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Background: The plasticity of macrophages in the immune response is a dynamic situation dependent on external stimuli. The activation of macrophages both has beneficial and detrimental effects on mature oligodendrocytes (OLs) and myelin. The activation towards inflammatory macrophages has a critical role in the immune-mediated oligodendrocytes death in multiple sclerosis (MS) lesions., New Method: We established an in vitro co-culture method to study the function of macrophages in the survival and maturation of OLs., Results: We revealed that M1 macrophages decreased the number of mature OLs and phagocytosed the myelin. Interestingly, non-activated as well as M2 macrophages contributed to an increase in the number of mature OLs in our in vitro co-culture platform., Comparison With Existing Methods: We added an antibody against an OL surface antigen in our in vitro co-cultures. The antibody presents the OLs to the macrophages enabling the investigation of direct interactions between macrophages and OLs., Conclusion: Our co-culture system is a feasible method for the investigation of the direct cell-to-cell interactions between OLs and macrophages. We utilized it to show that M2 and non-activated macrophages may be employed to enhance remyelination., Competing Interests: Conflict of interest No potential conflict of interest was reported by the authors., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Disorders that disrupt myelin formation during development or in adulthood, such as multiple sclerosis and peripheral neuropathies, lead to severe pathologies, illustrating myelin's crucial role in normal neural functioning. However, although our understanding of glial biology is increasing, the signals that emanate from axons and regulate myelination remain largely unknown. To identify the core components of the myelination process, here we adopted a microarray analysis approach combined with laser-capture microdissection of spinal motoneurons during the myelinogenic phase of development. We identified neuronal genes whose expression was enriched during myelination and further investigated hepatoma-derived growth factorrelated protein 3 (HRP3 or HDGFRP3). HRP3 was strongly expressed in the white matter fiber tracts of the peripheral (PNS) and central (CNS) nervous systems during myelination and remyelination in a cuprizone-induced demyelination model. The dynamic localization of HPR3 between axons and nuclei duringmyelination was consistent with its axonal localization during neuritogenesis. To study this phenomenon, we identified two splice variants encoded by the HRP3 gene: the canonical isoform HRP3-I and a newly recognized isoform, HRP3-II. HRP3-I remained solely in the nucleus, whereas HRP3-II displayed distinct axonal localization both before and during myelination. Interestingly, HRP3-II remained in the nuclei of unmyelinated neurons and glial cells, suggesting the existence of a molecular machinery that transfers it to and retains it in the axons of neurons fated for myelination. Overexpression of HRP3-II, but not of HRP3-I, increased Schwann cell numbers and myelination in PNS neuron-glia co-cultures. However, HRP3-II overexpression in CNS co-cultures did not altermyelination. [ABSTRACT FROM AUTHOR]

Objective: Myelin is essential for a healthy nervous system. Myelin formed by oligodendrocytes, accelerates impulse propagation and supports neuronal survival. Demyelination leads to neurodegeneration. In multiple sclerosis (MS) immune attack results in demyelination. Our goal is to dissect interactions among oligodendrocytes, neurons, and immune cells to improve our understanding of myelination and the demyelinating diseases. We aim to discover new targets for remyelination therapies. Methods: We are building tools for analyzing protein-protein and cell-to-cell interactions. To identify genes involved in myelination and MS, we developed a bioinformatics-based strategy, interactome analysis, which combines proteome and gene expression methodologies. Identified genes are evaluated in peripheral blood of MS patients and in mouse models. To accelerate drug discovery, 23 machine learning-based methodologies were assessed for myelin identification in fluorescent microscopy images. Results: Interactome analysis identified hundreds of proteinprotein interactions between pairs of oligodendrocytes, neurons, macrophages, microglia, and T cells. Most significant interactions are further analyzed in vivo and in vitro. Our customizedconvolutional neural network and Boosted Tree methods segmented myelin at over 98% accuracy. Identified myelin can be quantified and visualized in 3D. Conclusion: The interactome analysis yielded novel genes that are likely to be linked to MS. Machine learning-based methodologies are very effective in accelerating myelin quantification and thus, drug screens against demyelinating diseases such as MS. Overall, our innovative analysis strategies employing computer assistance produced novel avenues of exploration for myelination and demyelinating diseases. This study was supported TUBITAK (218S495,316S026), Istanbul Medipol University (BAP2018/06), and Turkish Academy of Sciences (GEBIP). [ABSTRACT FROM AUTHOR]

Objective: Function of the myelin membrane is to accelerate impulse propagation and support metabolism and health of an axon that may extend a long distance off the neuronal body. In the central nervous system specialized glia cells -oligodendrocyteswrap the axons. An oligodendrocyte has to generate a striking amount of membrane as it can wrap up to 30-40 internodes, which are myelinated regions between nodes of Ranvier. During the expansion of the oligodendrocyte membrane towards the nodes of Ranvier large amounts of lipid and protein are trafficked to the cell membrane. Thus, defects in the cellular vesicular transport may result in myelin disorders such as "Pelizaeus-Merzbacher" disease (PMD). Cellular transport and the resulting membrane expansion processes were studied in detail at the ultrastructural level mainly by immunocytochemistry and electron microscopy, yet their dynamics are poorly understood during myelination. In order to fill the gap in our understanding, we aim to monitor lipid and protein transport to the cellular membrane in real-time. Methods: Using oligodendrocytes derived from stem cells, the cargo vesicles, lipids and lipid rafts in oligodendrocytes were monitored in real-time during myelin formation using fluorescent dyes and fluorescent proteins. Monitored oligodendrocytes were categorized according to their maturation status. Results: Our early results revealed that membrane lipids and cargo vesicles carrying different proteins followed different transportation patterns and integrated to the membrane at different locations. Conclusion: Higher temporal and spatial resolution observations are needed to reach a more detailed description of molecular physiology of myelination. Increased knowledge on myelination will not only result in a better understanding of the basic biology of the oligodendrocytes but will also improve our understanding of the myelination disorders such as PMD. [ABSTRACT FROM AUTHOR]