Systematic approaches to central nervous system myelin Patricia de Monasterio-Schrader 1 , Olaf Jahn 2,3 , Stefan Tenzer 4 , Sven P. Wichert 1 , Julia Patzig 1 , and Hauke B. Werner 1* This is the author’s version as accepted for publication. The copyrighted e-offprint is available from Springer Basel AG, as published in Cellular and Molecular Life Sciences (2012), Digital Object Identifier (DOI) 10.1007/s00018-012-0958-9. Authors addresses 1 Department of Neurogenetics Max Planck Institute of Experimental Medicine, Göttingen, Germany 2 Proteomics Group Max Planck Institute of Experimental Medicine, Göttingen, Germany 3 DFG Research Center for Molecular Physiology of the Brain Göttingen, Germany 4 Institute of Immunology University Medical Center of the Johannes Gutenberg University Mainz, Germany * Corresponding author: Dr. Hauke Werner Max Planck Institute of Experimental Medicine Department of Neurogenetics Hermann-Rein-Str. 3 D-37075 Göttingen, Germany Tel.: +49 (551) 389-9759 Fax.: +49 (551) 389-9758 E-mail: [email protected]Running title Systematic approaches to CNS myelin Manuscript organization 22 pages, 4 figures, 2 tables, 1 supplemental table Acknowledgements We thank W. Möbius for providing the electron micrograph in Figure 1, J. M. Edgar for critical reading of the manuscript, C. M. Kassmann for discussion and K.-A. Nave for continuous support. ST is supported by the Deutsche Forschungsgemeinschaft (SFB 490 Z3) and the Forschungszentrum Immunologie (FZI) at the University of Mainz, and HBW is supported by the BMBF (DLR-Leukonet) and the European Commission (FP7-LeukoTreat).
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Systematic approaches to central nervous system myelin
Patricia de Monasterio-Schrader1, Olaf Jahn2,3, Stefan Tenzer4, Sven P. Wichert1, Julia Patzig1, and Hauke B. Werner1*
This is the author’s version as accepted for publication. The copyrighted e-offprint is available from Springer Basel AG, as published in Cellular and Molecular Life Sciences (2012), Digital Object Identifier (DOI) 10.1007/s00018-012-0958-9. Authors addresses 1 Department of Neurogenetics
Max Planck Institute of Experimental Medicine, Göttingen, Germany 2 Proteomics Group
Max Planck Institute of Experimental Medicine, Göttingen, Germany 3 DFG Research Center for Molecular Physiology of the Brain Göttingen, Germany 4 Institute of Immunology University Medical Center of the Johannes Gutenberg University Mainz, Germany * Corresponding author: Dr. Hauke Werner Max Planck Institute of Experimental Medicine Department of Neurogenetics Hermann-Rein-Str. 3 D-37075 Göttingen, Germany Tel.: +49 (551) 389-9759 Fax.: +49 (551) 389-9758 E-mail: [email protected] Running title Systematic approaches to CNS myelin Manuscript organization 22 pages, 4 figures, 2 tables, 1 supplemental table Acknowledgements We thank W. Möbius for providing the electron micrograph in Figure 1, J. M. Edgar for critical reading of the manuscript, C. M. Kassmann for discussion and K.-A. Nave for continuous support. ST is supported by the Deutsche Forschungsgemeinschaft (SFB 490 Z3) and the Forschungszentrum Immunologie (FZI) at the University of Mainz, and HBW is supported by the BMBF (DLR-Leukonet) and the European Commission (FP7-LeukoTreat).
Abstract
Rapid signal propagation along vertebrate axons is facilitated by their insulation with myelin, a
plasma membrane specialization of glial cells. The recent application of ‘omics’ approaches to
the myelinating cells of the central nervous system, oligodendrocytes, revealed their mRNA
signatures, enhanced our understanding of how myelination is regulated and established that
the protein composition of myelin is much more complex than previously thought. This
review provides a meta-analysis of the >1200 proteins thus far identified by mass
spectrometry in biochemically purified central nervous system myelin. Contaminating proteins
are surprisingly infrequent according to bioinformatic prediction of subcellular localization and
comparison with the transcriptional profile of oligodendrocytes. The integration of datasets
also allowed the subcategorization of the myelin proteome into functional groups comprising
genes that are coregulated during oligodendroglial differentiation. An unexpectedly large
number of myelin-related genes cause - when mutated in humans - hereditary diseases
affecting the physiology of the white matter. Systematic approaches to oligodendrocytes
and myelin thus provide valuable resources for the molecular dissection of developmental
myelination, glia-axonal interactions, leukodystrophies and demyelinating diseases.
