Zine Eddine Latioui
email: zine.eddine.latioui@efrei.fr

Lamine Bougueroua
email: lamine.bougueroua@efrei.fr

Alain Moretto
email: alain.moretto@efrei.fr

Social Media Chatbot System -Beekeeping Case Study

Keywords: Text mining, deep learning, Social media data, Chatbot

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Introduction

Social Networks are indisputably popular nowadays and show no sign of slowdown.

According to the Kepios study [START_REF] Kepios | Digital in 2018, essential insights into internet, social media, mobile, and ecommerce use around the world[END_REF], the number of active users of social networks increased by 13% in 2017 to reach 3.3 billion users in April 2018. For example, Facebook attracts more than 2.2 billion users a month. Penetrating ever more aspects of our daily life, they become not only a considerable threat for our privacy, but also an encompassing tool for analyzing opinions, habits, trends and some would even saythoughts.

In the current growth of artificial intelligence, machine learning and natural language processing, driven by new technological possibilities, it is possible to automate the analysis of vast amounts of publicly published data.

Text Mining and Social Network Analysis have become a necessity for analyzing not only information but also the connections across them. The main objective is to identify the necessary information as efficiently as possible, finding the relationships between available information by applying algorithmic, statistical, and data management methods on the knowledge. The automation of sentiment detection on these social networks has gained attention for various purposes [START_REF] Ghiassi | Twitter brand sentiment analysis: A hybrid system using n-gram analysis and dynamic artificial neural network[END_REF][3] [START_REF] Salathé | The dynamics of health behavior sentiments on a large online social network[END_REF].

Sentiment Detection, or in its simplified form -Polarity Classification, is a tedious and complex task. Contextual changes of polarity indicating words, such as negation, sarcasm as well as weak syntactical structures make it troublesome for both machines and humans to safely determine polarity of social media messages.

Twitter is a social network that allows the user to freely publish short messages, called Tweets via the Internet, instant messaging or SMS. These messages are limited to 140 characters (more exactly, NFC normalized codepoints [START_REF] Sriram | Short text classification in twitter to improve information filtering[END_REF]). With about 330 million monthly active users (as of 2018, Twitter Inc.), Twitter is a leading social network, which is known for its ease of use for mobile devices (90% of users access the social network via mobile device). Note also, the more mature age of Twitter users: the most represented age group is 35-49 years old. Twitter known by the diversity of content, as well as its comprehensive list of APIs offered to developers.

With an average of 500 million messages sent per day, the platform seems ideal for live tracking opinions on various subjects. Furthermore, the very short format messages facilitate classification since short messages rarely discuss more than one topic. However, automated interpretation is complicated by embedded links, abbreviations and misspellings. Facing these challenges is becoming increasingly important for Economic and Market Intelligence in order to successfully recognize trends and threats.

We are interested in a particular use case; it concerns the sector of beekeeping. The importance of honeybees in agriculture has gained public attention in recent years, along with wide news coverage of their decline. Growing numbers of people are becoming concerned about the plight of honeybees. According to FranceAgrimer [START_REF] Proteis+ | Audit economique de la filière apicole française[END_REF], the average age of beekeepers in France is 42 years old.

The beekeeping industry faces many problems related to the health of bee colonies concomitant with a general decline in production. Scientific work focused on understanding these phenomena has allowed identifying several causes and establishing concrete elements to guide the decisions of beekeepers.

Due to pollution and climate change, experts confirmed that the massive destruction of marine creatures could occur very soon. Many terrestrial species are also exposed to the same fate. The death of the honeybees' population is considered the most important warning to humanity, as they play a more vital role in pollination (this is an important step in horticulture and agriculture).

In this paper, we will present an original method in order to help beekeepers take care of their apiary. Once consistent data from different sources are collected, a deep learning AI is run to give beekeepers advices trough a smart Chatbot.

This paper is structured as follows. In the first place, we discuss the state of art then we pass to describe the utilities and functionalities of our smartphone application in section 3. In section 4, we talk about text mining and data aggregation, and we end with a conclusion and some perspectives.

Related work

This idea is inspired by previous work in the domain of machine learning especially in deep learning where we could find a lot of interesting deep neural net applied to speech recognition needed in our application. We can mention for example [START_REF] Graves | Towards end-to-end speech recognition with recurrent neural networks[END_REF][8] [START_REF] Chan | Listen, attend and spell: A neural network for large vocabulary conversational speech recognition[END_REF], however we will be using Baidu deep speech 2 [START_REF] Amodei | Deep speech 2: End-to-end speech recognition in english and mandarin[END_REF] because they have proved its performance over two different languages (English and Mandarin). Since the approach is highly generic, it can be quickly be applied to new languages. Therefore, we suppose that it will be suitable for other languages like the French language, which is our main language.

Text mining is an active research area when it comes to web and social media data, as mentioned in [START_REF] Parikh | Movassate Sentiment analysis of user-generated twitter updates using various classification techniques[END_REF][12], people on social media such as Twitter don't pay much attention to their spelling or grammatical construction faults, as a result preprocessing these data is an irreversible step towards a valid mining system.

In this regards we intend to do as in [START_REF] Kharde | Sentiment analysis of twitter data: A survey of techniques[END_REF], so we will be using an n-gram model to correct the spelling and grammar faults, we replace the emoticons with their meaning and also we will remove punctuation, symbols, links, hashtags, targets, replace opinion phrases and idioms with their truth meaning, and also filter the language used in the tweet. Since we want to use machine-learning techniques to deal with this problem we first need to extract feature from the preprocessed tweets.

Different type of features are used in the literature, we note for example: using an ngram model to link words with their negative and positive probabilities.

System architecture

The core of our system is a Chatbot capable of sending valuable information to subscribed beekeepers by collecting and extracting data from blocks and from deferent sources. So that it could use the collected data to train machine learning model capable of generating advice or alerts to users in human understandable language.

Figure 1 shows the structure of our proposed model we can see that this system is composed of different parts; it consists of four major components:

 apiary(smartphone application),

 social media and web mining, (i) We use our application to collect real-time information from beekeepers that uses our application to control their apiaries.

 expertise rules,  Chatbot.
(ii) We applied text-mining approach to extract data from social media such as Twitter and filter it to keep the most relevant information.

(iii) At this stage, we use expert's knowledge to form some sort of rules. We thus create an expert agent.

(iv) The Chatbot ApiSoft is the main component of our system. Its mission is to dress beekeepers with eventual alerts or valuable information based on data provided from all other parts of the system.

A. Smartphone application (Apiaries)

The reason for creating this application is to help beekeepers manage their apiaries. At the same time, we can use data collected by this application to feed the Chatbot. For example, if there is a certain bee disease that has been located in a geographic area, then the Chatbot can notify all nearby beekeepers about that disease.

Fig. 2.

Deep neural network used for speech recognition [START_REF] Amodei | Deep speech 2: End-to-end speech recognition in english and mandarin[END_REF].

In this application, we have proposed a speech recognition system inspired by Baidu deep speech 2 [START_REF] Amodei | Deep speech 2: End-to-end speech recognition in english and mandarin[END_REF]. Figure 2 presents the structure of deep neural network we use. The first layers consist of convolutional ones since they have proved capable of extracting pertinent features.

After the convolutional step, we implemented bidirectional recurrent layers using Gated Recurrent Units (GRUs). GRU units are preferred to LSTMs since they consume much less energy and are easier to train compared to LSTMs. We finish with a one fully connected layer. Furthermore, we have used Connectionist Temporal Classification (CTC) loss function [START_REF] Graves | Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks[END_REF] to train our model. For performance reasons, we chose to use WrapCTC [START_REF] Amodei | Deep speech 2: End-to-end speech recognition in english and mandarin[END_REF]. The most challenging part in this deep learning approach was to find data for training since deep learning required more training data then traditional approaches.

With this Speech Recognition (SR) system, users are capable of wearing there bee uniforms and communicating commands and information about their beehives to this application over their voice, at the same time. They do not need to touch their phones so they are not bothered in their movements. One additional utility of this application consists in processing images data such in order to detect and count Varroa mites.

B. Social media and web mining

The block, described in figure 3, is responsible for collecting topic related data from the web particularly from social media like Twitter or Facebook. They represent major sources of data. Because of its data type and the number of users, we use a python client interface to connect to twitter API to search for tweets on a specific topic. For example, we can search for tweets containing words like apiary, honey, beekeeping, etc.

