Anitei | Spatiotemporal Control of Lipid Conversion, Actin-Based Mechanical Forces, and Curvature Sensors during Clathrin/AP-1-Coated Vesicle Biogenesis[END_REF] and in turn the binding of Arf1 or the activity of Lipin-1. Although not demonstrated yet, mechanosensitive pathways such as the Lipin-1/DAG/Arf1/SREBP pathway may be involved in polarity events activated by cell-matrix adhesion cues.

Concluding remarks and open questions

The Golgi apparatus plays a pivotal role in polarized cell functions. For instance, Golgi positioning and orientation control polarized membrane transport during cell migration or T-cell immunological synapse formation (Fig. 1A,C). We have described here the main molecular pathways controlling Golgi-driven polarity, according to which element of the Golgi is involved, Golgi-associated cytoskeleton and motors, the Golgi matrix or Golgi membranes. As these pathways are likely to interact, understanding how the actors identified so far work in concert and mechanically couple the different constituents of the Golgi apparatus is the main challenge for the coming years. Accordingly, a physical link between the Golgi matrix and the actin cytoskeleton implicating the golgin GCC88 and the CDC42 guanine exchange factor (GEF) ITSN-1 has recently been identified [START_REF] Makhoul | Intersectin-1 interacts with the golgin GCC88 to couple the actin network and Golgi architecture[END_REF]• (Fig. 3A). Interesting novel targets could also emerge. For instance, as part of the cytoskeleton, spectrins [START_REF] Beck | Spectrins and the Golgi[END_REF], septins [START_REF] Spiliotis | Epithelial polarity requires septin coupling of vesicle transport to polyglutamylated microtubules[END_REF], [START_REF] Song | This study investigates the potential involvement of septins in the structure and function of the Golgi apparatus. The authors show that septin 1 promotes Golgi positioning and anterograde trafficking by localizing at the cis-Golgi in a GM130-dependent manner, facilitating nucleation of microtubules and recruiting centrosomal proteins at the Golgi surface. 90. Etienne-Manneville S: Cytoplasmic Intermediate Filaments in Cell Biology[END_REF]•• and intermediate filaments [90] may fill some missing links in current models. While they are known to interact with the Golgi apparatus and participate in Golgi organization and membrane trafficking [START_REF] Beck | Spectrins and the Golgi[END_REF]90], it is not known whether their interaction with the Golgi apparatus is directly involved in cell polarity. Technical developments such as optogenetics, FRET-based probes or laser ablation, should be instrumental to better decipher how forces are generated at the Golgi apparatus during cell polarization. It is also tempting to speculate that mechanosensitive properties of the Golgi apparatus are key during establishment of cell polarity.

Finally, since cell polarity is deregulated in cancer, not surprisingly several polarity regulators associated with the Golgi apparatus have been implicated in cancer and invasion. The epithelial-to-mesenchymal transition (EMT) was recently shown to increase rearward positioning of the Golgi apparatus at the back of the nucleus in migrating breast cancer cells [START_REF] Natividad | Golgi Stabilization, Not Its Front-Rear Bias, Is Associated with EMT-Enhanced Fibrillar Migration[END_REF]. However, the increased migration of the cells correlates more with a stable positioning of the Golgi apparatus than with its position at the back or at the front of the nucleus [START_REF] Natividad | Golgi Stabilization, Not Its Front-Rear Bias, Is Associated with EMT-Enhanced Fibrillar Migration[END_REF]. GOLPH3 has been identified as an oncogene [68,[START_REF] Kuna | GOLPH3: a Golgi phosphatidylinositol(4)phosphate effector that directs vesicle trafficking and drives cancer[END_REF]. By driving Golgi reorientation and polarized trafficking, GOLPH3 enhances cell migration and cellular transformation [71]. Another protein implicated in cancer progression is Intraflagellar transport 20 (IFT20), which affects the nucleation of Golgi-derived microtubules and promotes intra-Golgi transport to induce invadopodia and tumor invasion [START_REF] Nishita | Ror2 Signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness[END_REF]. On the contrary, perturbing Golgi-derived microtubules by depleting CAMSAP2-AKAP450 in highly invasive fibrosarcoma cells diminishes their ability to migrate [START_REF] Wu | Molecular Pathway of Microtubule Organization at the Golgi Apparatus[END_REF]••. These findings point to polarity pathways associated with the Golgi apparatus as potential targets in cancer therapy.