Scamp5)) is developmentally unchanged, suggesting continued requirement of the gene
product.
Notably, the membrane of vesicular exosomes derived from multivesicular bodies [105, 106]
comprises a particular abundance of tetraspans, in which they may facilitate fission and
fusion [107]. Oligodendrocyte-derived exosomes may be required to locally dispose off
superfluous membrane and to transfer material to axons [108] and microglia [109].
However, they also counteract the extension of oligodendroglial plasma membrane, at least in
vitro [110], possibly reflecting a function in the spatial segregation of myelin sheaths in vivo
related to that of Nogo (Rtn4) [82, 111]. Strikingly, there is a high overlap between the
tetraspans of exosomes and of myelin, including PLP, CD9, CD81, CD82 and CD63
(tetraspanin 30). It is attractive to speculate on commonalities of the two compartments
regarding biosynthesis and function. Together, the integration of proteomic and
transcriptomic datasets provides a background to study protein groups with structural and
functional similarity and co-regulated expression.
Heritable myelin-related diseases
Hereditary diseases affecting myelination or the physiology of the white matter
(leukodystrophies or leukoencephalopathies) vary considerably regarding the affected genes
and the pathophysiology. Importantly, only a subset of the causative genes encodes myelin
proteins [112-117]. For example mutations affecting the PLP1-gene, which encodes the
most abundant protein of CNS myelin, PLP, cause the hypomyelinating leukodystrophy
‘Pelizaus-Merzbacher disease‘ or the allelic ‘spastic paraplegia type 2‘ [118-120].
As oligodendrocytes, astrocytes, microglia and neurons intimately interact, the cellular
pathologies of leukodystrophies are very complex. Indeed, the identification of novel
leukodystrophy disease genes, which has accelerated in recent years [121-125], has
facilitated - often unexpected - insights into the biology and the interactions of glial cells
[126]. Importantly, many leukodystrophies are caused by mutations that do not affect
‘classical‘ myelin genes, or even genes considered to be expressed specifically in cells other
than oligodendrocytes. This is exemplified by ‘hypomyelination and congenital cataract‘
(HCC), which is caused by mutations affecting the FAM126A gene [127] encoding the
primarily neuronal protein hyccin [128], or by ‘hereditary diffuse leukoencephalopathy with
spheroids‘ (HDLS), which is caused by mutations affecting the gene encoding ‘colony
stimulating factor 1 receptor‘ (CSF1R) [125], considered exclusively expressed in microglia
[129]. However, such prior knowledge may infer an unjustified bias in the search for the
pathomechanism. For example, astrocytes are commonly considered the primary site of
pathology in ‘Alexander’s disease‘. Here, the white matter degeneration coincides with the
emergence of aggregates (termed Rosenthal fibers) in astrocytes. Rosenthal fibers comprise
the product of the causative gene, which encodes the intermediate filament glial fibrillary
acidic protein (Gfap) [130, 131]. However, whether astrocytic Rosenthal fibers indeed
contribute to the emergence of myelin abnormalities has not been satisfactorily shown.
Strikingly, GFAP is commonly thought to be exclusive to astrocytes, while our meta-analysis
emphasizes that GFAP was identified by MS in purified myelin and that the corresponding
mRNA was detected in oligodendrocytes (cluster ‘ASCENDING‘; Fig. 4). This suggests that
the expression of GFAP is less restricted than anticipated, and that it ought not be excluded
that oligodendrocytes and myelin are primary sites of pathology in Alexander’s disease.