Fig. 3. Proposed structure for collecting and mining social media network data.

Twitter which is proved to be a great source of information [START_REF] Barbosa | Robust sentiment detection on twitter from biased and noisy data[END_REF][16] since it contains a large community and only handles short text data, which make it ideal of text mining techniques.

We perform an evaluation of the collected tweets, in which we will be using a probabilistic n-gram model to indicate the polarity of the tweet. This mechanism will allow us to extract knowledge or patterns and store it in our database so that we can use it to generate advice or alerts. Chatbot communicates all information to users.

C. Expertise rules

In this part, we take bee experts knowledge to form a sort of rules. We use these rules to build a decision tree. We uses this tree on information provided from other blocks, which can help us generate meaningful warnings and assistance.

We came to choose a decision tree since despite it does not require too much data; it is capable of handling multi output problems. Besides, the cost of implementing a tree is logarithmic which a gain in complexity.

First we begin by creating a web survey addressed to bee experts, to collect their knowledge in a format that we want, after that we pass to train the model using C5.0 which is a sophisticated data mining tool generally describe as if-else-rules [START_REF] Hou | Research on C5. 0 algorithm improvement and the test in lightning disaster statistics[END_REF].

D. Chatbot

This is the main component of our system. It uses all information and approaches accumulated from other blocks, to generate human comprehensive text.

To create a system capable of generating human understandable content we will be using a sequence-to-sequence neural net. We came to this chose as these models provide versatility compared to traditional machine learning methods that required a fixed output length. The generated message is then broadcasted to all concerned beekeepers so that it can help them while they maintain their apiary.

Results and Discussion

In this study, we are interested in the voice recognition part. We first, we speak about hotword detection where we try to detect specific word if this word is pronounced. In order to select the suited system we tested two methods Snowboy detection and CMU Sphinx.

Snowboy: is a personalized real-time deep neural network capable of identifying hotword from continues speech. The advantage of this library is that it uses insignificant computing power that makes it capable of working even in Raspberry Pi of the first generation.

The second toolkit is CMU Sphinx, which is mainly a full speech recognition system. It also offers a special mode that makes it able to detect targeted words.

We tested the performance between this two libraries by a dataset containing words like hey google, Apisoft etc. we have used confusion matrix (shown in figure Fig. 4) as a metric of performance evaluation.

Fig. 4. Confusion matrix

We can clearly see that in term of hotword detection Snowboy is clearly a better approach with 95 % of accuracy compared to 64% for CMU Sphinx. For speech recognition, we have also tested two approaches. In orders to discuss whatever to choose of using CMU sphinx completes speech recognition or an end-toend deep neural network.

The first approach is based on the classical pipeline of a typical speech recognition system which counting an acoustic model. In the case of CMU Sphinx, they have used a Hidden Markov model capable of converting a set of audio features into a list phonemes, the second component is a dictionary to do the mapping between the phonemes the worlds, the last component is the language model it's trying to minimize vocabulary and grammatical errors.

The second approach is a deep recurrent neural network that we trained based on deep speech two architecture we have used 50 hours of training data (mainly VoxForge dataset plus books reading samples). Since we do not really have a large amount of data, we just keep the network as simple as possible with three convolutional layers followed by a bidirectional neural network.

We did a comparison of these two methods described above. the figure 5 show the WER (Word error Rate) by the length of sentences for the two systems we can see that CMU Sphinx, in general, is still a bit better than the end to end DNN approach with 32% compared to 35% for the neural network. We think that this is due to the quantity of data we have. Since the end to end, DNN approaches generally required a larger dataset to train. However, we will interpret the data problem, considering we have some collaborators that are willing to give us the necessary data to train a <10% WER Speech recognition system based on this approach.

Conclusion

In this paper, we have presented a novel way capable of helping beekeepers to control their apiary by communicating to users' notifications about the state of apiaries in their respective areas and inform them if there is a phenomenon to consider.

Our method based on machine learning and text mining techniques tries to build a Chatbot that collects data from various sources such as social media, experts and real data (different types of sensors in hives) collected by smartphone application. We think this approach will continue to improve as this system continues to work and training.

At last, we expect that this system will give valuable aids in the beekeeping process. We also hope that our solution will contribute to the improvement of the quantity and quality of honey production and will participate in the prevention against the extinction of honeybees.

Fig. 1 .

 1 Fig. 1. General model structure.

Fig. 5 .

 5 Fig. 5. Word error Rate by the length of sentences


Motohide Murate
email: motohide.murate@unistra.fr

Nario Tomishige
email: nario.tomishige@unistra.fr

Toshihide Kobayashi
email: toshihide.kobayashi@unistra.fr

Wrapping axons in mammals and Drosophila: different lipids, same principle

Keywords: CerS, ceramide synthase, CGT, UDP-galactose ceramide galactosyltransferase (GalCer synthase), CNS, central nervous system, CPE, ceramide phosphoethanolamine, DPH, 1,6-diphenyl-1,3 ceramide phosphoethanolamine, galactosylceramide, glial ensheathment, myelin Highlights

Plasma membranes of axon-wrapping glial cells develop specific cylindrical bilayer membranes that surround thin individual axons or axon bundles. Axons are wrapped with single layered glial cells in lower organisms whereas in the mammalian nervous system, axons are surrounded with a characteristic complex multilamellar myelin structure. The high content of lipids in myelin suggests that lipids play crucial roles in the structure and function of myelin.

The most striking feature of myelin lipids is the high content of galactosylceramide (GalCer).

Serological and genetic studies indicate that GalCer plays a key role in the formation and function of the myelin sheath in mammals. In contrast to mammals, Drosophila lacks GalCer.

Instead of GalCer, ceramide phosphoethanolamine (CPE) has an important role to ensheath axons with glial cells in Drosophila. GalCer and CPE share similar physical properties: both lipids have a high phase transition temperature and high packing, are immiscible with cholesterol and form helical liposomes. These properties are caused by both the strong headgroup interactions and the tight packing resulting from the small size of the headgroup and the hydrogen bonds between lipid molecules. These results suggest that mammals and Drosophila wrap axons using different lipids but the same conserved principle.

Introduction

Neurons establish an elaborate network to build a comprehensive nervous system in the body. Each neuron receives chemical information at the synapse and propagates it to the nerve terminal through the axon fibre as an action potential that is generated by voltage-gated ion channels. The action potential emitted from one axon is small and localized. To achieve rapid and distant neural transmission and to block the leakage of electric current, axons are surrounded by glial cells that provide an electric insulation barrier.

Axons are wrapped with single layered glial cells in juvenile acoel [START_REF] Bery | Structure of the central nervous system of a juvenile acoel, Symsagittifera roscoffensis[END_REF], spiny lobster [2],

housefly [START_REF] Saint Marie | The fine structure of neuroglia in the lamina ganglionaris of the housefly, Musca domestica L[END_REF] and Drosophila [START_REF] Banerjee | Glial ensheathment of peripheral axons in Drosophila[END_REF]. In contrast, in the mammalian peripheral nervous system (PNS), axons are surrounded with a characteristic complex multilamellar myelin structure formed by specific glial cells called Schwann cells. PNS is also wrapped with non-myelinating Schwann cells, such as Remak Schwann cells, terminal Schwann cells and enteric glia [START_REF] Harty | Unwrapping the unappreciated: recent progress in Remak Schwann cell biology[END_REF]. In the central nervous system (CNS) of gnatostomata (jawed vertebrates) but not in agnathans (jawless vertebrates), axons are wrapped by myelins formed by oligodendrocytes [START_REF] Bullock | Evolution of myelin sheaths: both lamprey and hagfish lack myelin[END_REF][START_REF] Weil | Axonal Ensheathment in the Nervous System of Lamprey: Implications for the Evolution of Myelinating Glia[END_REF].