This study shows that loss of GM130 in Purkinje neurons induces loss from the Golgi apparatus of GRASP65 and of AKAP450, a large Golgi and centrosomal protein which links the Golgi apparatus to the centrosome. GM130, although not involved in the initial polarization of Golgi trafficking, plays a central role in maintaining the polarized distribution of the Golgi apparatus in these cells by linking the Golgi apparatus to the centrosome.

28. • Tormanen K, Ton C, Waring BM, Wang K, Sütterlin C: Function of Golgicentrosome proximity in RPE-1 cells. PLoS One 2019, 14.

The authors use stable retinal pigment epithelial (RPE-1) cell lines in which GM130 is knocked out by CRISPR/Cas9 to show that the physical proximity between the centrosome and the Golgi apparatus is not necessary for protein transport, cell migration, or ciliogenesis.

This study demonstrates how CAMSAP2 organizes the microtubule network at the Golgi apparatus with the help of AKAP450 and myomegalin (MMG). In CAMSAP2 KO RPE-1 cells the localization of CAMSAP2-decorated microtubule stretches at the Golgi apparatus, depends on the AKAP450/MMG complex, ruling out a CLASPs-dependent interaction. The authors use AKAP450, MMG or CAMSAP2 KO cell lines and depletion of centrioles. In cells lacking centrosomes, enhanced interaction of -tubulin and microtubules with the Golgi apparatus is driven by AKAP450 and MMG. Cells lacking centrosomes and AKAP450 exhibit intact Golgi stacks and increased number of vesicles surrounding the Golgi apparatus, suggesting that vesicular trafficking, or at least the formation of transport intermediates, requires the presence of abundant Golgiderived microtubules. The authors show that the unconventional myosin motor myosin 18A (MYO18A) has no motor activity in the presence of GOLPH3, questioning the GOLPH3/MYO18A/actin model according to which actin-MYO18A contractility stretches the Golgi ribbon. Moreover, MYO18A does not appear to localize on the Golgi apparatus or to impact on Golgi morphology. Disrupting actin induces Golgi lateral compaction and vertical extension which is paralleled by similar morphological changes of the whole cell, suggesting that actin acts indireclty on Golgi morphology. Knockdown of the formin protein FHDC1/IFN1 is shown to perturb Golgi assembly in fibroblasts, a phenotype consistent with defects in Golgi-derived microtubules. Conversely, overexpression of FHDC1 induces the dispersion of the Golgi apparatus into functional ministacks. The authors explain these observations by a collaborative effect between the interaction of the microtubule-binding domain of FHDC1 with Golgiderived microtubules and the interaction between its FH2 domain with the actin cytoskeleton. Following their previous work on GOLPH3, the authors identify PtdIns(4)P as a critical Golgi lipid for anterograde trafficking from the Golgi apparatus to the plasma membrane by allowing GOLPH3 binding to Golgi membranes and subsequent membrane deformation. In vitro reconstitution experiments demonstrate that PtdIns(4)P is required for membrane curvature induced by GOLPH3. The authors show that a duo of Phosphatidylinositol transfer proteins (PITPs), PITPNA and PITPNB, drives the PtdIns(4)P-dependent recruitment of GOLPH3 in a redundant manner and also possibly recruits ceramide transfer protein (CERT) to Golgi membranes. The PITP/PtdIns(4)P/GOLPH3/CERT lipid signaling pathway appears to regulate apically directed membrane trafficking rather than bulk membrane trafficking in neural stem cells during neocortex development in mice. Interestingly CERT also plays an important role in Golgi positioning in these cells via a PtdIns(4)P-dependent mechanism. Downregulating CERT by shRNA perturbs both Golgi positioning and radial alignment phenocopying PITPNA/PITPNB or GOLPH3 deficiency phenotypes. However CERT does not operate via the GOLPH3/actin pathway and the downstream effectors of CERT associated with Golgi reorientation and/or polarity proteins remain to be identified. The authors identify a pathway involving the sterol regulatory element binding protein (SREBP), a regulator of lipogenesis, and the Lipin-1 phosphatidate phosphatase that converts phosphatidic acid (PA) to diacylglycerol (DAG) as a key mechanosensitive pathway linking extracellular physical constraints to the Golgi apparatus. High actomyosin contractility increases Lipin-1 activity and consequently DAG and Arf1 levels on Golgi membranes, preventing SREBP from shuttling from the ER to Golgi apparatus. Interestingly, a force directly applied on the Golgi apparatus using optical tweezers increases the amount of DAG on Golgi membranes mimicking the effects of increased contractility. Conversely, under reduced acto-myosin contractility, Lipin-1 is inhibited, SREBP accumulates in the Golgi apparatus where it is cleaved and then translocates to the nucleus where SREBP transcription factors are activated to promote lipid synthesis.