In Table 2 we have compiled a list of genes that fulfill three criteria: (1) the protein was
identified by MS in myelin, (2) the mRNA was robustly detected in oligodendrocytes, and (3)
mutations affecting the corresponding human gene cause a disease that includes pathology
of myelin or the white matter, at least in a subset of patients. For example, one of the
causative genes for megalencephalic leukoencephalopathy with subcortical cysts (MLC), glial
cell adhesion molecule (GlialCAM, official gene name Hepacam; Cluster Down-UP in Fig. 4),
encodes an abundant CNS myelin protein [132] but is also expressed in astrocytes [124,
133]. In the latter, GlialCAM is involved in the intracellular trafficking of MLC1, a
transmembrane protein with distant homology to sodium channels, to its normal localization
at the junctions between astrocytes and neighboring astrocytes or the endothelial cells of
the blood-brain-barrier. As MLC1 is also a causative gene in MLC [134], a failure of GlialCAM-
dependent trafficking of MLC1 to astrocytic junctions is very likely disease relevant.
However, the emergence of myelin vacuoles in a subset of MLC patients may potentially be
attributed to the presence of GlialCAM in normal CNS myelin.
Taken together, oligodendrocytes and myelin may well contribute to the pathogenesis in
white matter diseases in which the affected genes are erroneously thought to be expressed
mainly or exclusively in other cells. However, proof for the involvement of particular cell
types in the pathogenesis of any leukodystrophy must come from the analysis of cell-type
specific mutant mice, which is also prerequisite for the development of rational therapy
concepts. We propose that the present compendium of myelin proteins also provides a useful
resource to identify causative genes in association studies in which only chromosomal
segments (comprising many genes) are currently known.
Tools and perspectives
Until recently, the constituents of myelin were mainly approached by single gene analysis.
However, with the advent of ‘omics’ techniques it became evident that all myelin proteins are
embedded in a context of molecular networks involving co-regulated expression and physical
protein-protein interactions. The present meta-analysis integrates systematic information
gained by proteomic analysis of normal CNS myelin in 11 published datasets and by
transcriptional profiling of differentiating oligodendrocytes upon immunopanning, i.e. cell
purification using antibodies directed against stage-specific surface antigens [9].
In an alternative approach to obtain samples for transcriptional profiling of distinct cell types,
BAC-transgenic mice were generated in which cell-type specific promoters drive the
expression of the ribosomal protein L10a with an EGFP-tag suited to affinity-purify labeled
polysomes for the subsequent analysis of the associated RNA (‘translating ribosome affinity
purification‘, TRAP) [135]. For the oligodendrocyte lineage, the Olig2 promoter (active from
OPCs to mOL) and the Cmtm5 promoter (active in mOL) were used [136]. Interestingly,
CMTM5 is a proven constituent of peripheral myelin [52], while antibody-based validation as
an oligodendroglial protein is yet lacking. However, its occurrence in the present compendium
(Cluster ‘Ascending‘ in Fig. 4) suggests that CMTM5 is a myelin protein also in the CNS.
Thus, the TRAP study has identified over 1000 probes representing hundreds of mRNAs with
a high probability of being translated in oligodendrocytes, which is also supported by the
considerable number of known myelin-related genes in the dataset (supplemental table S5 in
[136]. Considering that transgene expression under control of the Cmtm5 promoter was
comparatively weak, the future variation of TRAP utilizing a stronger oligodendrocyte-specific
promoter may allow the complementation of immunopanning for future transcriptional
profiling approaches in comparative analyses of mouse models of myelin-related diseases.
However, the application of either technique may remain limited, e.g. when oligodendroglial
surface antigens or the activity of driver-promoters are altered as part of the pathology.
Large-scale in situ-hybridization as supplied in the ‘Allen Brain Atlas‘ (mouse.brain-map.org)
and subsequent sorting of labeling patterns (Supplemental Table 11 in [137] by the time of
publication allowed the identification of 79 mRNAs with a high probability of oligodendrocyte-
enriched expression. Reassuringly, 37 (47%) among them are also represented in the current
myelin proteome compendium. Many of the remaining oligodendrocyte-enriched mRNAs
encode enzymes of the lipid metabolism (Abca2, Edg8, Fa2h, Fabp5, Hmgcs1, Lass2, Npc1,
Ugt8) and known oligodendroglial transcription factors (Olig1, Olig2, Mrf/Gm98, Sox10).