Myelin-like structures are also found in invertebrates such as Annelida (leeches [START_REF] Coggeshall | The Fine Structure of the Central Nervous System of the Leech, Hirudo Medicinalis[END_REF] and earthworms [START_REF] Hama | Some observations on the fine structure of the giant nerve fibers of the earthworm, Eisenia foetida[END_REF][START_REF] Roots | Myelinating glia of earthworm giant axons: thermally induced intramembranous changes[END_REF]), Mollusca (squids [START_REF] Geren | The Structure of the Schwann Cell and Its Relation to the Axon in Certain Invertebrate Nerve Fibers[END_REF]), Crustacea (prawns [START_REF] Heuser | The fine structural organization of nerve fibers, sheaths, and glial cells in the prawn, Palaemonetes vulgaris[END_REF], lobsters [START_REF] Govind | Growth of lobster giant axons: correlation between conduction velocity and axon diameter[END_REF], shrimps [START_REF] Hama | The fine structure of the Schwann cell sheath of the nerve fiber in the shrimp (Penaeus japonicus)[END_REF] and crabs [START_REF] Mc | The fine structure of Schwann cells, nodes of Ranvier and Schmidt-Lanterman incisures in the central nervous system of the crab, Cancer irroratus[END_REF]) and Arthropoda (cockroaches [START_REF] Hess | The fine structure of nerve cells and fibers, neuroglia, and sheaths of the ganglion chain in the cockroach (Periplaneta americana)[END_REF]).

Plasma membranes of axon-wrapping glial cells develop specific cylindrical bilayer membranes to surround thin individual axon or axon bundles. It is speculated that glial cells from different animal species share the same principle to organize membranes. However, our knowledge on the composition and distribution of plasma membrane components in glial cells is limited to a few animal species.

Myelination is a complex and developmentally regulated process to form a concentric wrapping of axons by a continuous thin layer from which cytoplasm has mostly been excluded.

While a set of proteins and lipids in myelinating glial cells co-ordinately functions in myelin formation and maintenance, its cylindrical multilamellar structure is thought to be provided with high stability by the large amounts of lipid constituents. Approximately 70% of the mammalian myelin membrane is composed of lipids [START_REF] Gent | The Lipid-Protein Unit in Myelin[END_REF][START_REF] Norton | The Chemical Composition of Bovine Cns Myelin[END_REF][START_REF] O'brien | Lipid composition of the normal human brain: gray matter, white matter, and myelin[END_REF][START_REF] Norton | Myelination in rat brain: changes in myelin composition during brain maturation[END_REF][START_REF] Devries | Lipid composition of axolemma-enriched fractions from human brains[END_REF][START_REF] Svennerholm | Membrane lipids of human peripheral nerve and spinal cord[END_REF]. This value is extremely high, compared to that of plasma membranes from other cell types (red blood cells: 30% [START_REF] De | Some lipid characteristics of red cell membranes of various animal species[END_REF][START_REF] Dodge | The preparation and chemical characteristics of hemoglobin-free ghosts of human erythrocytes[END_REF], Baby Hamster Kidney cell line: 30-60 % [START_REF] Klenk | Lipids of plasma membranes of monkey and hamster kidney cells and of parainfluenza virions grown in these cells[END_REF][START_REF] Renkonen | The lipids of the plasma membranes and endoplasmic reticulum from cultured baby hamster kidney cells (BHK21)[END_REF], rat liver: 40% [START_REF] Ray | Lipid composition of rat liver plasma membranes[END_REF]). The high content of lipids in myelin also suggests that lipids play crucial roles in the structure and function of myelin. Myelin sheaths of both CNS and PNS from mouse and human exhibit unique lipid compositions. High content of cholesterol (Chol) (27-28%) in myelin sheaths from CNS and PNS and low sphingomyelin (SM) content in myelins from CNS have been reported [START_REF] Norton | Myelination in rat brain: changes in myelin composition during brain maturation[END_REF]. However, the most striking feature of myelin lipids is the high content of two kinds of glycosphingolipids, galactosylceramide (GalCer) (Fig. 1), galactose-conjugated ceramide, and its sulfated derivative, 3-O-sulfogalactosylceramide (sulfatide). GalCer and sulfatide account for 20-24% and 3-7% of total lipids, respectively [START_REF] Garbay | Myelin synthesis in the peripheral nervous system[END_REF][START_REF] Ozgen | Oligodendroglial membrane dynamics in relation to myelin biogenesis[END_REF]. GalCer is not myelin-specific and is also distributed in the plasma membrane of non-myelinating, but axon-wrapping Remak Schwann cells [START_REF] Jessen | Axonal signals regulate the differentiation of non-myelin-forming Schwann cells: an immunohistochemical study of galactocerebroside in transected and regenerating nerves[END_REF]. The amounts of GalCer and sulfatide in neurons are much lower than those in axon-wrapping glial cells [START_REF] Raghavan | Ceramide galactoside of enriched neuronal and glial fractions from rat brain[END_REF]. GalCer is expressed from the very early stage of development in oligodendrocytes and Schwann cells, prior to the formation of myelin and the expression of myelin basic protein (MBP), the key protein that establishes the structure of the myelin sheath [START_REF] Mirsky | Myelin-specific proteins and glycolipids in rat Schwann cells and oligodendrocytes in culture[END_REF][START_REF] Ranscht | Development of oligodendrocytes and Schwann cells studied with a monoclonal antibody against galactocerebroside[END_REF].

Binding of anti-GalCer antibodies [START_REF] Raff | Cell-type-specific markers for distinguishing and studying neurons and the major classes of glial cells in culture[END_REF][START_REF] Zalc | Immunohistochemical localization of galactosyl and sulfogalactosyl ceramide in the brain of the 30-day-old mouse[END_REF] and accessibility to galactose oxidase and sodium periodate [START_REF] Linington | Accessibility of galactosyl ceramides to probe reagents in central nervous system myelin[END_REF] indicate that GalCer is exposed to the cell surface of myelin. In isolated central nerve myelin, 50 % of GalCer was assessable to galactose oxidase, whereas 90 % of GalCer was attacked by sodium periodate [START_REF] Linington | Accessibility of galactosyl ceramides to probe reagents in central nervous system myelin[END_REF]. Currently, the possibility of the presence of GalCer in the cytoplasmic leaflet is not excluded. Asymmetric distribution of other lipid components of myelin is also reported. Treatment with mercury chloride and X-ray diffraction analysis of sciatic nerve myelin revealed that phosphatidylethanolamine (PE) plasmalogen was preferentially localized in the inner leaflets [START_REF] Kirschner | Myelin labeled with mercuric chloride. Asymmetric localization of phosphatidylethanolamine plasmalogen[END_REF]. Using Schwann cell line, it was indicated that 90% of SM and phosphatidylcholine (PC) were localized in the outer leaflet, whereas PE, phosphatidylserine (PS) and phosphatidylinositol were distributed mainly in the inner leaflet (85%, 96% and 69%, respectively) of the plasma membrane [START_REF] Calderon | Lipid composition and phospholipid asymmetry of membranes from a Schwann cell line[END_REF].

In contrast to the extensive characterization of lipids in mammalian myelin, information on the lipid composition of wrapping glia in invertebrate is limited. Lipid composition is diverse in different animal species and GalCer is limited only in deuterostomia [START_REF] Okamura | Phylogenetic dichotomy of nerve glycosphingolipids[END_REF]. Shrimp myelin is enriched with glucosylceramide (GlcCer), which is glucose-conjugated ceramide, instead of GalCer [START_REF] Okamura | Phylogenetic dichotomy of nerve glycosphingolipids[END_REF][START_REF] Shimomura | An unusual glucocerebroside in the crustacean nervous system[END_REF][START_REF] Okamura | Isolation and characterization of multilayered sheath membrane rich in glucocerebroside from shrimp ventral nerve[END_REF]. In Drosophila, ceramide phosphoethanolamine (CPE), which is phosphoethanolamine-conjugated ceramide (Fig. 1) has an important role to ensheath axons by wrapping glial cells in PNS [START_REF] Ghosh | A Global In Vivo Drosophila RNAi Screen Identifies a Key Role of Ceramide Phosphoethanolamine for Glial Ensheathment of Axons[END_REF]. CPE is a relatively low-abundance lipid in membranes, constituting only 4% of the brain in fly [START_REF] Carvalho | Effects of diet and development on the Drosophila lipidome[END_REF]. However, a recently discovered CPE-specific protein conjugated with EGFP (pleurotolysin A2 (PlyA2)-EGFP) revealed selective labelling of glial cells, indicating enrichment of CPE in glial cells [START_REF] Bhat | Evaluation of aegerolysins as novel tools to detect and visualize ceramide phosphoethanolamine, a major sphingolipid in invertebrates[END_REF]. Labelling cultured Kc167

Drosophila cells with PlyA2-EGFP followed by SDS-FRL (SDS-digested freeze-fracture replica labelling) [START_REF] Murate | Transbilayer distribution of lipids at nano scale[END_REF] revealed that CPE is highly enriched in the exoplasmic leaflet of the plasma membrane [START_REF] Bhat | Evaluation of aegerolysins as novel tools to detect and visualize ceramide phosphoethanolamine, a major sphingolipid in invertebrates[END_REF]. PE is the most abundant phospholipid in Drosophila, accounting for 55% of the total phospholipids. Due to this abundance, PE cannot be localized in a single leaflet. Indeed, SDS-FRL showed that 63 % of PE was localized in the outer leaflet of the Kc167 cell plasma membrane (Murate, unpublished).