Figure legends

Figure 1 -Positioning of the Golgi apparatus in different contexts of cell polarity A. In most (but not all) migrating cell types, the Golgi apparatus is positioned with the centrosome in front of the nucleus in the direction of migration. Leucocytes are a notable exception. B. Epithelial cells exhibit baso-lateral polarity which relies on polarized membrane trafficking. In these cells, the Golgi apparatus is located between the nucleus and the apical surface. C. During the formation of an immunological synapse between a T-cell and a target antigen-presenting cell, the T-cell polarizes and its Golgi apparatus reorients towards the synapse to maintain polarized membrane trafficking towards establishing a target cell-T-cell contact. D. Transport in the axon from the cell body to the growth cone is crucial to maintain the polarized organization of neuronal cells. In pyramidal neurons, the position of the Golgi apparatus in the cell body correlates with the position of the main axon. E. Radial glial cells display a nonpericentrosomal Golgi positioning. The centrosome localizes close to the ventral side, while the Golgi apparatus is shifted towards the basal lamina close to the nucleus. Vesicular trafficking is mostly oriented perpendicular to the polarity axis in these cells. A number of actin regulators have been identified to localize at the Golgi apparatus. Among them, the formin family members FMLNL2/3 are regulated by CDC42, nucleate actin polymerization at the surface of the Golgi apparatus and participate in cell polarity. B. A main pathway involving Golgi-associated actin in Golgi architecture and in the polarization of membrane trafficking is the GOLPH3/MYO18A/F-actin pathway. Phosphatidylinositol-4-phosphate (PtdIns(4)P) and upstream lipid transfer proteins (PITPs and CERT) regulate this pathway.

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  75. LaFlamme SE, Mathew-Steiner S, Singh N, Colello-Borges D, Nieves B: Integrin and microtubule crosstalk in the regulation of cellular processes. Cell Mol Life Sci 2018, 75:4177-4185. 76. Seetharaman S, Etienne-Manneville S: Microtubules at focal adhesionsa double-edged sword. J Cell Sci 2019, 132:in press. 77. Mahamid J, Pfeffer S, Schaffer M, Villa E, Danev R, Cuellar LK, Förster F, Hyman AA, Plitzko JM, Baumeister W: Visualizing the molecular sociology at the HeLa cell nuclear periphery. Science (80-) 2016, 351:969-972. 78. • Copeland SJ, Thurston SF, Copeland JW: Actin-and microtubule-dependent regulation of Golgi morphology by FHDC1. Mol Biol Cell 2016, 27:260-276.

  79. Singh V, Erady C, Balasubramanian N: Cell-matrix adhesion controls Golgi organization and function through Arf1 activation in anchorage-dependent cells. J Cell Sci 2018, 131:jcs215855. 80. Shi M, Chen B, Mahajan D, Boh BK, Zhou Y, Dutta B, Tie HC, Sze SK, Wu G, Lu L: Amino acids stimulate the endosome-to-Golgi trafficking through Ragulator and small GTPase Arl5. Nat Commun 2018, 9. 81. Fourriere L, Kasri A, Gareil N, Bardin S, Bousquet H, Pereira D, Perez F, Goud B, Boncompain G, Miserey-Lenkei S: RAB6 and microtubules restrict protein secretion to focal adhesions. J Cell Biol 2019, 218:2215-2231. 82. • Rahajeng J, Kuna RS, Makowski SL, Tran TTT, Buschman MD, Li S, Cheng N, Ng MM, Field SJ: Efficient Golgi Forward Trafficking Requires GOLPH3.1016/j.devcel.2019.05.038.

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Figure 2 -

 2 Figure 2 -Golgi-associated microtubules A. The Golgi matrix protein GM130 bound to AKAP450 recruits the -TuRC binding proteins CEP215 and myomegalin (MMG). TuRC subsequent binding to CEP215 and MMG induces microtubule nucleation at the surface of the Golgi apparatus. B. The elongation of microtubules is associated with several microtubule-stabilizing proteins such as CLASPs. C. CAMSAP2 and end-binding proteins EB1/3 tether microtubules to the Golgi apparatus therefore regulating Golgi positioning and reorientation during directed cell migration. Abbreviation: MT, microtubule.