A more direct strategy to identify transcription factors in the oligodendrocyte lineage
involved in silico-screening [138] of a previously established transcription factor expression
atlas based on in situ-hybridization in the developing mouse CNS (‘Mahoney atlas‘) [139].
Out of 1445 transcription factors in the pictorial, 87 displayed an embryonic mRNA labeling
pattern compatible with expression in glial progenitors, and 20 displayed sustained glia-like
labeling at birth. Among those, 8 were already known to be involved in glial development
while 9 were newly identified as enriched in OPCs. One of them, the HMG-box transcription
factor 7-like 2 (Tcf7l2), was shown to be functionally involved in OPC maturation [138, 140,
141]. Together, the exploitation of pictorials allows the identification of molecules relevant
for oligodendrocytes, and thus is promising also beyond the application to transcription
factors. However, the interpretation of expression atlas data, their validation and their
integration with other systematic datasets [142-147] remains a challenge.
In conclusion, a wealth of systematically gained molecular information has recently emerged
for the normal development of oligodendrocytes and their accompanying non-myelinating
cells. As of today, the exploitation of these resources is still in its infancy, and the field is
confronted with the luxury problem to choose the most interesting candidate proteins for
individual functional analysis. We believe that the integration of systematic datasets - as
illustrated here - can facilitate the selection of proteins for in-depth follow-up studies. The
current technical limitations of systematic approaches, including non-represented genes and
unsuited probes (affecting microarrays and pictorials), non-specific antibodies
(immunohistochemistry) and proteins unsuited for MS sequencing upon trypsin digest
(proteomics), may well be overcome, e.g. by whole-transcriptome sequencing, more specific
antibodies and alternative proteases, respectively. Rather, the systematic application beyond
normal tissue is laborious and expensive and may thus remain limited at last. However,
disease-relevant insights into the pathophysiology of the white matter eventually require
comprehensive knowledge of the spatio-temporal expression of all mRNAs, regulatory RNAs
and proteins, not only in the normal brain but also in disease models and ultimately in
patients. While there are obvious limitations to the availability of human brain samples,
techniques for differential analyses of models of myelin disease have been established at the
proteomic [53, 148] and transcriptomic [14, 149, 150] level. It is encouraging that also the
application to complex traits in humans, such as multiple sclerosis [151-157] and psychiatric
diseases [158-162], has been initiated.
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Figure legends
Figure 1. Central nervous system myelin.
(A) The optic nerve of an adult, wild-type mouse was visualized by transmission electron
microscopy upon fixation by high-pressure freezing and freeze substitution. Several
myelinated axons are shown in cross-section. Note the periodic arrangement of myelin
membranes. Electron micrograph kindly provided by W. Möbius. (B) One-dimensional gel-
separation of CNS myelin. Myelin purified from wild-type mouse brains was separated by SDS-
PAGE in different buffer systems providing improved resolution either in the low (MES) or
high (MOPS) molecular weight range. Proteins were visualized with colloidal Coomassie
(Coom., 5 µg protein load) or silver staining (0.5 µg protein load). Bands are denoted, which
are constituted by known myelin proteins according to mass spectrometric identification.
myelin-associated oligodendrocytic basic protein. In bands marked with arrowheads, only
proteins not previously associated with myelin were identified.
Figure 2. Assembling a compendium of CNS myelin proteins.
(A) The number of proteins identified in different approaches to the CNS myelin proteome is
plotted. The total number of myelin-associated proteins is unknown. Transmembrane proteins
(black) were systematically predicted by TMHMM2, Phobius and TMpred software. Proteins
derived from mitochondria (which are diminished but not entirely lost during myelin
purification) were predicted by Cello and Wolfpsort software and according to the literature.