In this review, we summarize the roles of GalCer and CPE on the ensheathment of axons in mammalian cells and Drosophila. We will also compare the physical properties of GalCer, GlcCer and CPE and discuss whether there is the conserved physical principle to wrap axons.

Role of lipids in wrapping axons in vertebrates

Role of GalCer in axon ensheathment

The structure of the GalCer molecule is composed of galactose, sphingosine and fatty acid (Fig. 1). The sphingosine moiety of GalCer is mainly composed of C18:1 sphingosine [START_REF] Dawson | Mass spectrometry of neutral, mono-and disialoglycosphingolipids[END_REF].

Fatty acids of GalCer consist of nearly equal amounts of fatty acid (non-hydroxy fatty acid, NFA) and sphingolipid-specific 2-hydroxy fatty acid (HFA) in adult mammals [START_REF] Svennerholm | Membrane lipids of human peripheral nerve and spinal cord[END_REF][START_REF] Hoshi | Characterization of brain cerebrosides at early stages of development in the rat[END_REF]. In contrast, HFA is present in proportions as low as 8 % in the early stage of myelination [START_REF] Hoshi | Characterization of brain cerebrosides at early stages of development in the rat[END_REF].

Anti-GalCer antibody was shown to inhibit myelination in cells and tissues of both the CNS and the PNS [START_REF] Kies | Myelination inhibition factor: dissociation from induction of experimental allergic encephalomyelitis[END_REF][START_REF] Fry | Cerebroside antibody inhibits sulfatide synthesis and myelination and demyelinates in cord tissue cultures[END_REF]. The application of anti-GalCer antibody to cultured oligodendrocytes prevented theproduction of membrane sheets. This effect was diminished after the removal of antibody [START_REF] Dyer | Antibody to galactocerebroside alters organization of oligodendroglial membrane sheets in culture[END_REF]. Myelination was inhibited by anti-GalCer antibody when Schwann cells were co-cultured with nerve cells. However, Schwann cells kept contacts with neurons and surrounded the axons by one turn of the plasma membrane under this condition [START_REF] Ranscht | Inhibition of in vitro peripheral myelin formation by monoclonal anti-galactocerebroside[END_REF]. Inhibition of myelination by anti-GalCer antibody was also observed in an organ culture of the cerebellum [START_REF] Dorfman | Cerebroside antibody titers in antisera capable of myelination inhibition and demyelination[END_REF]. In addition to inhibiting myelination, anti-GalCer antibody accumulated MBP underneath the GalCer clusters, changed F-actin and microtubule distribution and induced calcium flux [START_REF] Dyer | Glycolipids and transmembrane signaling: antibodies to galactocerebroside cause an influx of calcium in oligodendrocytes[END_REF].

These studies suggest that GalCer plays a key role in the formation and function of the myelin sheath.

GalCer biosynthesis is catalysed by UDP-galactose ceramide galactosyltransferase (GalCer synthase, CGT), which catalyses the transfer of galactose to ceramide and, lesser extent, to diacylglycerol [START_REF] Van Der Bijl | Synthesis of non-hydroxy-galactosylceramides and galactosyldiglycerides by hydroxy-ceramide galactosyltransferase[END_REF]. GalCer is also a precursor of sulfatide. In fact, CGT-KO mice are deficient in not only GalCer but also sulfatide and GalDAG [START_REF] Bosio | Composition and biophysical properties of myelin lipid define the neurological defects in galactocerebroside-and sulfatide-deficient mice[END_REF]. Although the experiments using anti-GalCer antibodies suggest the importance of GalCer in myelination, CGT-KO mice exhibited myelinated axons in both the CNS and the PNS [START_REF] Bosio | Functional breakdown of the lipid bilayer of the myelin membrane in central and peripheral nervous system by disrupted galactocerebroside synthesis[END_REF][START_REF] Coetzee | Myelination in the absence of galactocerebroside and sulfatide: normal structure with abnormal function and regional instability[END_REF]. In young mice, the density of layers and the distance between each layer of myelin in KO mice had no differences from those of control animals. However, the old KO mice showed decreased thickness of myelin up to approximately 70%, wider space between each layer, and vacuolation in the myelin sheath. In addition, there was a significant increase in the number of non-myelinated axons in old KO mice [START_REF] Marcus | Effects of galactolipid elimination on oligodendrocyte development and myelination[END_REF]. At the same time, KO mice displayed tremor and paralysis of hindlimbs. Myelin lipid analyses indicated that HFA-containing GlcCer and -SM were accumulated in the CNS myelin of CGT-KO mice [START_REF] Coetzee | Myelination in the absence of galactocerebroside and sulfatide: normal structure with abnormal function and regional instability[END_REF]. GlcCer is synthesized by UDP-glucose ceramide glucosyltransferase (GlcCer synthase, UGCG). GlcCer is hardly detected in the myelin of normal mice. Mice that lack UGCG in myelin-producing cells were analysed in the CGT-KO background. They exhibited increased amounts of PC, PE, PS and ceramide, but no difference in SM contents in CNS myelin compared to CGT-KO mice. Myelin abnormalities were not accelerated by the lack of GlcCer in oligodendrocytes [START_REF] Saadat | Absence of oligodendroglial glucosylceramide synthesis does not result in CNS myelin abnormalities or alter the dysmyelinating phenotype of CGT-deficient mice[END_REF]. Myelin ultrastructure, behavioural phenotype and lipid contents observed in CGT-KO mice were rescued by restricted expression of CGT in myelin-producing cells (oligodendrocytes and Schwann cells) in the CGT-deficient background, except for the increase in NFA-GalCer in old animals [START_REF] Zoller | Oligodendrocyte-specific ceramide galactosyltransferase (CGT) expression phenotypically rescues CGT-deficient mice and demonstrates that CGT activity does not limit brain galactosylceramide level[END_REF].

Sulfatide is synthesized from GalCer by adding a sulfate group. This reaction is catalysed by cerebroside sulfotransferase (CST). Lipid analysis of CST-KO mice demonstrated the complete absence of sulfatide, but no change in other glycolipids and phospholipids [START_REF] Honke | Paranodal junction formation and spermatogenesis require sulfoglycolipids[END_REF][START_REF] Wang | Alterations in mouse brain lipidome after disruption of CST gene: a lipidomics study[END_REF]. CST-KO mice displayed thinner myelin sheath, vacuolation of myelin and decreased velocity of nerve conduction [START_REF] Honke | Paranodal junction formation and spermatogenesis require sulfoglycolipids[END_REF][START_REF] Marcus | Sulfatide is essential for the maintenance of CNS myelin and axon structure[END_REF]. However, compared to CGT-KO, the effect was less significant. In addition, no obvious symptom of demyelination was detected in the PNS of CST-KO old animals, indicating the stability of myelin [START_REF] Ishibashi | A myelin galactolipid, sulfatide, is essential for maintenance of ion channels on myelinated axon but not essential for initial cluster formation[END_REF]. The CST-deficient mice showed distinct tremor and ataxia with age but were able to survive longer than CGT-KO mice.