Figure 3 -

 3 Figure 3 -Golgi-associated actin A.A number of actin regulators have been identified to localize at the Golgi apparatus. Among them, the formin family members FMLNL2/3 are regulated by CDC42, nucleate actin polymerization at the surface of the Golgi apparatus and participate in cell polarity. B. A main pathway involving Golgi-associated actin in Golgi architecture and in the polarization of membrane trafficking is the GOLPH3/MYO18A/F-actin pathway. Phosphatidylinositol-4-phosphate (PtdIns(4)P) and upstream lipid transfer proteins (PITPs and CERT) regulate this pathway.

Acknowledgements

Y.Ravichandran is funded by the Polarnet ITN (Innovative Training Network) part of the European Commission and the Fondation pour la Recherche Médicale (FRM). We apologize to colleagues whose work we could not cite due to space limitations. The authors declare no conflict of interest.

Conflict of interest

The authors declare no conflict of interest.

B

Apico-basal polarityepitehial cells

C T-cell polarity E

Neuronal polarity -radial glial cells Neuronal polarity -pyramidal neurons


Mario Aricò

Jimmy Da Silva

Lucas Joseph

Ignacio Avellino

Philippe Gauthier

Jesus Mago

Eleonore Ferrier-Barbut

Guillaume Morel

Marie-Aude Vitrani

A surgical Cockpit for Minimally Invasive Surgery

The Surgical Cockpit is a robotized platform for Minimally Invasive Surgery targeting the treatment of diseases affecting the digestive, urologic and gynaecologic systems. The platform is designed to assist and enhance the surgeon's gesture without disrupting the customary surgical workflow, which is standardized according to the type of intervention. Existing surgical platforms feature a Master-Slave approach, where the surgeon remotely manipulates a master console that drives the instruments via a slave robot. On the contrary, the Surgical Cockpit does not cut off the close contact between the surgeon and their patient. The choice of lightweight, transparent robotic arms seamlessly fits into surgical frame: the robots are placed at the patient's bedside and hold the tools and the endoscope, both conveniently fixed at the end-effector through magnetic clippers. This configuration enables a robot-surgeon co-manipulation paradigm.

Introduction:

In classical laparoscopic routine, surgery is carried out by means of long instruments inserted into an inflated abdomen via a number of tiny skin incisions. The surgeon manipulates the instruments and supervises the task thanks to the visual feedback streamed by an endoscopic camera usually hold by a medicine resident. Such a type of surgery demands the dexterity to be adapted to the environmental constraints that limit the degrees of freedom in the task execution. In particular, the presence of a fixed entry point acts as a movement inverter and introduces a bias in the perception of the tissue stiffness. In addition, this inversion may introduce inefficiencies in the surgeon-resident interaction if the directional movements for the camera positioning are not clearly coded and stated. The platform we propose tackles several downsides of the classical approaches by assisting and/or enhancing the gesture of the surgeon. In particular, the presence of a dedicated endoscope holder enables the surgeon to fully control the camera without any accessory help.

Setup and Features:

The Surgical Cockpit consists of two lightweight, cable-driven, 6DoFs robotic arms. One arm holds the surgical tool, while the second arm holds the endoscopic camera. Their cable-driven actuation ensure a high back-drivability and, in turn, a high transparency when manipulating the arm, thanks to the negligible friction at the joint level. Both robots are able to self-register their position with respect to the entry point [START_REF] Dong | Robust trocar detection and localization during robot-assisted endoscopic surgery[END_REF]. They can sustain the weight of the tool/camera thanks to a gravity compensation module that compute the optimal balance force based on the current insertion level into the trocar. For safety reasons, no compensatory Cartesian moments are applied at the robot end-effector, to ensure a zero-sum force pulling along the skin the surrounds the trocar, perpendicularly to the insertion direction [START_REF] Dong | Assistance to laparoscopic surgery through comanipulation[END_REF]. Natural hand tremor, which is often magnified on the images, is filtered out thanks to a variable viscous field applied either at the instrument tip or handle: for fine movements, requiring a firm gesture, the felt viscosity increases to stabilize the tool, while for agile movements, the viscosity linearly decreases to minimize the perceived hindrance [START_REF] Dong | Assistance to laparoscopic surgery through comanipulation[END_REF]. Both robots are able to lock into a defined Cartesian position and keep the chosen position in a very accurate way: a low-gain integrator in the PID controller ensures that static errors are slowly balanced out and prevents the storage of high energy levels that could be transferred to the patient with harmful effects. However, for tele-manipulation modes (explained in the following), a non linear term is added to the control law to rapidly overcome non-linearities as friction at the entry point [START_REF] Mago | Safe teleoperation of a laparoscope holder with dynamic precision but low stiffness[END_REF]. The fulcrum point distorts the haptic feedback: tool-tissue interaction forces at the instrument tip can be either magnified or reduced depending on the current insertion depth. This can lead to involuntary excessive forces that can damage tissues or organs [START_REF] Gruijthuijsen | Leveraging the Fulcrum Point in Robotic Minimally Invasive Surgery[END_REF]. Sensorized tools can be used to send back a corrective force to the robotic instrument holder to restore the true interaction force felt by the surgeon [START_REF] Schmitty | Using comanipulation with active force feedback to undistort stiffness perception in laparoscopy[END_REF]. Several control modes have been implemented and tested for the intuitive control of the endoscope. The reference mode is the manual mode, where the surgeon can freely hand-manoeuvre with minimal friction. In case the endoscope is locked into a fixed position, a gentle pull will suffice to unlock it and reposition as deemed best. Image-based navigation can be achieved by displacing the camera via a tactile screen. The user inputs a direction UP/DOWN, LEFT/RIGHT by trailing the finger accordingly. Zoom IN/OUT commands are coded with a 2-finger gesture. The speed is also proportional to the amplitude of the finger movement. Automatic control can be achieved by controlling the endoscope with the surgical tool. In particular, the "Follow" mode ensures that the instrument tip is always visible on the image, preserving a constant position in the camera frame. The choice of the modality is partly automatic and partly commanded via a foot pedal. Moreover, a particular pose of the camera can be saved and the surgeon can restore it whenever desired through a tactile screen and pedal interface. Another important aspect of the research is the surgical learning process. Robot-assisted laparoscopic surgery is overtaking classic laparoscopic surgery: it allows to significantly increase the surgeon's performance while reducing physical/mental difficulties. Several studies have been carried out to analyse the motor skills developed when using the robot, and the impact on performance without the robot [START_REF] Candalh-Touta | How can we improve the Training of Laparoscopic Surgery thanks to the Knowledge in Robotics[END_REF].

Discussions:

The surgical cockpit is a co-manipulative robotic system for Minimally Invasive Surgery: it features two lightweight, back-drivable robotic arms that allows for safe manipulation of the tools. The surgeon benefits from low-level assistance, such as gravity compensation and trocar detection, up to more complex interaction modalities, such as endoscope manipulation through a tactile interface or automatic modalities. The platform design is centred around the patient's safety, which is the main decisional driver for the technical development. Such a setup is our starting point toward the development of Augmented Surgery, by embedding Augmented Reality applications, sensorized tools for enhanced haptic feedback and surgeon-centred human-machine interfaces.


Smaine Mazouzi
email: mazouzismaine@yahoo.fr

Zahia Guessoum
email: zahia.guessoum@lip6.fr

Fabien Michel
email: fmichel@lirmm.fr

A Distributed and Collective Approach for Curved Object-Based Range Image Segmentation

Keywords: Image segmentation, Multi-agent systems, Curved Object, Range image

In this paper, we use multi-agent paradigm in order to propose a new method of image segmentation. The images considered in this work are the range images which can contain at once polyhedral and curved objects. The proposed method uses a multi-agent approach where agents align the region borders to the surrounding surfaces which make emerging a collective segmentation of the image. The agents move on the image and when they arrive on the pixels of a region border they align these pixels to their respective surfaces. The resulting competitive alignment allows at once the emergence of the image edges and the disappearance of the noise regions. The test results obtained with real images show a good potential of the new method for accurate image segmentation.