T [55]; V [54]; R [57]; W [53]; B [58]; J [7]; D [59]. I [56] provide datasets for mouse (I-
m) and human (I-h) myelin. The integration of all datasets (‘All’) yields a catalogue of 1261
proteins for which a unique gene identifier was available. (B) Single and multiple
identifications. For all proteins identified in CNS myelin it was plotted in how many
approaches they were identified. Note that fewer than half of the proteins (48%) were
identified in only one approach. (C) Cross-study reproducibility. For all approaches to the
CNS myelin proteome it was plotted which percentage of identified proteins were additionally
identified in at least one other approach. Note the high overall reproducibility. The seemingly
low reproducibility of the dataset B [58] is due to the subfractionation of myelin by ion
exchange chromatography (IEX) (see text for details).
Figure 3. Venn diagram comparing the number of proteins identified in human versus rodent
CNS myelin (A), and in CNS versus PNS myelin (B) according to [52].
Figure 4. Profi les of myelin-associated mRNAs in oligodendrocytes.
(A) The mRNA abundance profiles in oligodendrocyte progenitor cells (OPC), pre-myelinating,
post-mitotic oligodendrocytes (OL) and myelinating oligodendrocytes (mOL), as determined
by [9], were filtered for the proteins identified by MS in purified myelin. Upon k-means
clustering, the normalized mRNA-abundance profiles were plotted with regard to the
differentiation stage. Genes with significant mRNA-abundance changes were categorized in
eight clusters. Known myelin-related genes are in bold, and genes encoding proteins probably
derived from mitochondrial, blood or nuclear contamination are in gray. mRNAs in the clusters
‘UP’ or ‘ASCENDING’ display significantly increased abundance during oligodendrocyte
differentiation while mRNAs in the clusters ‘DOWN’ or ‘DESCENDING’ are significantly
suppressed during development. (B) The numbers of mRNAs per cluster are given.
Supplemental Table S1. Compendium of proteins identified by mass
spectrometry in CNS myelin.
Out of the 1280 proteins listed, 1261 proteins could be assigned to a unique gene identifier,
of which 1249 could be correlated with the oligodendroglial transcriptome as established by
[9] (last column). The proteins are classified into three groups: known myelin proteins,
proteins identified by MS in myelin, and proteins presumably derived from mitochondria that
contaminate the myelin-enriched fraction. Identification of a protein in one of the 11 available
proteomic datasets (see main text for references) is indicated by "1". Potential mitochondrial
localization was classified by prior knowledge (MitoCarta) and prediction of subcellular
localization according to three algorithms (TargetP, Cello, Wolfpsort). The number of
transmembrane domains was predicted by three algorithms (TMpred, TMHMM, Phobius). If
available, correlation with a large-scale in situ-hybridization dataset (‘Allen Brain Atlas‘) is
provided (OL, oligodendrocyte; AS, astrocyte; NE, neuron) according to supplemental table
11 in [137].
Table 1. Relative abundance of major myelin proteins by mass spectrometric quantification Protein CNS myelin (%) PNS myelin (%) PLP 17 0.2 MBP 8 8 CNP 4 0.5 MOG 1 nd MAG 1 0.3 SIRT2 1 nd OSP 1 nd P0 nd 21 Periaxin nd 16 FASN nd 1 4.1G nd 1 Others 67 52 Proteins associated with purified CNS or PNS myelin were identified and quantified by LC-MSE [7, 52]. Selected myelin proteins are sorted by their relative abundance in CNS myelin. nd, not detected.
Table 2. Comparison of proteins identified in CNS myelin and disease genes associated with pathology of myelin or the white matter Gene Protein name mRNA profile OMIM Disease Remarks AHCY S-Adenosylhomocysteine Hydrolase Unchanged *180960
#613752 Hypermethioninemia Slow myelination, white
matter atrophy CTSD Cathepsin D Unchanged *116840
#610127 Ceroid Lipofuscinosis White matter
abnormalities GFAP Glial Fibrillary Acidic Protein Ascending *137780
Probably mitochondrial localization AUH Au-specific RNA-binding Protein Ascending *600529
#250950 3-Methylglutaconic Aciduria White matter lesions
Proteins are listed that fulfill three criteria: (1) the protein was identified by MS in purified CNS myelin, (2) the corresponding mRNA was detected in oligodendrocytes and (3) mutations affecting the corresponding gene are associated with diseases that reportedly can include pathology of myelin or the white matter. Localization to mitochondria, which partly co-purify with myelin, was designated according to software-based prediction and a brain mitochondrial proteome study [68]. Note that mutations affecting mitochondrial proteins may infer myelin-related pathology. For proteins with additional expression in astrocytes, microglia, or neurons it is presently unknown whether loss/gain of function in oligodendrocytes is indeed causative of the disease. The mRNA abundance profile according to k-means cluster analysis (Fig. 4) is given.
