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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
Cell-type-specific metabolic labeling of nascent
proteomes in vivo
Beatriz Alvarez-Castelao1, Christoph T Schanzenbächer1,2,6, Cyril Hanus1,5,6, Caspar Glock1, Susanne tom Dieck1,
Aline R Dörrbaum1,2, Ina Bartnik1, Belquis Nassim-Assir1, Elena Ciirdaeva1, Anke Mueller3,
Daniela C Dieterich3, David A Tirrell4, Julian D Langer1,2 & Erin M Schuman1
Although advances in protein labeling methods have made it
possible to measure the proteome of mixed cell populations, it
has not been possible to isolate cell-type-specific proteomes
in vivo. This is because the existing methods for metabolic
protein labeling in vivo access all cell types. We report
the development of a transgenic mouse line where Crerecombinase-induced expression of a mutant methionyl-tRNA
synthetase (L274G) enables the cell-type-specific labeling
of nascent proteins with a non-canonical amino-acid and
click chemistry. Using immunoblotting, imaging and mass
spectrometry, we use our transgenic mouse to label and analyze
proteins in excitatory principal neurons and Purkinje neurons
in vitro (brain slices) and in vivo. We discover more than 200
proteins that are differentially regulated in hippocampal
excitatory neurons by exposing mice to an environment with
enriched sensory cues. Our approach can be used to isolate,
analyze and quantitate cell-type-specific proteomes and their
dynamics in healthy and diseased tissues.
Measuring the proteomes of specific cell types and analyzing their
similarities and differences is essential for understanding both the
function and dysfunction of multi-cellular organisms. Bio-orthogonal
strategies based on metabolic precursors allow labeling of proteins
or the introduction of measurable protein modifications1–3. Because
the incorporation of precursors into proteins requires processing by
endogenous cell machinery, bioorthogonal labeling strategies are particularly amenable to genetic control. For example, the expression
of a methionyl-tRNA synthetase (MetRS) with an expanded aminoacid binding site (MetRS L274G) enables the methionine tRNA to be
charged with the methionine surrogate azidonorleucine (ANL) 4. By
controlling transcription of a gene encoding MetRS L274G with celltype-specific promoters it is possible to direct cell-type-specific incorporation of ANL into nascent polypeptides, which can then be tagged
by a CLICK reaction and imaged or isolated by affinity purification5.
Adding to recent advances in invertebrate model organisms6,7, we
implemented and developed MetRS L274G in mouse, the most versatile mammalian genetic model organism. We engineered a mouse
line in which the conditional expression of MetRS L274G is under the
control of Cre recombinase. When crossed with animals expressing
Cre under the control of a cell-type-specific promoter, this approach
enables the metabolic labeling of proteins in any cell type for which
a Cre-driver mouse line exists. Using our method we labeled, visualized and identified nascent proteins in excitatory principal neurons
(hippocampus) and Purkinje neurons (cerebellum).
To enable cell-type-selective non-canonical amino-acid tagging in
mammals, we cloned and mutated the mouse MetRS to introduce a
L274G point mutation at the position analogous to the L13 position
in the bacterial protein (Fig. 1a)4,8. Mouse MetRS L274G (MmMetRSL274G, hereafter referred to as MetRS*) was co-expressed with
green fluorescent protein (GFP) from a GFP-2A-MetRS* construct
(Supplementary Figs. 1a and 2g). To test conditional protein metabolic labeling in mammalian cells, we performed bio-orthogonal
non-canonical amino-acid tagging (BONCAT)2 in COS7 or HEK
cells transfected with GFP-2A-MetRS* after metabolic labeling with
ANL. As expected, ANL incorporation into protein was detected only
in cells expressing MetRS*, and could be detected after ANL incubation periods as short as 20 min (Supplementary Figs. 1b and 2a–c).
Proteins in MetRS*-expressing (HeLa) cells treated with ANL exhibited turnover rates indistinguishable from controls (Supplementary
Fig. 2d–f).
To enable in vivo cell-type-specific nascent proteome labeling, a
transgenic mouse line was generated by inserting a floxed-STOP version
of the GFP-2A-MetRS* construct for conditional expression under a
CAG promoter9 in the ROSA26 (R26) locus10 (Supplementary Fig. 1a).
To assess conditional expression in specific neuronal types in vivo,
R26-MetRS* mice were crossed with two different Cre-driver lines:
CaMK2a-Cre and glutamic-acid decarboxylase 2 (GAD2-Cre), to
induce GFP-2A-MetRS* expression in glutamatergic (excitatory) neurons11 and GABAergic (inhibitory) neurons12 (Online Methods and
Supplementary Fig. 1d,e). To visualize GFP-2A-MetRS* expression,
whole brain slices were immunolabeled with an anti-GFP antibody.
In CaMK2a-Cre::R26-MetRS* mice, MetRS* expression was primarily restricted to hippocampal CA1 pyramidal (excitatory) neurons,
dentate granule (excitatory) cells and to neurons in the striatum and
1Max
Planck Institute for Brain Research, Frankfurt, Germany. 2Max Planck Institute of Biophysics, Frankfurt, Germany. 3Institute for Pharmacology and Toxicology,
Otto von Guericke University, Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany; and Center for Behavioral Brain Sciences, Magdeburg,
Germany. 4Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California, USA. 5Present address: Center for Psychiatry and
Neurosciences, Inserm 894, Paris, France. 6These authors contributed equally to this work. Correspondence should be addressed to E.M.S. (erin.schuman@brain.mpg.de).
Received 12 December 2016; accepted 19 October 2017; published online 6 November 2017; doi:10.1038/nbt.4016
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a
MetRS
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G274
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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
FUNCAT
FUNCAT (CA1)
Figure 1 Genetically targeted protein labeling. (a) A single mutation
(L274G) in the amino acid binding site of methionyl-tRNA synthetase
(MetRS) enables the loading of the methionine surrogate azidonorleucine
(ANL) onto methionine tRNA, and hence the bioorthogonal tagging of
nascent proteins synthesized in the cells that express MetRS*.
(b) Workflow for the preparation of acute hippocampal sections from
CaMK2a-Cre::R26-MetRS* or WT animals and incubation for 4 h with
ANL ex vivo. (c) GFP expression and nascent protein labeling in acute
hippocampal slices from CaMK2a-Cre::R26-MetRS* mice incubated
with ANL for 4 h. CA3, Cornu Ammonis 3; CA1, Cornu Ammonis 1; DG,
dentate gyrus. Note the FUNCAT signal in the apical dendrites of CA1
pyramidal cells (arrow). Scale bars, 100 µM, 50 µM and 50 µM, from left
to right. (d) Cultured hippocampal neurons expressing GFP-P2A-R26MetRS* were labeled with ANL for 1 h, and the subcellular localization of
newly synthesized Drebrin, GluA1 and Lamin proteins was evaluated using
FUNCAT-PLA. Scale bar, 25 µM See Supplementary Figures 1–4.
cortex (Supplementary Figs. 1d and 3a,b). In contrast, in GAD2Cre::R26-MetRS* mice, MetRS* expression was most prominent in
Purkinje (inhibitory) neurons of the cerebellum (Supplementary
Figs. 1d and 3c,d). To examine the potential for labeling and visualizing nascent proteins in a genetically targeted cell type, hippocampal
slices from CaMK2a-Cre::R26-MetRS* or wild-type mice were prepared and incubated with artificial cerebrospinal fluid (ACSF), supplemented with ANL or methionine and then processed for fluorescent
non-canonical amino-acid tagging (FUNCAT), enabling visualization
of newly synthesized proteins in situ13 (Fig. 1b). As expected, MetRS*
expression in CA1 pyramidal neurons coupled with ANL treatment
resulted in a strong FUNCAT signal; newly synthesized proteins were
clearly visible in neuronal somata and in dendrites (Fig. 1c), whereas
no signal was detectable in other cell types (e.g., astrocytes) or in Mettreated slices (Supplementary Fig. 4a). Similar results were obtained
from MetRS* brain slices transduced with a Cre-containing virus
(Supplementary Fig. 4c). Neither expression of the MetRS* transgene
nor exposure of hippocampal slices to ANL affected synaptic transmission in the hippocampal slice (Supplementary Fig. 4b).