Role of HFA in the formation and maintenance of myelin

Unlike mammalian myelin, the myelins of several Caudata (urodeles, Necturus (salamander) and Notophthalmus (newt)) lack HFA-containing GalCer and sulfatide although they contain NFA counterparts. Compared to the reptile Anolis (chameleon), which contains HFA-GalCer and -sulfatide, Urodeles showed reduction in nerve conduction velocity and unusual myelin thickness [START_REF] Ki | Structure and function of urodele myelin lacking alpha-hydroxy fatty acid-containing galactosphingolipids: slow nerve conduction and unusual myelin thickness[END_REF], suggesting the importance of HFA in the structure and function of myelin. An anti-GalCer monoclonal antibody that binds to HFA-GalCer but not to NFA-GalCer has been reported, suggesting that the conformation of GalCer is influenced by the presence of hydroxyl residue at the 2 position of the constituent fatty acid [START_REF] Nakakuma | Monoclonal antibody to galactosylceramide: discrimination of structural difference in the ceramide moiety[END_REF].

The 2-hydroxy group of HFA is incorporated into NFA by the enzyme fatty acid 2-hydroxylase (FA2H). FA2H is expressed in oligodendrocytes and Schwann cells, and the increase in its activity parallels the time of the myelination [START_REF] Eckhardt | A mammalian fatty acid hydroxylase responsible for the formation of alpha-hydroxylated galactosylceramide in myelin[END_REF][START_REF] Alderson | FA2H-dependent fatty acid 2-hydroxylation in postnatal mouse brain[END_REF]. Myelin from mice that lack FA2H showed no morphological and functional differences from control in young animals.

However, in old animals, myelin stability was damaged in CNS, leading to demyelination.

Demyelination was not observed in PNS [START_REF] Zoller | Absence of 2-hydroxylated sphingolipids is compatible with normal neural development but causes late-onset axon and myelin sheath degeneration[END_REF]. Similar results were obtained from oligodendrocyte-specific conditional FA2H-KO mice [START_REF] Potter | Central nervous system dysfunction in a mouse model of FA2H deficiency[END_REF]. Loss of HFA-GalCer and -sulfatide in FA2H-KO was not accompanied by the increase in NFA-galactosphingolipids. As a result, galactolipids were decreased to 60 % of control in FA2H-KO mice. Interestingly, mice with overexpression of CGT displayed increased amounts of GalCer and sulfatide with NFA, and concomitant decrease in HFA-containing counterparts. Thus, the total amount of galactosphingolipids was not changed from control animals. CGT-overexpressing mice showed demyelination and vacuolation in myelin sheaths of both the CNS and the PNS, with serious consequences in the CNS [START_REF] Fewou | Reversal of non-hydroxy:alpha-hydroxy galactosylceramide ratio and unstable myelin in transgenic mice overexpressing UDP-galactose:ceramide galactosyltransferase[END_REF]. The change of the NFA/HFA ratio in GalCer was also observed in oligodendrocyte-specific overexpression of CGT in a wild-type background [START_REF] Zoller | Oligodendrocyte-specific ceramide galactosyltransferase (CGT) expression phenotypically rescues CGT-deficient mice and demonstrates that CGT activity does not limit brain galactosylceramide level[END_REF].

Loss of GalCer and sulfatide in CGT-KO mice is accompanied by upregulation of HFA-GlcCer and HFA-SM in myelin. CGT/FA2H double KO mice lack GalCer, sulfatide, HFA-GlcCer and HFA-SM. In addition, 60-80% of NFA-GlcCer disappeared and very long NFA-containing SM was significantly accumulated in the CNS and PNS myelin. Nevertheless, a severe phenotype in myelin was not observed biochemically and morphologically in double mutant mice compared to CGT-KO mice. The weight of myelin and the ratio of myelin thickness against the axon diameter were indistinguishable in both mutants. In addition, there was no obvious behavioural defect in double KO mice compared to CGT-KO mice [START_REF] Meixner | Myelination in the absence of UDP-galactose:ceramide galactosyl-transferase and fatty acid 2 -hydroxylase[END_REF].

Role of very-long-chain fatty acids in the formation and maintenance of myelin

In bovine brain GalCer, the N-linked fatty acids in HFA-GalCer are composed of 15% of C24:1 (here 24 is the number of carbons and 1 means one double bond), 30% of C24:0 and 16% of C18:0, while those in NFA-GalCer are composed of 40% of C24:1, 17% of C24:0 and 6% of C18:0 [START_REF] O'brien | The fatty acid composition of brain sphingolipids: sphingomyelin, ceramide, cerebroside, and cerebroside sulfate[END_REF]. Several enzymes contribute to the formation of long chain GalCer. Ceramide synthase (CerS) catalyses the acylation of dehydrosphingosine using acyl-CoA as a fatty acid donor. There are six isoforms of CerSs that utilize different acyl-CoA with defined chain lengths in mammals. Among them, ceramide synthase 2 (CerS2) is responsible for the synthesis of ceramides with very-long-chain fatty acids (C22-C24). CerS2 is highly expressed in oligodendrocytes and Schwann cells, and its expression parallels the myelination [START_REF] Becker | Differential expression of (dihydro)ceramide synthases in mouse brain: oligodendrocyte-specific expression of CerS2/Lass2[END_REF]. In CerS2-KO mice, demyelination was clearly detected in the brain, and disarranged stacks of myelin membranes were observed between the localized regions of the inner surfaces of myelin sheaths and neuronal membranes of 20% of PNS axons. Lipidomics analyses revealed that the amounts of both HFA-and NFA-GalCer with C22:0, C24:0 and C24:1 were reduced to very low or undetectable levels. Conversely, GalCer with C16:0, and ceramide with C16:0 and C20:0 were increased in the brain. In addition, the total amounts of GalCer and sulfatide were decreased in both the CNS and the PNS [START_REF] Imgrund | Adult ceramide synthase 2 (CERS2)-deficient mice exhibit myelin sheath defects, cerebellar degeneration, and hepatocarcinomas[END_REF][START_REF] Ben-David | Encephalopathy caused by ablation of very long acyl chain ceramide synthesis may be largely due to reduced galactosylceramide levels[END_REF].

Very-long-chain fatty acids (>C20) are synthesized from long-chain fatty acids (C11-20) by the addition of every 2 carbon unit in one cycle. The rate-limiting enzymes of this elongation are fatty acid elongases, called ELOVLs (elongation of very-long-chain fatty acid proteins).

Mammals have seven isoforms of ELOVLs. Similar to CerS, ELOVLs show characteristic chain lengths specificities. ELOVL1 catalyses the synthesis of saturated and monounsaturated C20 to C24 fatty acids. In addition, it is reported that patients with de novo mutation in the ELOVL1 gene exhibited the hypomyelination in axons of the CNS [START_REF] Kutkowska-Kazmierczak | Dominant ELOVL1 mutation causes neurological disorder with ichthyotic keratoderma, spasticity, hypomyelination and dysmorphic features[END_REF][START_REF] Mueller | De novo mutation in ELOVL1 causes ichthyosis, acanthosis nigricans, hypomyelination, spastic paraplegia, high frequency deafness and optic atrophy[END_REF]. ELOVL1-KO mice exhibited significantly thinner myelin in CNS than control mice and mild defects in coordinated ambulation. Lipidomics analyses revealed that the amounts of GalCer and sulfatide with C22:0, C24:0 and C24:1 were dramatically decreased, whereas C22:1, C20:0 and much shorter fatty acid species were significantly increased, regardless of HFA and NFA. The total amount of GalCer with NFA and HFA was reduced to 30-40% of control animals. In contrast, sulfatide showed no differences in KO and control mice. The quantities of SM and ceramide with very-long-chain fatty acids, such as C22:0 and much longer species, were also decreased in ELOVL1-deficient mice. Conversely, the amount of SM with shorter fatty acids (<C20) was not affected, and the amount of ceramide with C20:1 and C18:1 was increased in KO mice [START_REF] Isokawa | Reduced chain length in myelin sphingolipids and poorer motor coordination in mice deficient in the fatty acid elongase Elovl1[END_REF].

Role of lipids in wrapping neurons in invertebrates

Whereas GalCer is the predominant glycolipids in vertebrate myelin, the nerves of shrimp and some other protostome animals only contain glucose-containing glycosphingolipids such as GlcCer. HFA is also not observed in protostomes. These results suggest that NFA-GlcCer may play important roles in wrapping axons in shrimp.