Introduction

A range image represents the visible surface of a three-dimensional scene, where at each pixel of the image is stored the depth of the corresponding point of the scene. Range images are mainly used in recognition of 3D objects in robotic vision, because the 3D information, which is required for object recognition is immediately available. However, these images are recognized as being highly noised images [START_REF] Hoover | An experimental comparison of range image segmentation algorithms[END_REF] and are consequently hard to segment and to interpret. Several authors proposed methods of segmentation for this class of images [START_REF] Jiang | Edge detection in range images based on Scan Line approximation[END_REF][START_REF] Mazouzi | A new bayesian method for range image segmentation[END_REF]. However, most of these authors limited themselves to the images based on polyhedral objects. For these last ones, the detection of the regions of interest is widely easier compared with images containing curved objects [START_REF] Jiang | Edge detection in range images based on Scan Line approximation[END_REF].

Aiming at segmenting range images with both polyhedral and curved objects, we have appealed to multi-agent paradigm and more particularly to the reactive agents [START_REF] Ferber | Les systèmes multi-agents : vers une intelligence collective[END_REF]. We have used simple agents with weak granularity and having simple behavior which based on the mechanism of stimulus-reaction. The agents move on the image and act on the met pixels. An agent aligns the first not homogeneous pixel to the surface on which it moves. So, pixels belonging to the noise regions or situated on the circumferences of surfaces are systematically aligned to the surfaces which surround them. We show that the alternative alignment of pixels on the borders of regions allows preserving edges. On the other hand, because there is no pixel alignment within the noise regions, theses regions progressively disappear. This collective action of the agents allows the emergence of edges and the disappearance of the noise regions.

Most of the methods having used the agent paradigm [START_REF] Ballet | Edge detection using a multiagent system[END_REF][START_REF] Liu | Adaptive image segmentation with distributed behavior-based agents[END_REF][START_REF] Richard | Automated segmentation of human brain MR images using a multi-agent approach[END_REF][START_REF] Rodin | An immune oriented multi-agent system for biological image processing[END_REF][START_REF] Jones | Image enhancement, an emergent pattern formation approach via decentralised multi-agent systems[END_REF] are supervised and consequently they can be applied only to the images for which they were conceived. The method proposed in this paper is unsupervised. It makes no assumption on the number and the shape of the surfaces which compose objects in the image. This allows the adaptation of the method to any type of images by defining the criteria of homogeneity of the regions composing the treated images. The distribution of treatments and decision which characterize our approach, as well as the weak coupling of the reactive agents, offers a parallel method well suitable for real-time image interpretation. The experimentation of the method by using real images allowed to validate the new approach and to show its potential for an accurate and effective segmentation of range images.

The reminder of the paper is organized as follows: in Section 2 we present the main approaches having used multi-agent systems for image segmentation. Section 3 is devoted to the proposed approach. We present at first the criterion of homogeneity curved surfaces adopted in our case. Then, we introduce the principle of the multi-agent system and we show how a collective segmentation emerges form the simple and reactive behaviors of the agents. Our test results are introduced in the section 5, in which we show the the parameter selection and we comment on the obtained results. Finally, a conclusion summarizes our work and underlines its potential extensions.

Multi-agent Approches for Image Segmentation

Since the publication of the first works proposing multi-agent approaches for image processing, the cooperation and the interaction between agents represented the new contributions to deal with the problem of ambiguity which characterizes image visual data [START_REF] Ballet | Edge detection using a multiagent system[END_REF][START_REF] Liu | Adaptive image segmentation with distributed behavior-based agents[END_REF].

In the category of edge based segmentation methods using a reactive approach, Ballet et al. [START_REF] Ballet | Edge detection using a multiagent system[END_REF] have defined a multi-agent system for edge detection and following in 2D images. In this system an agent is situated on an extremum of the luminance gradient, then follows the crest of the edge and records its path in a shared memory. The previously recorded edge segments are used by other agents to initialize new edge segments or finish others. The method proposed by the authors is based on an original approach of parallel and distributed edge detection. However, the authors have not considered any mechanism of cooperation or coordination to strengthen the detection and improve the segmentation results.

The same authors [START_REF] Rodin | An immune oriented multi-agent system for biological image processing[END_REF] have resumed later the same approach and have extended it by using the multi-agent language oRis. By considering the a priori knowledge on the topology of regions in certain types of images, the agents follow the lines of gradient extremum. By considering two types of image regions, two categories of agents named respectively darkening agents and lightning agents are defined. According to their category, the agents follow respectively the dark regions or the light regions. By remaining on crest lines, the agents strengthen the difference of contrast between the pairs of neighboring regions. The proposed system is well dedicated to images containing roof edges (detected by the discontinuity of the first derivative of the image). Indeed, theses edges characterize the considered images by the authors.