Using a recently described technique14 we were also able to label
newly synthesized proteins of interest, including the synaptic proteins
Drebrin (Dbn) and a glutamate receptor (GluA1) as well as the nuclear
protein Lamin, in cultured MetRS*-expressing hippocampal neurons
treated with ANL (Fig. 1d). Nascent Dbn and GluA1 were clearly visible
in both the soma and dendrites of MetRS*-expressing neurons (but not
neighboring neurons), whereas the nascent Lamin was confined to the
somatic compartment (Fig. 1d). Besides the visualization of nascent proteins of interest in cell types of interest, these data show that labeling with
ANL does not perturb the normal localization of labeled proteins.
To label newly synthesized proteins in vivo, CaMK2a-Cre::R26MetRS* (or control WT) mice were supplied with drinking water
supplemented with ANL (16–60 mM) and maltose (to increase water
intake) (Fig. 2a). Different amounts of ANL and labeling periods
were tested (Supplementary Fig. 5a,b); consumption of ANL had no
apparent behavioral effect in WT or MetRS* mice (Supplementary
Fig. 5c,d). After 21 d of ANL consumption, the hippocampus was
dissected and a click reaction with a biotin alkyne tag was performed in order to visualize or identify the nascent proteome in
excitatory neurons (Fig. 2a). Nascent labeled proteins, detected using
FUNCAT13, were clearly visible in hippocampal neurons expressing MetRS* (Fig. 2b). Western blot analysis revealed an abundance
of biotinylated nascent proteins, spanning all molecular weights, in
hippocampal tissue from the CaMK2a-Cre::R26-MetRS* and much
lower background levels of biotinylated proteins obtained from the
WT mice (Fig. 2b and Supplementary Fig. 5a,b). For protein purification, metabolically labeled proteins were clicked with a cleavable biotin-alkyne tag, affinity-purified and then selectively eluted
by the cleavage and reduction of the alkyne. Eluted proteins were
digested and identified using liquid-chromatography-coupled tandem mass spectrometry (Supplementary Fig. 5e). To identify the
CaMK2a hippocampal proteome, we analyzed proteins that were
detected exclusively or enriched in CaMK2a-Cre::R26-MetRS*
compared to the corresponding WT control experiments. To this
end, we filtered for proteins exclusively detected in CaMK2a samples
(in three of six replicates and in none of the WT samples) and for
proteins more than threefold enriched in at least three biological
CaMK2a replicates (Supplementary Fig. 6). We detected a total of
2,384 proteins (1,110 unique proteins and 1,274 enriched proteins;
Fig. 3c,d, Supplementary Table 1 and Supplementary Fig. 7a). To
address whether the ANL-labeled proteome is biased, we compared
the protein lengths and methionine content of the CaMK2a-Cre::
R26-MetRS* proteome to other proteomes and found no significant
difference (Supplementary Fig. 7b,c).
To understand the functional nature of the CaMK2a hippocampal proteome, we performed a gene ontology (GO) analysis for
cellular components and processes and found a significant enrichment of proteins represented by neuronal components (Fig. 2e and
Supplementary Table 2). Importantly, terms associated with synaptic transmission and synaptic plasticity were among the most
significantly enriched GO groups, thus supporting the fidelity of the
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Camk2
WT MetRS*
c
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Enriched proteins
250
Protein intensities in MetRS*
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20
© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
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34
29
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Disease-related proteins
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40
App
Grm5
Htt
Prnp
Shank2
Snca
Alzheimer
Autism
Huntington
Creutzfeldt-Jakob
Autism
Parkinson
Protein RNA
0.4
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BONCAT
Proteins
Cell recognition
NADH metabolic process
NAD metabolic process
Negative regulation of dendrite development
Regulation of postsynaptic membrane potential
Excitatory postsynaptic potential
Sodium ion transmembrane transport
Action potential
Regulation of synaptic transmission, glutamatergic
Regulation of dendritic spine morphogenesis
Regulation of long-term neuronal synaptic plasticity
Regulation of synaptic vesicle cycle
Regulation of adherens junction organization
G-protein coupled receptor signaling pathway, coupled to
adenylate cyclase-modulating G-protein coupled receptor
Cell-cell recognition
Response to ammonium ion
Negative regulation of dendrite morphogenesis
Hydrogen ion transmembrane transport
Regulation of synaptic vesicle exocytosis
Regulation of peptidyl-threonine phosphorylation
Motor neuron axon guidance
Negative regulation of dendritic spine development
Negative regulation of adherens junction organization
Protein localization to synapse
****
MS
CA1 pyramidal cells
bFUNCAT
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marker enrichment
Gene ontology
(top 25 cellular processes) 0 1 2 3 4 5 6
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vs WT
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Neurons
e
Slice
–0.1
–0.2
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ANL
Enrichment compared to whole hippocampal proteome
a
Figure 2 Cell-type-specific proteomics in vivo: the hippocampal excitatory neuron proteome. (a) CaMK2a-Cre::R26-MetRS* mice were provided with
ANL in their drinking water and their brains were collected and processed for FUNCAT (Supplementary Fig. 5) or BONCAT and protein identification
by mass spectrometry (MS). (b) FUNCAT of in vivo-labeled proteins in MetRS* mice (left panel) and BONCAT in WT or MetRS* mice that were
provided with ANL (60 mM) for 21 d. Scale bar, 20 µM. (c,d) Labeled (biotinylated) proteins were affinity purified, digested and identified by peptide
fingerprinting. Scatter plot showing the increased levels (peptide intensities) of proteins found in both MetRS*and WT mice (n = 6 biological replicates
for each group) (c). The hippocampal excitatory neuron proteome was obtained by the union of proteins unique to or markedly enriched (over threefold
difference from WT) in MetRS* mice (d). (e) Gene ontology analysis. Top 25 cellular processes enriched in the hippocampal excitatory neuron proteome
(−log [P values]). Note the presence of multiple terms related to synaptic transmission and plasticity (bold). (f) Example proteins of particular clinical
relevance found in the hippocampal excitatory proteome. (g) Relative abundance of previously identified brain-cell-type markers in hippocampal
excitatory neuron proteome as compared to the hippocampal proteome. In the left bar, note the de-enrichment for glial markers and to the right, the
enrichment for neuronal and CA1 pyramidal neuron markers. See Supplementary Figures 5–7.
cell-type-specific labeling of excitatory neurons. In addition, within
the excitatory neuron proteome we detected several key proteins, the
mutations of which give rise to important neurodevelopmental or
neurodegenerative disorders (Fig. 2f). To further confirm the cell
specificity of the CaMK2a hippocampal proteome, we focused on
cell-type-specific markers defined by proteomic and transcriptomic
studies. Compared to a whole hippocampal proteome, our data set
was significantly de-enriched for glial cell markers and enriched for
general neuronal and CA1-pyramidal neuronal markers (P < 0.05,
Fig. 2g and Supplementary Table 3).