In Drosophila, neurons are surrounded by a thin, single-layered plasma membrane of cortex glial cells in the CNS and of inner wrapping glial cells in the PNS, such as Remak bundles, while myelin-like structures were observed in the thoracic ganglion [START_REF] Freeman | Glial cell biology in Drosophila and vertebrates[END_REF][START_REF] Yildirim | Drosophila glia: Few cell types and many conserved functions[END_REF]. Drosophila lacks GalCer. Instead, CPE has an important role to ensheath axons by glial cells of both the PNS and the CNS in Drosophila. CPE is a phosphosphingolipid analogue of SM where the phosphocholine of SM is replaced by phosphoethanolamine (Fig. 1) [START_REF] Hullin-Matsuda | Protein probes to visualize sphingomyelin and ceramide phosphoethanolamine[END_REF][START_REF] Panevska | Ceramide phosphoethanolamine, an enigmatic cellular membrane sphingolipid, Biochimica et biophysica acta[END_REF]. CPE is the major sphingolipid in insects such as Drosophila [START_REF] Carvalho | Effects of diet and development on the Drosophila lipidome[END_REF][START_REF] Vacaru | Ceramide phosphoethanolamine biosynthesis in Drosophila is mediated by a unique ethanolamine phosphotransferase in the Golgi lumen[END_REF] and in some protozoa parasites such as

Trypanosoma brucei responsible for African sleeping disease [START_REF] Sutterwala | Developmentally regulated sphingolipid synthesis in African trypanosomes[END_REF]. In contrast, only trace amounts of CPE are found in mammalian cells [START_REF] Tafesse | Sphingomyelin synthase-related protein SMSr is a suppressor of ceramide-induced mitochondrial apoptosis[END_REF] and tissues representing only 0.002 to 0.02 mole % of total phospholipids [START_REF] Bickert | Functional characterization of enzymes catalyzing ceramide phosphoethanolamine biosynthesis in mice[END_REF].

By knocking down one of four genes involved in the biosynthesis of CPE (Spt-I, schlank, Des1, and Pect), or serine palmitoyltransferase, which is the key enzyme of all sphingolipid synthesis, glial cells failed to extend the plasma membrane to ensheath axons in PNS.

Lipidomics analyses of all the mutants indicated that CPE was significantly reduced, whereas the amounts of PC and PE were slightly changed [START_REF] Ghosh | A Global In Vivo Drosophila RNAi Screen Identifies a Key Role of Ceramide Phosphoethanolamine for Glial Ensheathment of Axons[END_REF]. The cortex glial membranes were severely compromised in CPE synthase (cpes)-null mutants and failed to encapsulate the neuronal cell bodies in the Drosophila neuronal cortex [START_REF] Kunduri | Defective cortex glia plasma membrane structure underlies light-induced epilepsy in cpes mutants[END_REF]. These phenotypes were rescued by the cortex glial cell-specific expression of CPE synthase. Lipid analyses of cpes mutants showed dramatic reduction of CPE and significant increases in lysophospholipids, lysoPC and lysoPE, with no changes in ceramide and hexosylceramide. Interestingly, the expression of human SM synthase 1 in glial cells of cpes-deficient flies rescued these phenotypes of cortex glial cells, in which SM, but not CPE, was expressed [START_REF] Kunduri | Defective cortex glia plasma membrane structure underlies light-induced epilepsy in cpes mutants[END_REF].

Physical properties of GalCer, GlcCer and CPE

The results of CGT-KO mice suggest that GalCer is important for the long-term maintenance of myelin, rather than myelin formation. Experiments using CGT-KO mice and CGT/FA2H double KO mice suggest that HFA-SM, HFA-GlcCer or very long NFA SM partially compensates the function of GalCer. Studies on Drosophila suggest that CPE can be replaced by SM. These results suggest that the physical properties of the lipids, rather than the chemical structures of the lipids enriched in glial cells, are important to wrap axons.

Phase transition temperature

The gel to liquid crystalline phase transition temperatures of GalCer, GlcCer, and CPE have been measured by differential scanning calorimetry (DSC) and fluorescence anisotropy of 1,6-diphenyl-1,3,5-hexatriene (DPH) (Table 1). Earlier studies using a combination of DSC and X-ray diffraction showed that, in general, sphingolipids with very long acyl chains displayed complex thermotropic behavior with several phase transitions whose peaks were attributed to different metastable gel phases [START_REF] Ruocco | X-ray diffraction and calorimetric study of anhydrous and hydrated N-palmitoylgalactosylsphingosine (cerebroside)[END_REF][START_REF] Reed | Effect of chain unsaturation on the structure and thermotropic properties of galactocerebrosides[END_REF][START_REF] Saxena | Structure and properties of totally synthetic galacto-and gluco-cerebrosides[END_REF].

Compared to other membrane lipids, GalCers exhibit extremely high phase transition temperature. Differences in the lengths of N-linked saturated fatty acyl chains (16:0, 18:0 and 24:0) did not result in much impact on the main thermal transition (approx. 82-85°C) [START_REF] Ruocco | X-ray diffraction and calorimetric study of anhydrous and hydrated N-palmitoylgalactosylsphingosine (cerebroside)[END_REF][START_REF] Reed | Effect of chain unsaturation on the structure and thermotropic properties of galactocerebrosides[END_REF][START_REF] Saxena | Structure and properties of totally synthetic galacto-and gluco-cerebrosides[END_REF][START_REF] Curatolo | Phase behavior of galactocerebrosides from bovine brain[END_REF][START_REF] Bjorkqvist | Thermotropic behavior and lateral distribution of very long chain sphingolipids[END_REF] (Table 1). In contrast, in unsaturated 24:1 GalCer, the transition temperature was approximately 20 degrees lower than that of 24:0 GalCer (Table 1) [START_REF] Reed | Effect of chain unsaturation on the structure and thermotropic properties of galactocerebrosides[END_REF][START_REF] Bjorkqvist | Thermotropic behavior and lateral distribution of very long chain sphingolipids[END_REF][START_REF] Kulkarni | Thermotropic behavior of galactosylceramides with cis-monoenoic fatty acyl chains[END_REF]. The α-hydroxylation at the C-2 position of the N-acyl chain also reduces the transition temperature approximately 10 degrees compared to NFA-GalCer [START_REF] Curatolo | Phase behavior of galactocerebrosides from bovine brain[END_REF][START_REF] Bunow | Two gel states of cerebrosides. Calorimetric and Raman spectroscopic evidence[END_REF][START_REF] Bunow | Molecular conformations of cerebrosides in bilayers determined by Raman spectroscopy[END_REF][START_REF] Jackson | Differential scanning calorimetric and Fourier transform infrared spectroscopic investigations of cerebroside polymorphism[END_REF]. Raman spectroscopy [START_REF] Bunow | Molecular conformations of cerebrosides in bilayers determined by Raman spectroscopy[END_REF] and FT-IR spectroscopy [98] indicate that α-hydroxylation contributes to extensive hydrogen bonding formation, resulting in the disturbance of van der Waals interaction between alkyl chains and thus a decrease in the phase transition temperature.

The phase transition temperatures of GlcCers are 88°C, 68°C and 87°C, for d18:1/24:0 (here d18:1 indicates the structure of sphingosine base with 'd' referring to 'di' and indicating the presence of two hydroxyl groups, followed by the carbon chain length and number of double bonds; 24:0 indicates the structure of the N-linked fatty acid), d18:1/24:1 and d18:1/16:0 species, respectively [START_REF] Saxena | Structure and properties of totally synthetic galacto-and gluco-cerebrosides[END_REF][START_REF] Bjorkqvist | Thermotropic behavior and lateral distribution of very long chain sphingolipids[END_REF]. These values are similar to those of corresponding GalCers.

The phase transition temperatures of GalCer and GlcCer are much higher than those of corresponding SM (Table 1). An increase of sugar moieties in a headgroup of glycosphingolipid results in a lowering of the phase transition temperature (Table 1). Most of the glycerolipids contain unsaturated fatty acids and thus exhibit low phase transition temperature. This suggests that the membrane-forming lipids with the highest phase transition temperature were utilized in myelin and wrapping glial cells in vertebrates and invertebrates.