Figure 1. Central nervous system myelin. (A) The optic nerve of an adult, wild-type mouse was visualized by transmission electron microscopy upon �xation by high-pressure freezing and freeze substitution. Several myelinated axons are shown in cross-section. Note the periodic arrangement of myelin membranes. Electron micrograph kindly provided by W. Möbius. (B) One-dimensional gel-separation of CNS myelin. Myelin puri�ed from wild-type mouse brains was separated by SDS-PAGE in di�erent bu�er systems providing improved resolution either in the low (MES) or high (MOPS) molecular weight range. Proteins were visualized with colloidal Coomassie (Coom., 5 µg protein load) or silver staining (0.5 µg protein load). Bands are denoted, which are constituted by known myelin proteins according to mass spectrometric identi�cation. MAG, myelin associated glycoprotein; TUBA, α-tubulin; CNP, 2’,3’-cyclic nucleotide phosphodiesterase; SIRT2, sirtuin 2; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; CLDN11, claudin 11/OSP; MOG, myelin oligodendrocyte glycoprotein; PLP, proteolipid protein; MBP, myelin basic protein; CKB, brain creatine kinase; CA2, carbonic anhydrase 2; MOBP, myelin-associated oligodendrocytic basic protein. In bands marked with arrowheads, only proteins not previously associated with myelin were identi�ed.
Figure 2. Assembling a compendium of CNS myelin proteins. (A) The number of proteins identi�ed in di�erent approaches to the CNS myelin proteome is plotted. The total number of myelin-associated proteins is unknown. Transmembrane proteins (black) were systematically predicted by TMHMM2, Phobius and TMpred software. Proteins derived from mitochondria (which are diminished but not entirely lost during myelin puri�cation) were predicted by Cello and Wolfpsort software and according to the literature. T [55]; V [54]; R [57]; W [53]; B [58]; J [7]; D [59]. I [56] provide datasets for mouse (I-m) and human (I-h) myelin. The integration of all datasets (‘All’) yields a catalogue of 1261 proteins for which a unique gene identi�er was available. (B) Single and multiple identi�cations. For all proteins identi�ed in CNS myelin it was plotted in how many approaches they were identi�ed. Note that fewer than half of the proteins (48%) were identi�ed in only one approach. (C) Cross-study reproducibility. For all approaches to the CNS myelin proteome it was plotted which percentage of identi�ed proteins were additionally identi�ed in at least one other approach. Note the high overall reproducibility. The seemingly low reproducibility of the dataset B [58] is due to the subfractionation of myelin by ion exchange chromatography (IEX) (see text for details).
Figure 3. Venn diagram comparing the number of proteins identi�ed in human versus rodent CNS myelin (A), and in CNS versus PNS myelin (B) according to [52].
Figure 4. Pro�les of myelin-associated mRNAs in oligodendrocytes.(A) The mRNA abundance pro�les in oligodendrocyte progenitor cells (OPC), pre-myelinating, post-mitotic oligodendrocytes (OL) and myelinating oligodendrocytes (mOL), as determined by [9], were �ltered for the proteins identi�ed by MS in puri�ed myelin. Upon k-means clustering, the normalized mRNA-abundance pro�les were plotted with regard to the di�erentiation stage. Genes with signi�cant mRNA-abundance changes were categorized in eight clusters. Known myelin-related genes are in bold, and genes encoding proteins probably derived from mitochondrial, blood or nuclear contamination are in gray. mRNAs in the clusters ‘UP’ or ‘ASCENDING’ display signi�cantly increased abundance during oligodendrocyte di�erentiation while mRNAs in the clusters ‘DOWN’ or ‘DESCENDING’ are signi�cantly suppressed during development. (B) The numbers of mRNAs per cluster are given.