To examine the versatility of our method, we analyzed the cellular
identity of the proteome obtained from the cerebellum of GAD2::R26MetRS* mice, where (inhibitory) Purkinje cells are predominantly
labeled (Supplementary Figs. 6, 7 and 8a). A comparison with proteins labeled in control WT mice yielded 1,687 proteins in the GAD2
cerebellar proteome (Supplementary Fig. 8b,c and Supplementary
Table 4). A GO analysis revealed a significant enrichment of proteins and terms related to metabolism (Supplementary Fig. 8d and
Supplementary Table 5). This finding is in good agreement with the
special metabolic requirements observed in Purkinje cells15. As above,
an analysis of cell-type-specific markers revealed a de-enrichment for
glial markers and enrichment for neuronal markers and Purkinje neuron markers (Supplementary Fig. 8e and Supplementary Table 3).
We next compared the hippocampal excitatory to the cerebellar
inhibitory proteome and discovered 95 and 70 ‘unique’ proteins in
each proteome (Fig. 3a, Supplementary Fig. 6 and Supplementary
Table 6). By comparing the peptide intensities of the shared (1,382)
proteins we discovered 180 and 188 proteins that were significantly
enriched in the hippocampal excitatory or cerebellar inhibitory proteomes, respectively, likely reflecting important functional differences
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in the cell types (permutation-based false discovery rate of 2%, S0=0.1;
Fig. 3b and Supplementary Table 6). Among the most enriched proteins in the excitatory hippocampal proteome, we found important
synaptic proteins such as Dlg4 (PSD-95; ref. 16), a multi-functional
scaffolding molecule, and Nckap1, a regulator of the actin cytoskeleton17. Consistent with the established role of the hippocampal excitatory
neurons in learning, we also found enriched proteins related to synaptic
plasticity and learning such as Ncdn (neurochondrin18). Intriguingly,
we also identified several disease-related proteins such Cyfip2, a protein
related to Fragile X syndrome19, and Dync1h1, a protein associated with
axonal transport implicated in Charcot–Marie–Tooth disease20. Among
the most upregulated proteins in the cerebellar inhibitory proteome was
calbindin-1, a canonical Purkinje cell marker and Itpr1, a regulator of
calcium channel activity linked to cerebellar Ataxias21.
We carried out a hierarchical clustering of all proteins expressed
in both cell types, sorting proteins by expression levels (Fig. 3c). As
expected, this showed a consistent pattern of expression within each
cell type, but also revealed the two proteomes were distinguishable
on the basis of differential expression of proteins. Lastly, in order
to examine whether the proteomic data obtained were sufficient to
separate distinct tissues and cell types, we conducted a principal
component analysis (PCA) including comprehensive hippocampal,
cerebellar and glial proteomes (Supplementary Figs. 6 and 7a). The
PCA (Fig. 3d) illustrates that the CaMK2a hippocampal proteome
and the Gad2 proteome were clearly separated, and the proximity
of each to its tissue of origin proteome was also apparent (Fig. 3d).
Taken together, these data indicate that this methodology allows for
the identification of cell-type-specific proteomes labeled in vivo in
complex tissues without mechanical dissociation and isolation of
specific cell types.
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CaMK2a
Gad2
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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
95
Normalized log2 LFQ intensity
15
Component 1 (64.5%)
Figure 3 Cell-type-specific proteomics in vivo. Comparison of hippocampal
excitatory neuron and the cerebellar inhibitory neuron proteomes.
(a) Venn diagram depicting the numbers of proteins found only in the
hippocampal excitatory neuron proteome, the cerebellar inhibitory neuron
proteome or both proteomes. (b) Relative abundance of proteins found
in both neuronal types in both proteomes (Volcano plot). Shown are folddifferences of protein relative expression (x axis), statistical significance
of the enrichment (y axis) and detection threshold based on false-discovery
rates (permutation-based) of 2%, S0 = 0.1; thin black lines. Shown
in colored dots are proteins significantly enriched in the hippocampal
excitatory proteome (left side) or the Purkinje neuron proteome (right
side), proteins expressed at similar levels (gray dots). The top five proteins
with highest enrichment in each group are labeled. (c) Hierarchical
clustering of proteins common to hippocampal excitatory neuron and
cerebellar inhibitory neuron proteome showing the net separation (see
upper brackets) of the multiple biological replicates (n = 3) analyzed
for each neuronal type. LFQ, label-free quantification. (d) Principal
component analysis (PCA) showing the net segregation of the hippocampal
excitatory neuron and cerebellar inhibitory neuron proteomes, whole
hippocampus and cultured glial cells (3–6 biological replicates each)
based on two components accounting for ~64% and ~9% of the variability
in protein expression levels. See Supplementary Figures 6–8.
External stimuli lead to changes in cellular proteomes that represent responses or adaptation. To examine whether our method
can also detect proteome dynamics, we exposed CaMK2a-Cre::R26MetRS* mice to an enriched sensory environment (Fig. 4a), which
has been shown to modify brain circuits, changing the density of
synapses and increasing the volume of the cerebral cortex22. We
compared the CaMK2a hippocampal proteomes of mice housed in
an enriched environment (EE) to mice that were housed in standard cages (SC) for 21 d. As expected, the two proteomes (2,384
and 2,365 for SC and EE, respectively) (Supplementary Fig. 6 and
Supplementary Tables 1 and 7) were largely overlapping (87.2% of
the EE proteome was detected in the SC proteome), but 225 proteins
were significantly regulated, either increased or decreased in expression between the two environments (permutation-based false discovery rate of 2%, S0=0.1; Fig. 4b and Supplementary Tables 8 and 9).
The significantly differentially expressed proteins were enriched for
neuron and synapse function (Fig. 4c) and included many important signaling molecules, especially those related to protein translation (e.g., MTOR, Raptor, Eif4a1 and Eef2) and degradation (e.g.,
Ubr4, Ubqln1, Psma6 and Trim3) (Fig. 4b and Supplementary
Fig. 9a,b). Additionally, proteins involved in the synaptic vesicle cycle
(e.g., Cplx2, Syt12, Vamp1, Amph and SNCA), synapse-organizing
cell adhesion molecules and scaffold proteins (e.g., Shank1, Ctnnd2,
Ncam2, and Dlg2), and GABA receptor subunits (Gabbr1 and 2) were
regulated (Fig. 4d). Atl1 and Itpka, for example, have been previously
linked with alterations in spine morphology and dynamics23. Taken
together, these data demonstrate that genetically targeted protein
labeling in MetRS* mice possesses sufficient sensitivity to capture
adaptive changes in cell-type-specific proteomes in vivo.