The phase transition temperatures of CPE were investigated by measuring the anisotropy of DPH or calculating GPex values of Laurdan. The mid-temperatures of the transition for d18:1/18:1 CPE, d17:1/12:0 CPE, d18:1/24:1 ∆15(c) CPE (here, ∆15 means the position of the double bond at carbon number 15 from carboxyl residue, and (c) means cis double bond), milk CPE, d18:1/16:0 CPE and d18:1/24:0 CPE were 24°C, 38°C, 50°C, 59°C, 62-65.3°C and 72°C, respectively [99][START_REF] Bjorkbom | Effect of sphingomyelin headgroup size on molecular properties and interactions with cholesterol[END_REF][START_REF] Inaba | Formation of tubules and helical ribbons by ceramide phosphoethanolamine-containing membranes[END_REF], indicating that the shorter acyl chain and the unsaturation reduce the transition temperature. SM contains three additional methyl groups to CPE. The addition of each methyl group decreased the phase transition temperature of CPE. A similar relationship was observed between PC and PE [START_REF] Bjorkbom | Effect of sphingomyelin headgroup size on molecular properties and interactions with cholesterol[END_REF]. The phase transition temperatures of saturated PEs are 20-30 degrees above the corresponding PCs [START_REF] Van Dijck | The preference of cholesterol for phosphatidylcholine in mixed phosphatidylcholine-phosphatidylethanolamine bilayers[END_REF][START_REF] Lee | Analysis of the defect structure of gel-phase lipid[END_REF]. These differences are attributed to both the stronger headgroup interaction and the tighter packing owing to the small size of the headgroup and the intermolecular hydrogen bonding of PE molecules. By analogy with PE, the small headgroup size of CPE has been proposed to play a critical role to facilitate the strong CPE-CPE interaction [99]. This is consistent with our recent report of a stronger amide bond interaction between CPE molecules compared to SM molecules [START_REF] Shirota | Detection of Sphingomyelin Clusters by Raman Spectroscopy[END_REF].

The phase transition temperatures of GalCer, GlcCer and CPE are well over the growing temperature of the animals. Thus, these lipids exhibit gel phase in the body. However, other sphingolipids, such as lactosylceramide (LacCer) and SM, are also in gel phase at body temperature. Thus, it is suggested that, in addition to lipid phase, tight membrane packing of GalCer, GlcCer and CPE may play a role in the axon wrapping.

Lipid packing

Lipid packing in the monolayer membrane is dependent on the inter-and intramolecular hydrogen bonding of the lipid, the hydration at the air-water interface of the lipid, and van der Waals interactions in the chain region. The molecular area of d18:1/16:0 GalCer, d18:1/18:0 GalCer and d18:1/24:0 GalCer showed similar value (approximately 40 Å 2 at 30 mN/m at 24°C) (Table 2) [START_REF] Ali | Acyl structure regulates galactosylceramide's interfacial interactions[END_REF][START_REF] Smaby | Cholesterol-induced interfacial area condensations of galactosylceramides and sphingomyelins with identical acyl chains[END_REF][START_REF] Zhai | Lactosylceramide: lateral interactions with cholesterol[END_REF], consistent with the results of the transition temperatures. Although unsaturated d18:1/24:1 ∆15(c) GalCer showed lower phase transition temperature than d18:1/24:0 GalCer, the molecular areas of these two lipids were similar. In contrast, d18:1/24:1 ∆15(c) SM showed significantly larger molecular area than d18:1/24:0 SM (Table 2). This result indicates strong headgroup interaction in GalCer.

The molecular areas of GalCer and CPE are smaller than those of SM with the same sphingosine and fatty acid structure [106] [99, 108]. The molecular area of d18:1/24:1 ∆15(c)

GalCer was 38.0 Å 2 at 30 mN/m at 24 °C whereas that of d18:1/24:1 ∆15(c) SM was 59.7 Å 2 at the same condition [START_REF] Smaby | Cholesterol-induced interfacial area condensations of galactosylceramides and sphingomyelins with identical acyl chains[END_REF]. Similarly, the molecular area of d18:1/16:0 CPE was approximately 42 Å 2 at 30 mN/m at 22 °C [99] whereas that of d18:1/16:0 SM was 55 Å 2 [START_REF] Ramstedt | Interaction of cholesterol with sphingomyelins and acyl-chain-matched phosphatidylcholines: a comparative study of the effect of the chain length[END_REF]. In glycerolipids, PE and monogalactosyl glycerolipid have similar hydration levels whereas PC possesses much more water molecules [START_REF] Sen | Direct measurement of headgroup hydration of polar lipids in inverted micelles[END_REF]. This is consistent with the small molecular area of GalCer and CPE compared to SM.

The surface compressional moduli (Cs -1 where Cs=-(δA/δπ)T/A in pressure-molecular area (π-A) isotherms) for LacCers, GalCers and SMs of identical ceramide region are in the order of GalCer>LacCer >SM [START_REF] Zhai | Lactosylceramide: lateral interactions with cholesterol[END_REF]. Cs -1 is a measure of membrane stiffness. This result thus indicates that GalCer contributes to the impermeability of the membrane and electrical insulation.

Immiscibility of GalCer and CPE with Chol

It is well known that Chol condenses the molecular area of SM. The condensing effect is much less in GalCer/Chol mixture [START_REF] Smaby | Cholesterol-induced interfacial area condensations of galactosylceramides and sphingomyelins with identical acyl chains[END_REF][START_REF] Slotte | Cholesterol interacts with lactosyl and maltosyl cerebrosides but not with glucosyl or galactosyl cerebrosides in mixed monolayers[END_REF][START_REF] Ali | Cholesterol's interfacial interactions with galactosylceramides[END_REF] (Table 2). FT-IR measurement indicated that the presence of 9 % Chol disrupts the hydrogen bond interaction of GalCer-GalCer [START_REF] Jackson | Differential scanning calorimetric and Fourier transform infrared spectroscopic investigations of cerebroside polymorphism[END_REF].

However, DSC showed that NFA-GalCer and Chol are phase-separated until as high as 39%.

This value was decreased to 34% in HFA-GalCer/Chol mixture [START_REF] Johnston | A calorimetric study of the thermotropic behaviour of mixtures of brain cerebrosides with other brain lipids[END_REF]. In contrast, phase separation was abolished in SM/Chol mixture when Chol was higher than 25 % [START_REF] Calhoun | Sphingomyelin--lecithin bilayers and their interaction with cholesterol[END_REF]. The higher miscibility of Chol with HFA-GalCer than with NFA-GalCer is due to stronger intermolecular interaction in NFA-GalCer as observed in the higher phase transition temperature.

The immiscibility of GalCer with Chol has been observed in gel phase but not in liquid-crystalline phase by calorimetric measurement [START_REF] Johnston | A calorimetric study of the thermotropic behaviour of mixtures of brain cerebrosides with other brain lipids[END_REF][START_REF] Ruocco | Interaction of cholesterol with galactocerebroside and galactocerebroside-phosphatidylcholine bilayer membranes[END_REF][START_REF] Bjorkqvist | Domain formation and stability in complex lipid bilayers as reported by cholestatrienol[END_REF], suggesting that GalCer and Chol are phase separated at physiological temperature.

In CPE/Chol membrane, Chol shows a condensing effect in a concentration-dependent manner, indicating that Chol is, to some extent, miscible with CPE [99]. However, the interaction of CPE and Chol is much weaker than that of SM and Chol as shown by the much faster desorption of Chol by methyl-β-cyclodextrin from mixed monolayers [99]. Amide I-mediated intermolecular hydrogen bonding among CPE molecules, monitored by Raman spectroscopy, remained unaffected in the presence of Chol. This is in clear contrast to the disappearance of the signal in SM/Chol mixture [START_REF] Shirota | Detection of Sphingomyelin Clusters by Raman Spectroscopy[END_REF]. These results indicate that both GalCer and CPE are immiscible with Chol.