The previous multi-agent approaches like most of edge based approches, have proceeded to detection without any region representation. This does not facilitate the region based segmentation of the treated images.

In the category of region based methods, Liu et al. [START_REF] Liu | Adaptive image segmentation with distributed behavior-based agents[END_REF] have used a reactive agent based system for the segmentation of Magnetic Resonance Images (MRI) of the brain. The authors used four types of agents, which correspond to the four tissues in the pathological cerebral matter. A first generation of agents is initialized inside the various tissues. Then, when every agent recognizes its region, it creates offspring agents and places them so that they are lucky to find more other homogeneous pixels. For the same type of images, Richard and his co-authors [START_REF] Richard | Automated segmentation of human brain MR images using a multi-agent approach[END_REF] proposed a multi-agent system were agents are organized hierarchically as follows: 1) One global control agent which partition the image volume in partial volumes; 2) Local control agents, allocated each one to a partial volume; 3) tissue dedicated agents, which work under the control of a local control agent, to segment the tissue inside a partial volume. So, the detection is performed at the lowest level by the tissue dedicated agents, then synthetized by the local control agents and the global control agent.

Like most of the region based approaches of image segmentation, the previous two works follow supervised approaches, where it is necessary to know the number of regions and their shapes. We introduce into this paper a new approach which is general and unsupervised for range image segmentation. We show that the competitive alignment of edges performed by reactive agents allows the emergence of a collective segmentation of an image. The proposed approach is unsupervised. It makes no preliminary assumption on the number or the nature of the regions which form the images to be segmented.

Image Segmentation by Edge Emergence

In order to do not make any assumption on the shape of regions, we have used the directional curvatures of surface, as the homogeneity criterion. Let a pixel (x, y), the two directional curvatures, respectively horizonal C h and vertical C v , are defined as follows:

C h (x, Y ) = - I (x, .) 1 + I 2 (x, .) (1) C v (X, y) = - I (., y) 1 + I 2 (., y) (2)
where I (x, .) and I (x, .) are the first and the second derivative of the image following the x axis, by fixing the value of y to Y . The same, I (., y) and I (., y) are the first and the second derivative of the image following the y axis, by fixing the value of x to X. C h expresses the curvature projection of the surface of the plane y = Y , while C v expresses the curvature projection of the surface on the plane x = X. A contiguous set R of pixels {(x k , y k ), k ∈ R} is considered homogenous, and represents an image region, if all of its pixels have, according to a given threshold T r c , the same directional curvatures:

∀k, l ∈ R; |C h (x k , y k ) -C h (x l , y l )| < T r c ∧ |C v (x k , y k ) -C v (x l , y l )| < T r c
T r c is a curvature comparison threshold where the value is automatically set at the stage of parameter learning (see Section 4). So, the pixels on interest, which are situated at the borders of the true regions or are in the noise regions, are detected when one of the two curvature C h ou C v changes.

System Dynamic

A high number of reactive agents (N =3500 see Section 4) are initialized at random positions in the image. After, agents start to move within the image following random directions. An agent searchs for an homogenous region around its current position (x c , y c ), by checking the last L visited pixels. The path length in pixels L (set at Section 4) allows the agent to be sure that it is within a homogenous region. If these last L pixels have all the same directional curvatures, the agent considers that it is within a homogenous region (CurrentRegion). It acquires then the ability to alter the image (AlterationAbility ← TRUE). This ability allows the agent to modify the depths of the encountered pixels. In its future moves, it smoothes the encountered pixels if these latter belong to the surface on which it currently moves. When the agent arrives on the first non homogenous pixel, it aligns this pixel to the current surface. The agent loses its alteration ability and restarts to search for a new homogenous region. The next algorithm introduces the method "step()" executed by an agent at every step on its path.