Application of our conditional MetRS* expression enabled us
to purify and identify 3,969 proteins in two neuronal types labeled
in vivo over a time course of 21 d. Importantly, we show that ANL
crosses the blood–brain barrier and that reliable protein labeling can
be achieved in animals heterozygous for the MetRS* transgene, which
will greatly facilitate the use of the mice in a broad array of Cre-drivers
or disease models. A wealth of isotopic metabolic labeling and quantitative proteomics approaches have recently been developed (e.g.,
SILAC)24 that can track increasingly subtle changes in proteome dynamics and post-translational modifications25. These isotopic labeling techniques are compatible with the use of non-canonical amino acids and
BONCAT26–28 and can thus now, in principle, be targeted to specific
cell types in vivo in R26-MetRS* mice. Alternatively, or in combination,
mice could be raised on an ANL diet and then the conditional expression
of MetRS* could be driven by a drug-inducible system, or in neurons,
via an activity-dependent promoter, enabling a comparison of nascent
protein expression in different control and experimental animals.
Using our CaMK2a-Cre::R26 mouse, we identified with cell-type
resolution 225 proteins that changed expression levels in excitatory
hippocampal neurons following environmental enrichment. Not surprisingly, many of the identified proteins are associated with synapses
or their regulation. Intriguingly, proteins associated with protein
synthesis and degradation were up- or downregulated. Both protein
synthesis and degradation are of critical importance in the remodeling of synaptic proteomes, especially associated with information
storage29. A previous study in rodents30 examined environmentinduced changes in hippocampal proteins using two-dimensional
gels, but unique protein quantification was not confirmed with mass
spectrometry; we nevertheless identified several potentially overlapping proteins (Supplementary Table 8). It is notable that the proteins
we identified reside in excitatory hippocampal neurons, which are
crucial for spatial navigation and spatial memory31. The excitatory
neurons in hippocampal area CA1 represent an animal’s location in
the environment32. The proteomic changes we identify in the circuits
responsible for sensing and encoding the spatial environment might
suggest that ‘perception’ of the environment is altered as a result of
the enriched experience.
We found multiple brain-disease-related proteins in the hippocampal excitatory neuron proteome. Surprisingly, a large fraction of the
proteins (~30%) that were regulated by exposure to an enriched environment were also associated with disease. Most disease-related proteins are expressed in numerous cell types and tissues, complicating
any analysis that endeavors to examine whether disease phenotypes
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a
Standard
b
Enriched environment
EE 120 proteins
c
EE 105 proteins
Enrichment
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Rptor
Gene ontology
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Soga3
Ubr4
Gabbr1
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Usp7
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Cell projection
Acap
Spectrin
Psmc3
Spectrin-associated cytoskeleton
Acat 1
Vps13c
Synapse part
Dnpep
Rab3b
2
Extracellular region part
Hnrnpa0
Sod1 Vdac1
Prdx2
Pccb
Sgta
Dctn2
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Extracellular vesicle
Extracellular organelle
Mif
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Endocytosis
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Itsn1
Ywha/b/e/q/z
T
© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
Cytosol
Uncoating
Dbn
Ca2+
Ank3
Sh3gl/2/b2
Snph
Mitochondria
Arpc3
Atcay
Calb1
Sptbn
Endosome
fusion
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acidification
Snca
Rab3b/c
Atp2b4
Cplx2
Neurotransmitter
uptake
Ca2+
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Endosome
fusion
Dlgap2
Syne1
Add2
Brsk1
Trim3
Itpr1
Vamp1
Atl1
Bsg
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MTor Rufy3
Fus
Upf1
Rptor
Csnk2a1
Rasgrf1 Iqsec2
Pacsin1
Ncam2
Ptprz1
Gabbr1
Ywha/b/e/q/z
Nedd4
Shank1
Sgta
Gabbr2
Nos1
Adgrb/2/3
Rapgef4
Cytoskeleton
Sipa1l1
Figure 4 The CaMK2a excitatory hippocampal proteome in an enriched environment (EE). (a) Top-down and side-views of the standard cage and EE
cages. In the EE cage, a maze (with changeable side walls) was present on the top floor and toys of different sizes, textures and colors were added.
(b) Relative abundance of proteins detected in both the standard cage and EE proteome (Volcano plot). Fold-differences of relative protein expression
(x axis) is plotted against the statistical significance of the detection (y axis). The significance threshold is based on false-discovery rates (permutationbased) of 2%, S0=0.1; thin black lines. Proteins significantly de-enriched (left side) or enriched (right side) in the EE proteome are shown in dark
purple and magenta, respectively (non-differentially expressed proteins in gray). The top ten proteins with highest enrichment in each group are
labeled. (c) Gene ontology analysis. Selected cellular processes significantly over-represented in the EE hippocampal excitatory neuron proteome
(−log (P values)). Note the presence of multiple terms related to neuronal compartments and synapses (bold). (d) Scheme of presynaptic terminal and
postsynaptic compartment showing proteins important for synaptic function or the regulation of synaptic function that were significantly regulated
following exposure to the EE (proteins obtained from the Volcano plot in b). See Supplementary Figures 6, 7 and 9.
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letters
arise from particular cell types. Our findings show that within excitatory hippocampal neurons, not only were synaptic-disease-related
proteins regulated by the enriched environment but also proteins
involved in mRNA processing, protein translation and degradation,
mitochondrial function and oxidative stress. We conclude that a surprisingly high proportion of proteins regulated in excitatory neurons
by an enriched environment contribute—when misregulated—to a
cohort of different brain diseases (Supplementary Fig. 9b).
With increasing sequencing depth, it has become clear that many
genes thought to be specifically expressed in a particular cell type are
also present at detectable levels in other cells. In our experiments we
focus on the enrichment or de-enrichment of proteins in different
samples. To refine the molecular resolution of cellular phenotype,
combination of mRNA transcripts with spatial localization can provide deeper phenotyping33,34. The addition of our targetable proteome
identification strategy will add a spatial and temporal dimension to
our understanding of cellular identity and proteome dynamics in both
normal and diseased tissue.
Methods
Methods, including statements of data availability and any associated
accession codes and references, are available in the online version of
the paper.
Note: Any Supplementary Information and Source Data files are available in the
online version of the paper.
Acknowledgments
We thank H. Geptin, D. Vogel, N. Fuerst, I. Wüllenweber and F. Rupprecht for
excellent technical assistance. We thank E. Noll for the synthesis of ANL and
P. Landgraf for the synthesis of the SH-alkyne. We thank S. Garg for her help with
FUNCAT and M. Heumueller for his help with some of the experiments. We thank
R. Pieaud and S. Junek for their assistance with imaging. We thank F. Kretschmer
for his help with the open field analysis. We thank E. Northrup, S. Zeissler, S. Gil
Mast and the animal facility of MPI for Brain Research for their excellent support.
We thank J. Sanes and J. Chakkalakal for the early generation of a Thy-1 MetRS*
mouse. Work in the laboratory of E.M.S. is supported by the Max Planck Society,
the European Research Council, DFG CRC 902 and 1080, and the DFG Cluster of
Excellence for Macromolecular Complexes. B.A. was supported by a Marie Curie
Intra-European Fellowship for career development. C.H. was supported by a Marie
Curie Career Integration Grant. D.C.D. is supported by DFG CRC 779 and 854.