Assembly of GalCer-, GlcCer-, and CPE-containing membranes

Whereas aqueous dispersion of d18:1/24:1 ∆15(c) SM formed vesicles, d18:1/24:1 ∆15(c) GalCer showed nano-tubular structures (length, 250-400 nm; diameter, 25-30 nm) and d18:1/24:0 GalCer formed larger, variable-length helical ribbon-like structures (length, 5,000-10,000 nm) [START_REF] Kulkarni | Bilayer nanotubes and helical ribbons formed by hydrated galactosylceramides: acyl chain and headgroup effects[END_REF]. Similar to d18:1/24:1 ∆15(c) GalCer, d18:1/22:1 ∆13(c) GalCer formed nanotubes, whereas d18:1/20:1 ∆11(c) GalCer resembled helical ribbons with a right-handed twist, and d18:1/18:1 ∆9(c)

GalCer displayed a variety of morphologies, including large-diameter multilamellar cylinders and liposome-like structures [START_REF] Kulkarni | Modulation of nanotube formation by structural modifications of sphingolipids[END_REF]. Unlike d18:1/24:1 ∆15(c) GalCer, d18:1/24:1 ∆15(c) sulfatide formed large diameter multilamellar structure [START_REF] Kulkarni | Modulation of nanotube formation by structural modifications of sphingolipids[END_REF]. A 4:1 mixture of 16:0/18:1 PC and d18:1/16:0 GalCer exhibited long, thin, multilamellar tubules [START_REF] Curatolo | The effects of cerebrosides on model membrane shape[END_REF].

Equimolar suspension of bovine buttermilk CPE (milk CPE):di18:1 PC formed tubules and helical ribbons with 100-500 nm width [START_REF] Inaba | Formation of tubules and helical ribbons by ceramide phosphoethanolamine-containing membranes[END_REF]. These tubules and helices were composed of 5-10 nm tick slab-like multilayers (Fig. 2). Hydration of milk CPE alone mainly exhibited amorphous lipid aggregates and, at low frequency, straight needles, whereas aqueous suspension of pure di18:1 PC produced vesicles. An equimolar mixture of di18:1 PC and d17:1/12:0 CPE, d18:1/16:0 CPE or 18:1 CPE formed tubules while those of d18:1/24:0 CPE, d18:1/24:1 ∆15(c) CPE exhibited helical structures [START_REF] Inaba | Formation of tubules and helical ribbons by ceramide phosphoethanolamine-containing membranes[END_REF]. Any clear correlation between the phase transition temperature of these CPE species and the formation of helical structures of CPE suspensions was not obtained. However, there is a correlation between the lengths of N-acyl chain of CPE and the morphology of the lipid suspensions. Medium and long N-acyl chain CPEs formed tubules whereas very-long-chain CPEs formed helices. Milk CPE is mainly composed of 22:0, 23:0, and 24:0 N-acyl chains, consistent with this observation. Interestingly, helices formed in d18:1/N-24:1 ∆15(c) CPE: diC18:0 PC mixture were labelled with fluorescent protein fused CPE-binding protein, PlyA2-EGFP [START_REF] Bhat | Evaluation of aegerolysins as novel tools to detect and visualize ceramide phosphoethanolamine, a major sphingolipid in invertebrates[END_REF], indicating the presence of CPE in entire helices [START_REF] Inaba | Formation of tubules and helical ribbons by ceramide phosphoethanolamine-containing membranes[END_REF].

Conclusion

Genetic studies revealed the importance of GalCer in mammalian glial cells and of CPE in Drosophila to wrap axons. Interestingly, mammalian cells are deficient in CPE whereas Drosophila lacks GalCer, indicating that the same lipid has not been used during evolution to wrap axons. Nevertheless, GalCer and CPE share similar physical properties: both GalCer and CPE have high phase transition temperature, high packing, and immiscibility with Chol and form helical liposomes. These properties are caused by both the stronger headgroup interactions and the tighter packing due to the small size of the headgroup and the hydrogen bonds between lipid molecules. Although verylong-chain fatty acids of GalCer are crucial for myelination, the gel-to-liquid crystalline phase transition temperatures and molecular areas of d18:1/16:0 GalCer and d18:1/24:0 GalCer are similar (Table 1, 2). A clear difference between very-long-chain d18:1/24:0 GalCer and other GalCers is that d18:1/24:0 GalCer forms helical ribbons. It is speculated that strong acyl chain packing and hydrocarbon chain interdigitation stabilize ribbon-like structures [START_REF] Kulkarni | Modulation of nanotube formation by structural modifications of sphingolipids[END_REF]. Although helical ribbons were observed in vivo in Gaucher cells (defective in glucocerebrosidase) and Krabbe cells (defective in galactocerebrosidase) [START_REF] Yunis | Tubules of globoid leukodystrophy: a right-handed helix[END_REF], the relation between helical membrane formation and axon wrapping is not clear.

Similar to GalCer, very-long-chain CPE forms helical ribbon when mixed with di18:1 PC. It is speculated that the hydrophobic mismatch between very-long-chain CPE and diC18:1 PC induces the tilting of CPE-rich membrane domains in diC18:1 PC [START_REF] Inaba | Formation of tubules and helical ribbons by ceramide phosphoethanolamine-containing membranes[END_REF]. Interdigitated interaction between the very-long-chain CPEs in PC membrane may stabilize the tilted CPE domains. Moreover, the thin water layer on CPE may facilitate the piling up of the bilayer [START_REF] Inaba | Formation of tubules and helical ribbons by ceramide phosphoethanolamine-containing membranes[END_REF].

In Drosophila, the sphingolipid bases have shorter carbon chain length (d14:1 and d16:1) compared to mammals (d18:1) [START_REF] Guan | Biochemical membrane lipidomics during Drosophila development[END_REF]. However, the most abundant CPE species feature-very long N-acyl chains (d14:1/N-20:0 CPE and d14:1/N-22:0 CPE) [START_REF] Kunduri | Defective cortex glia plasma membrane structure underlies light-induced epilepsy in cpes mutants[END_REF][START_REF] Guan | Biochemical membrane lipidomics during Drosophila development[END_REF].

It is intriguing that very-long-chain SM was accumulated in CGT/FA2H double KO mice and that replacement of CPE with SM rescued cortex glial abnormalities in Drosophila [START_REF] Kunduri | Defective cortex glia plasma membrane structure underlies light-induced epilepsy in cpes mutants[END_REF].

These results suggest that there is no strict structure requirement for lipids to wrap axons. This notion is supported by the fact that vertebrates and Drosophila use different lipids to wrap axons.

Compared to GalCer and CPE, SM shows a lower phase transition temperature and looser membrane packing. However, the phase transition temperature of very-long-chain SM is still much higher than the body temperature (mammals, 35-40°C; Drosophila, 22-26°C). The Current understanding of the role of GalCer is that the lipid is required for the stability and maintenance of myelin in old age [START_REF] Schmitt | DSC /phosphate buffer pH 6.6 * 1 [114] GalCer Bovine brain 68.8/ DSC/ H2O[END_REF]. Very tight membrane packing of GalCer may be essential for long-term maintenance of myelin function. Similar to GalCer, CPE may be involved in the stability of glial membranes in the long term or under pathological conditions.

Figure 1 :

 1 Figure 1: Structures of d18:1/24:0 (NFA-)GalCer, d18:1/24:0 HFA-GalCer, d18:1/24:0 GlcCer, d14:1/20:0 CPE, d18:1/16:0 SM, and d18:1/24:0 SM. In d18:1/24:0 GalCer, galactose, sphingosine, and fatty acid moieties are enclosed by green, blue, and red lines, respectively.

Figure 2 :

 2 Figure 2: CPE forms helical liposomes. (A) PlyA2-EGFP was added to d18:1/24:1 ∆15 (c) CPE:diC18:1 PC (1:1) during hydration of the lipid film. A fluorescent image was acquired. (B) Negative staining electron micrographs of aqueous dispersion of milk CPE:diC18:1 PC (1:1).Closer views of the helices revealed that the structures were composed of multilayered 5-10 nm thick slab-like structures (arrow heads indicate each layer).

  Figure 1 Murate Tomishige Kobayashi

Table 1 : Gel-to-liquid crystalline phase transition temperatures of various lipidsTable 2 : Condensing effects of Chol on SM and GalCer Legend of figures:

 12

Acknowledgement

We are grateful to Prof Hiroshi Takahashi from Gunma University and Dr Françoise Hullin-Matsuda from UMR INSERM 1060-INSA Lyon for critically reading the manuscript. Grants from the Glycolipidologue Program of RIKEN and the Mizutani Foundation to T. K are acknowledged. The work of the authors was supported by RIKEN, INSERM, CNRS and Université de Strasbourg.

Author contributions

T.K. conceived of the presented idea. M.M., N. T. and T.K. participated with manuscript content and organization.