Initialisation :

AlterationAbility ← False (x c , y c ) ← (random(widthImg -1), random(heightImg -1)) l ← 0 // Set the path length

Noise Region Erasing and Edge Emergence

A noise region in a range image is either a homogenous region with weak size, or a non homogenous region formed by noise pixels having random or aberrant depths. In the case of a weak size, when it is crossed by an agent, this latter can not cover L homogenous contiguous pixels. When the region is formed only by noise pixels, an agent when crossing it does not find at least L homogenous pixels to be able to initialize a homogenous region whichever the diameter of the region. These regions are progressively erased by aligning their border pixels to the surrounding true regions. Indeed, when an agent comes on a pixel on the border of a noise region, it aligns this pixel and goes in this region. Since it could not cross L contiguous homogenous pixels, it remains incapable to alter pixels within the noise region. When it leaves this region, it does not align the first encountred pixel in the homogenous surrounding region. So, the border of the noise regions is then continually aligned from outside to the surrounding true regions. The noise regions will disappear after several times agents cross theses regions. Note that one noise region is surrounded by agents of a same group. Agents of this group are those moving on the true region which surrounds the noise region.

On the other hand, a segment of a thick edge, situated between two homogenous regions, is surrounded by two groups of agents. Agents of each group are situated entirely within only one region. Agents which cross the segment align the pixels of the segment border to the region from where they come. The edge segment between the two homogenous regions is thus continually thinned by the two groups of agents (Fig. 1a and1c).

When the edge becomes thin (one pixel wide), the agents of the two groups will become in competition to align the pixels of the thinned edge. Indeed, the pixels aligned by the agents of a giver group, let A in to the second region (B) by the agents of the second group. So, the pixels of the edge are continually switched between the two regions. Consequently, whichever the number of alignments of these pixels, they remain emergent in the image (Fig. 1d). Note that this result is not coded in any agent, but it emerges from the collective action of all the agents in the image. At the end of the process, noise regions are erased, and edges are thinned. So, a simple region growing controlled by the detected edges allows to produce a region based segmentation of the image.

Experimentation

We have used the framework proposed by Hoover et al. [START_REF] Hoover | An experimental comparison of range image segmentation algorithms[END_REF] to evaluate our approach, with range images from the set K2T containing both curved and polyhedral objects. All the images have a size of 640 × 480 pixels. A set of 10 range images was used to select the values of the used parameters: the number of agents N =3500; the path length L=7; and the curvature threshold T r c . The selected value correspond to the best segmentation, expressed as the number of the regions correctly detected, according to a ground truth (GT) segmentation [START_REF] Hoover | An experimental comparison of range image segmentation algorithms[END_REF].

In order to show how the noise regions are progressively erased and how edges are thinned, we show aligned pixels at regular intervals of time t. Figure 2a shows a sample of a range image. Figures 2b,2c,2d, 2e and 2f show the aligned pixels respectively at t=500,3500,7500,10500 and 13500. As the time progresses edges are detected and thinned, and noise regions are erased. Fig. 3 shows the average number of instances of correct detection corresponding respectively to our method (DCIS for Distributed and Collective Image Segmentation) and the method of EG (Edge based Segmentation), where authors have proposed a segmentation method for curved objects [START_REF] Jiang | Edge detection in range images based on Scan Line approximation[END_REF][START_REF] Jiang | Recent advances in range image segmentation[END_REF]. Theses results are obtained with the set K2T of images containing curved objets, and are computed according to a compare tool tolerance T , which is used to express the comparison tolerance. We can observe that our method records scores better than those of EG for T in {50%, 60%, 70% and 80%}. The two methods record equivalent scores for T in {90%,95%}.

Conclusion

We have proposed in this paper a new approach for edge detection and noise erasing in range images. This has allowed the segmentation of an image in its several homogenous regions. Combining the surface curvature and the competitive alignment of pixels has allowed to produce an accurate segmentation of images containing curved objects. These latter are recognized as difficult to segment in the case of range images. According to our approach, the detection of an edge segment results from the alternative alignment of its pixels. This alignment is performed by agents coming from the two regions. On the other hand, noise regions are progressively erased by the continuous alignment of the pixels of their borders to the homogenous surrounding regions. We think that the proposed approach could be applied to other types of images. For this, it's necessary to define a homogeneity criterion of regions in treated images.

  Fig 1b are immediately realigned

Fig. 1 .

 1 Fig. 1. Edge thinning (image abw.test.6). (a),(c) Edge pixels at t=800 ; (b),(d) Edge pixels at t= 8000.

Fig. 2 .

 2 Fig. 2. Segmentation Progression. (a) Rendered Range Image; (b) at t=500, (c) at t=3500 ; (d) at t=7500 ; (e) at t=10500 ; (f) at t=13500.

Fig. 3 .

 3 Fig. 3. Average number of correct detections in the set K2T for the two methods EG and DCIS according to T ; 50% ≤ T < 100%