Research on proteomic labelling at Caltech is supported by the Programmable
Molecular Technology Initiative of the Gordon and Betty Moore Foundation.
AUTHOR CONTRIBUTIONS
B.A.-C., C.T.S. and C.H.: conception and design of experiments, acquisition,
analysis and interpretation of data. C.G., S.t.D. and A.R.D.: conception and design
of experiments, acquisition of data. I.B., B.N.-A. and E.C.: acquisition of data.
A.M.: provided reagents. D.D.: provided reagents and advice on experiments.
D.A.T.: conception and design of experiments. J.D.L.: acquisition of data, analysis
and interpretation of data. E.M.S.: conception and design of experiments, analysis
and interpretation of data, drafting, writing and revising the article. All authors
contributed to the writing and revision of the manuscript.
COMPETING FINANCIAL INTERESTS
The authors declare no competing financial interests.
Reprints and permissions information is available online at http://www.nature.com/
reprints/index.html. Publisher’s note: Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
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advance online publication
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ONLINE METHODS
© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
Please also see the Life Sciences Reporting Summary for detailed information
on experimental design and reagents.
ANL synthesis. Azidonorleucine (ANL) was synthesized as previously
described4.
Constructs, cell culture and transfection. The mouse MetRS ORF (I.M.A.G.E
clone 6416029, GenBank ID BC079643, ATCC) was cloned by PCR into pEGFPC1 (Clontech). GFP-MetRS L274G (MetRS*) was generated by site-directed
mutagenesis (Stratagene). GFP-2A-MetRS* was generated by inserting a
sequence encoding for the foot-and-mouth disease virus 2A peptide sequence35
between GFP and MetRS* (Genscript). HEK, COS7 and HeLa cells (ATCC) were
maintained in Dulbecco’s modified Eagle’s medium (DMEM, Invitrogen) supplemented with 10% FCS (FCS) at 37 °C in a 5% CO2 atmosphere and transfected
with X-tremeGENE9 (Roche) according to the manufacturer’s instructions. Lack
of cell line contamination with mycoplasma was checked by PCR (eMyco detection kit, Intron Biotechnology). Experiments were performed 24–48 h posttransfection. For metabolic labeling, cells were incubated in methionine-free
DMEM (Invitrogen) supplemented with FCS and 4 mM l-methionine (Sigma),
or ANL for 20 min to 5 h, 40 µM anisomycin was added as indicated.
Antibodies. The following antibodies were used for immunofluorescence labeling (IF) and/or immunoblotting (IB) at the indicated dilutions: mouse antibiotin (IF and IB, 1:1,000, Sigma) or rabbit anti-biotin (IF and IB, 1:1,500, Cell
Signaling) or rabbit anti-GFP (IF and IB 1:750, Invitrogen) and/or chicken antiGFP (IF, 1:500; IB: 1:1,000; Aves), rabbit anti-parvalbumin (IF Swant 1:5,000),
goat anti-chicken Alexa 647 (IF, 1:750; IB, 1:7,500; Invitrogen), goat antirabbit Rhodamine RX (IF, 1:800, Jackson laboratory), goat anti-rabbit FITC
(IF, 1:800, Jackson laboratory), goat anti-mouse or anti-rabbit IR680 or IR800
(IB, 1:10,000, Licor), Gp anti-MAP2 (1:1,000, SYSY). Antibodies used for the
PLA experiments: rabbit anti-Lamin 1:1,000 (Abcam), rabbit anti-Debrin 1:500
(Sigma), rabbit anti-GluA1 1:500 (Abcam). Mouse anti-far red (1:100, Abcam).
In IF experiments DAPI was added to the secondary antibody solutions.
Organotypic slice culture and viral transduction. 450 µm hippocampal slices
were prepared from P5-P6 pups with a McIllwain tissue chopper and maintained, as previously described by others36. Slices were virally transfected after
24 h in vitro with a Cre-expressing recombinant adeno-associated virus (CMV
mCherry-2A-Cre rAAV, serotype 1:2, Open BioSystems). For metabolic labeling, 4 mM methionine or ANL were added to the standard slice maintenance
medium36 for up to 9 d.
Transgenic animals. The cassette - STOPFLOX - GFP-2A-MetRS*- expressed
under the control of the CAG actin-derived promoter knock-in in the mouse
ROSA26 locus10 was performed by recombination-mediated cassette exchange
(RMCE)37 in embryonic stem cells (Taconic GmbH). For activation of the
transgene in CA1 pyramidal neurons, homozygote STOPflox R26-MetRS* animals were crossed with homozygote CaMK2a-Cre T29-1 mice11 (Jackson laboratory, line #005359) or Gad2-Ires-Cre12 (Jackson Laboratory, line #010082).
Genotyping was done by PCR (see Supplementary Table 10 for primer list and
size of expected bands). All the procedures involving animals were performed
under protocols compliant with and approved by the Hessen Animal Welfare
Authority (protocols V54-19c20/15-F122/14 and V54-19c20/15-F126/1012)
and the Max Planck Society.
Acute hippocampal slices. 450–500 µm hippocampal slices were prepared
from adult animals (6 to 7 weeks old) with a McIllwain tissue chopper and
incubated at 30 °C in artificial cerebral spinal fluid (ACSF; in mM, NaCl 125,
NaHCO3 25, KCl 2.5, NaH2PO4 1.25, glucose 25, CaCl2 2, MgCl2 1) oxygenated by a 95/5 (v/v) O2/CO2 gas mixture. Slices were metabolically labeled
for 3–4 h with 4 mM methionine or ANL in the same medium or, when the
metabolic labeling was conducted in vivo, directly processed for FUNCAT,
as described below.
Fluorescent non-canonical amino-acid tagging (FUNCAT) and immunolabeling. After metabolic labeling in vivo mice were euthanized after anesthesia with isofluorane and transcardially perfused with PBS supplemented with
doi:10.1038/nbt.4016
20 mM methionine. Acute or organotypic slices were rinsed twice in ACSF
and fixed in 4% PFA in PBS for 20 min at RT. Fixed slices were then washed in
PBS and stored at 4 °C in the same buffer until processed further. Slices were
then mounted in 4% agar (w/v) and resliced at 30 or 50 µm with a vibratome
(Leica), incubated overnight at 4 °C in blocking buffer consisting of 0.5% Triton
X100 and 10% goat serum in PBS, 5% sucrose, 2% fish skin gelatin. Samples
were washed two times in PBS pH 7.8 and “clicked” overnight with biotinalkyne (PEG4 caboxamide-propargyl biotin, Molecular Probes) as previously
described4. After extensive washing, slices were incubated overnight at 4 °C
with anti-GFP and anti-biotin primary antibodies in a twofold dilution of the
blocking buffer, washed in 0.1% Triton in PBS and incubated for 3 h at RT with
secondary antibodies and DAPI in diluted blocking buffer. Slices were then
washed in PBS/Triton and then in PBS and mounted on microscope slides.
Fluorescence imaging was performed with a LSM780 laser scanning confocal
microscope (Zeiss) with ×20 (NA 0.8) or ×40 (NA 1.4) objectives with appropriate excitation laser lines and spectral detection windows.
MetRS* transfection, metabolic labeling and FUNCAT-PLA in cultured neurons. Neurons were transfected with Magnetofectamine (Life Technologies)
with 1.5 µg of DNA per 40 K neurons for 25 min. One day after transfection
the neurons were starved for 5 min in methionine-free Neurobasal A, B27,
Glutamax and labeled for 1 h in methionine-free Neurobasal A, B27, Glutamax
and 4 mM ANL. After the labeling the neurons were incubated for 10 min in
Neurobasal A, B27, Glutamax, washed 2× with PBS, fixed in 4%PFA for 20 min
and permeabilized with 0.5% Triton-X100 in 4% of goat serum for 15 min. The
FUNCAT reaction was performed overnight at RT. using 0.4 µM of the far-red
alkyne (Thermo A10278). After the click reaction, the neurons were blocked
for 1 h and incubated for 1.5 h at RT with the corresponding antibody. The
FUNCAT PLA protocol was performed as described in ref. 14. In brief, after the
FUNCAT protocol, cells were blocked at RT for 1 h (blocking buffer (BB): 4%
goat serum in PBS pH7.4), and incubated with the first antibodies during 1.5 h
at RT, then washed 3×, 5 min with PBS pH7.4 at RT. PLA oligo-coupled secondary antibodies (Sigma: DU092004/2) were diluted 1:10 in BB and incubated for
1 h at 37 °C. Probe ligation was performed during 30 min at 37 °C and washed
5× with buffer A (Sigma: 82047). Amplification buffer (Sigma; DU092008)
was added for 90 min. Cells were washed quickly twice, then 1 ×10 min
with buffer B (Sigma: 82048), and 2× quickly with PBS. Neurons were postfixed for 10 min (PBS pH7.4, 1 mM MgCl2, 0.1 mM CaCl2, 4% PFA, 4% w/v
sucrose) washed 5× with PBS and blocked for 1 h. Alexa-conjugated secondary
antibodies were added for 30 min, washed 3 × 5 min with PBS and imaged.
ANL administration to living animals. To achieve a deeper protein labeling
for the generation of neuronal-specific proteomes 6-week-old WT or R26MetR* mice were fed a low methionine diet (diet containing 0.1% methionine)
(Ssniff, Germany) beginning 1 week before labeling and were then provided
with 60 mM ANL for 21 d. ANL was provided in drinking water supplemented
with 7% l-maltose (Sigma) to increase water intake38, resulting in an average
daily ANL intake of 0.9 ± 0.1 (mean ± s.d.) mg/day/g body weight.
Open field experiments. After feeding the mice with ANL for 21 d, individual
animals were deposited in the center of the open field arena (100 × 100 × 30 cm).
The arena was divided in two different equally sized areas (inner and outer).
The light intensity was adjusted to 180 lx. Motor behavior movement was
evaluated during the 10 min after the initial deposition of the mouse into the
arena. Gad2-Cre::MetRS* and CaMK2a-cre::MetRS* were compared with WT
mice drinking ANL and with WT mice raised in the same conditions as the
ANL-drinking animals.
Enriched environment. Mice (6 weeks of age) were raised in Marlau cages
during the 21 d of the ANL-labeling. The labyrinth, running wheels and toys
were changed every 2 d to increase novelty. Small pieces of food were hidden
into the toys or bedding material to encourage exploratory behavior. Odors
were incorporated in toys and small pieces of food using Vanilla flavoring
(McCormick).
Electrophysiology. 500 µm hippocampal slices were prepared from 5-weekold MetRS* or WT mice using a Leica vibratome in cold ACSF-sucrose solution
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© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
(concentrations in mM as follows: NaCl 87; NaHCO3 25; NaH2PO4 1.25;
KCl 2.5; glucose 10; sucrose 75; CaCl2 0.5; MgCl2 7). Slices were recovered
submerged in oxygenated (95/5 O2/CO2) recovery/recording ACSF (concentrations in mM as follows: NaCl 125; NaHCO3 25; NaH2PO4 1.25; KCl
2.5; Glucose 10; CaCl2 2; MgCl2 1) for 1 h. The slices were transferred to a
recording set-up, and recovered for an additional hour in an interface chamber perfused with carbogenated ACSF. A stimulating electrode and recording
electrode were placed in stratum radiatum. During the recordings, different
stimulation intensities were used to obtain the input-output curves.
Pulse-chase turnover experiment. HeLa cells were transfected with CMVMetRS*-P2A-GFP. Transfection efficiency was evaluated under the microscope; dishes in which ~50% of the cells were transfected were used for the
experiment. 2 d after transfection the cells were labeled with 80 µCi S35
Cysteine per million of cells ± 8 mM ANL in methionine-free DMEM. Cells
were labeled for 1 h or 2 h, to evaluate protein synthesis. After 2 h of labeling
media was washed out and replaced by DMEM with 50 µM CHX (SigmaAldrich), protein degradation was studied after 6 and 12 h chase periods.
BONCAT, immunoblotting and protein isolation for mass spectrometry.
Tissue was homogenized and lysed in PBS supplemented with 1% (w/v) Triton
X100 and 0.4% (w/v) SDS, protease inhibitors (PI, 1:750 dilution of protease
inhibitor cocktail 3 w/o EDTA, Calbiochem) and benzonase (Sigma, 1:1,000)
at 75 °C for 15 min. Lysates were then cleared by centrifugation and stored
at −80 °C until used. BONCAT was performed as previously described39. In
brief, 90 µg proteins were treated in 120 µL PBS pH 7.8 supplemented with
0.08% (w/v) SDS, 0.2% (w/v) Triton, 300 µM Triazol (Sigma, ref. 678937),
50 µM biotin-alkyne tag (Thermo, ref. B10185) and 83 µg/mL CuBr (prepared
by dilution of fresh 10 mg/mL solution in DMSO) at 4 °C overnight in the dark.
Biotinylated proteins were then separated by electrophoresis and immunoblotted with anti-GFP and anti-biotin antibodies (see above) or directly with
streptavidin-Alexa 800 (1:10,000 dilution, Invitrogen, ref. Q10173MP). All
full-length gels are shown in Supplementary Figure 10.
For mass spectrometry (MS) analyses, tissue was lysed in PBS supplemented
with 0.5% Triton, 1% SDS, PI and benzonase, heated at 75 °C for 15 min and
cleared by centrifugation. Cleared extracts were alkylated twice with 20 mM
iodoacetamide (3 h at RT in the dark) and then cleaned by two passages on
PD-SpinTrap G-25 columns (GE healthcare). Samples were then clicked in PBS
pH7.8 supplemented with 0.06% SDS, 0.06% of Triton X-100, PI as described
above with a cleavable biotin-S-S-alkyne (probe 14b in ref. 40). After click
chemistry, excess biotin-alkyne was removed on PD-SpinTrap G-25 columns.
Tagged proteins were then affinity-purified with high-capacity Neutravidin
agarose beads (Thermo) in PBS supplemented with 1% Triton, 0.15% SDS and
PI (binding buffer) overnight at 4 °C. The beads were then washed extensively
at RT, first in binding buffer, then PBS + PI, 50 mM ammonium bicarbonate
+ PI and finally eluted by incubation with 5% β-mercaptoethanol, 0.03% SDS
and PI for 30 min at RT. Two consecutive elutions were performed. Eluted
proteins were lyophilized, resuspended in water and processed for MS as outlined below.
MS sample preparation and analyses. Eluted proteins were processed using
a modified FASP workflow41 as described previously42. In brief, protein
extracts (whole samples for CaMK2a and Gad2) were cleaned and digested
sequentially with Lys-C and trypsin on Microcon-10 filters (Merck Millipore, #
MRCPRT010 Ultracel YM-10). Digested samples were desalted using ZipTips
according to the manufacturer’s instructions, dried in a Speed-Vac and stored
at −20 °C until LC-MS/MS analysis. Dried peptides were dissolved in 5% acetonitrile with 0.1% formic acid, and subsequently loaded using a nano-HPLC
(Dionex U3000 RSLCnano) on reversed phase columns (trapping column:
particle size 3 µm, C18, L = 20 mm; analytical column: particle size = 2 µm,
C18, L = 50 cm; PepMap, Dionex/Thermo Fisher Scientific). Peptides were
eluted in gradients of water (buffer A: water with 5% v/v dimethylsulfoxide
and 0.1% formic acid) and acetonitrile (buffer B: 5% dimethylsulfoxide, 15%
water and 80% acetonitrile (v/v/v) and 0.08% formic acid). All LC-MS-grade
solvents were purchased from Fluka. Gradients were ramped from 4% to 48% B
in 178 min at a flowrate of 300 nl/min. Peptides eluting from the column were
ionized online using a Thermo nanoFlex ESI-source and analyzed in a Thermo
nature biotechnology
“Q Exactive Plus” mass spectrometer or a Thermo “Orbitrap Elite” mass spectrometer. Mass spectra were acquired over the mass range 350–1,400 m/z
(Q Exactive Plus) or 350-1,600 m/z (Orbitrap Elite) and sequence information
was acquired by computer-controlled, data-dependent automated switching to
MS/MS mode using collision energies based on mass and charge state of the
candidate ions (full parameter set in Supplementary Table 11). All samples
were measured in (at least) triplicate LC-MS runs and the biological replicates
(one mouse represents one replicate) for each group are noted in the respective figure legends.
Raw MS data were processed and analyzed using MaxQuant43 (see parameters in Supplementary Table 11). In brief, spectra were matched to a Mus
musculus database downloaded from uniprot.org (reviewed and non-reviewed,
downloaded on May 13, 2016) and a contaminant and decoy database.
Precursor mass tolerance was set to 4.5 p.p.m., fragment ion tolerance to 20
p.p.m. (QExactive) or 0.5 Da (Orbitrap Elite), with fixed modification of Cys
residues (carboxyamidomethylation +57.021 Da) and variable modifications of
Met residues (Ox +15.995 Da), Lys residues (acetylation +42.011 Da), Asn and
Gln residues (deamidation +0.984 Da) and of N termini (carbamylation +43.006
Da). Peptide identifications were calculated with FDR < 0.01, and proteins
with one peptide per protein included for subsequent analyses. All proteomic
data associated with this study have been deposited to the ProteomeXchange
Consortium via the PRIDE44 partner repository with the data set identifier
PXD007703. Peptide intensities were analyzed with MaxQuant and Perseus45
(normalization of the intensities: mean centering; Volcano plots: two-sided
t-test, unpaired; segmentation analysis: number of clusters: 300, maximal
number of iterations: 10). Proteins only identified by reverse peptides were
removed. Protein intensities and LFQ label-free quantification intensities were
averaged over technical triplicates (representing different runs of the same
biological replicate) and log 2 transformed. The full proteomes (cerebellum,
hippocampus, glial cells) were analyzed by using proteins only quantified by ≥2
biological replicates. The protein intensities in each proteome were normalized
by adjusting the mean protein intensity (measured over all biological replicates)
to the value “10”. Proteins purified in the MetRS samples of the CaMK2a and
Gad2 replicates were compared to the corresponding WT samples. The fold
enrichment of each protein was calculated by subtracting the non-normalized
MetRS intensity from the intensity measured in the paired WT sample. Only
proteins detected exclusively in the MetRS samples or found to be ≥3 times
enriched in MetRS in three replicates or more (≥2 replicates in Gad2) were
retained for further analysis. The other proteins enriched or exclusively quantified in fewer replicates were analyzed separately to detect “unique” proteins for
the distinct proteomes (e.g., CaMK2a against Gad2). Proteins with no enrichment but quantified in ≥3 replicates of MetRS and WT were counted as overlapping proteins (overlap in Venn diagrams in Figs. 2 and 3 and Supplementary
Fig. 8). Proteins enriched or exclusively detected both in different MetRS and
WT replicates were also assigned to the overlap. Proteins enriched in MetRS
were filtered, retaining only proteins with LFQ intensities in ≥3 replicates (or
≥2 replicates in Gad2). LFQ intensities were normalized by adjusting the mean
LFQ intensity of each Gad2 experiment or the mean LFQ intensity of all CaMK2
replicates to “10”. Normalized LFQ intensities of the purified MetRS samples
were analyzed against the full proteomes using proteins only quantified in
all samples. For principal component analysis (without category enrichment),
missing protein intensities were replaced by their respective mean LFQ intensity. LFQ intensities of each CaMK2 and Gad2 replicate were mean-centered
and adjusted to “10”. Differentially regulated proteins in CaMK2-EE against
CaMK2-HC, and Gad2 against CaMK-HC were analyzed by a two-sided t-test
(number of randomizations: 250, permutation-based FDR = 2.0%, S0 = 0.1).
Common proteins were hierarchically clustered using the Euclidean distance
of averaged LFQ intensities (linkage) preprocessed with k-means (number of
clusters: 50, max. 10 iterations).
The criteria used for “unique” proteins in the comparative study between
Camk2a and the Gad2 proteomes was: for the “unique” proteins in Gad2;
proteins that were detected in ≤2 out of 6 replicates in Camk2a proteome. For
the “unique” proteins in Camk2; proteins detected in ≤1 out of 3 replicates in
Gad2 proteome (Supplementary Table 6). For the Venn diagram in Figure 3,
we used a more stringent criteria for the unique protein numbers: for the
“unique” proteins in Gad2; proteins that were detected in ≤0 out of 6 replicates in Camk2a proteome. For the “unique” proteins in Camk2; proteins
doi:10.1038/nbt.4016
© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.
detected in ≤0 out of 3 replicates in Gad2 proteome (Supplementary Table
6). For the comparative study of Camk2-SC and Camk2-EE we found 16 and
12 “unique” proteins, respectively. These proteins were identified in all the
replicates of each proteome and completely absent in the other (0 out of 6
replicates). Nevertheless, we did not analyze these proteins further because the
corresponding peptides exhibited variable and relatively low intensities.
For the analysis of the methionine content of the purified proteomes
(Supplementary Fig. 7c) the number of methionine residues per 100 amino
acids was counted from the full protein sequences. The upper and lower
bounds of the box indicate the 75 and 25 percentiles of the data, respectively,
and the whiskers indicate the 95th (upper) and 5th (lower) percentiles.
Primary glial culture and preparation for MS. The cortices of P1-day-old rat
pups were dissected and mechanically dissociated after digestion with papain.
Cells were plated on uncoated 6 cm plastic culture dishes (equivalent to 1/5
cortex per dish) and grown at 37 °C in a 5% CO2 atmosphere in minimal
essential medium supplemented with glutamax and 10% FCS, and starting
after 7 d in vitro (DIV), in Neurobasal-A supplemented with B27 and Glutamax
(Life Technologies) pre-conditioned on primary cortical neuronal cultures46.
At DIV 18 the cells were washed and harvested in ice-cold PBS supplemented
with protease inhibitors. Cells were lysed in 200 mM Tris (pH 8.4), 1M NaCl
supplemented with 8 M urea, 4% CHAPS, and Benzonase, cleared by centrifugation and finally alkylated and enzymatically digested essentially as described
previously40 and stored at −20 °C until LC-MS/MS analysis.
Gene ontology, tracking of cell-type-specific marker distributions and genes
related to disease. Gene ontology analyses were performed with Gorilla47 by
comparing specific protein subsets (e.g., the CaMK2a hippocampal proteome)
to our mass spectrometry data from the tissue of origin (e.g., the hippocampus,
Supplementary Table 12) as background, the 30 GO terms most enriched
(P value <1 × 10−3) were ranked by ascending statistical significance P values
(see Figs. 2e and 4c, Supplementary Fig. 8d and Supplementary Tables 2,
5 and 9). The cell-type-specific markers used for evaluation of our neuronal
proteomes (Fig. 2g and Supplementary Fig. 8e) were obtained as follows: a
set of 290 glial and 644 neuronal protein markers was obtained by extracting
proteins showing a twofold higher abundance in astrocytes, oligodendrocytes
and microglia cultures compared with neuronal cultures in48. Unique hippocampal-cell-type markers were taken from reference49. Cerebellar layer-specific
markers (i.e., markers enriched in or excluded from the Purkinje neuron layer)
were extracted by selecting markers with an enrichment score ≥2 (enriched)
or ≤2 (de-enriched) in ref. 50 (see full lists in Supplementary Table 3).
doi:10.1038/nbt.4016
The statistical significance of marker enrichment was assessed based on their
relative hypergeometric probability distribution (Supplementary Table 3).
The proteins related to diseases that were regulated by EE were collected from
VarElect; only terms with scores > 50 were selected. In the case of bipolar disorders, genes with scores > 90 were selected due to the large number of genes
related to this disease. Some additional terms were manually added based on
the literature (Supplementary Fig. 9b).
35. de Felipe, P. et al. E unum pluribus: multiple proteins from a self-processing
polyprotein. Trends Biotechnol. 24, 68–75 (2006).
36. Stoppini, L., Buchs, P.A. & Muller, D. A simple method for organotypic cultures of
nervous tissue. J. Neurosci. Methods 37, 173–182 (1991).
37. Branda, C.S. & Dymecki, S.M. Talking about a revolution: The impact of site-specific
recombinases on genetic analyses in mice. Dev. Cell 6, 7–28 (2004).
38. Bachmanov, A.A., Tordoff, M.G. & Beauchamp, G.K. Sweetener preference of
C57BL/6ByJ and 129P3/J mice. Chem. Senses 26, 905–913 (2001).
39. Dieterich, D.C. et al. Labeling, detection and identification of newly synthesized
proteomes with bioorthogonal non-canonical amino-acid tagging. Nat. Protoc. 2,
532–540 (2007).
40. Szychowski, J. et al. Cleavable biotin probes for labeling of biomolecules via azidealkyne cycloaddition. J. Am. Chem. Soc. 132, 18351–18360 (2010).
41. Wiśniewski, J.R., Zougman, A., Nagaraj, N. & Mann, M. Universal sample preparation
method for proteome analysis. Nat. Methods 6, 359–362 (2009).
42. Schanzenbächer, C.T., Sambandan, S., Langer, J.D. & Schuman, E.M. Nascent
proteome remodeling following homeostatic scaling at hippocampal synapses.
Neuron 92, 358–371 (2016).
43. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized
p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat.
Biotechnol. 26, 1367–1372 (2008).
44. Vizcaíno, J.A. et al. ProteomeXchange provides globally coordinated proteomics data
submission and dissemination. Nat. Biotechnol. 32, 223–226 (2014).
45. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis
of (prote)omics data. Nat. Methods 13, 731–740 (2016).
46. Sutton, M.A. et al. Miniature neurotransmission stabilizes synaptic function via
tonic suppression of local dendritic protein synthesis. Cell 125, 785–799
(2006).
47. Eden, E., Navon, R., Steinfeld, I., Lipson, D. & Yakhini, Z. GOrilla: a tool for
discovery and visualization of enriched GO terms in ranked gene lists. BMC
Bioinformatics 10, 48 (2009).
48. Sharma, K. et al. Cell type- and brain region-resolved mouse brain proteome. Nat.
Neurosci. 18, 1819–1831 (2015).
49. Zeisel, A. et al. Brain structure. Cell types in the mouse cortex and hippocampus
revealed by single-cell RNA-seq. Science 347, 1138–1142 (2015).
50. Kirsch, L., Liscovitch, N. & Chechik, G. Localizing genes to cerebellar layers by
classifying ISH images. PLoS Comput. Biol. 8, e1002790 (2012).
nature biotechnology
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Life Sciences Reporting Summary
Nature Research wishes to improve the reproducibility of the work that we publish. This form is intended for publication with all accepted life
science papers and provides structure for consistency and transparency in reporting. Every life science submission will use this form; some list
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Experimental design
1. Sample size
Describe how sample size was determined.
The experiments described in this exploratory study were done for the first time.
No pre-specified effect size could be determined a priori.
For MS, in general, two replicates are acceptable if the overlap between them is
good (e.g. r2 greater than or equal to 0.80). In this study we used a minimum of
two replicates per proteome and up to 6 replicates. We had excellent
reproducibility between replicates, with r2 greater than 0.90.
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Corresponding author(s):
2. Data exclusions
Describe any data exclusions.
No data were excluded from the study.
3. Replication
Describe whether the experimental findings were
reliably reproduced.
The isolation of specific proteomes was reproducible as is shown in the paper and
described above. Nevertheless due to the several steps of the purification protocol,
the purification of some samples failed and there was no mass spec analysis.
4. Randomization
Describe how samples/organisms/participants were
allocated into experimental groups.
As a general rule, mice (wt or transgenic) were all exposed to the same treatment.
In the case of EE and HC experiments mice were randomly distributed in each of
the cage types.
5. Blinding
Describe whether the investigators were blinded to
group allocation during data collection and/or analysis.
Investigators were not blinded.
Note: all studies involving animals and/or human research participants must disclose whether blinding and randomization were used.
June 2017
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Nature Biotechnology: doi:10.1038/nbt.4016
6. Statistical parameters
n/a Confirmed
The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement (animals, litters, cultures, etc.)
A description of how samples were collected, noting whether measurements were taken from distinct samples or whether the same
sample was measured repeatedly
A statement indicating how many times each experiment was replicated
The statistical test(s) used and whether they are one- or two-sided (note: only common tests should be described solely by name; more
complex techniques should be described in the Methods section)
A description of any assumptions or corrections, such as an adjustment for multiple comparisons
The test results (e.g. P values) given as exact values whenever possible and with confidence intervals noted
A clear description of statistics including central tendency (e.g. median, mean) and variation (e.g. standard deviation, interquartile range)
Clearly defined error bars
See the web collection on statistics for biologists for further resources and guidance.
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For all figures and tables that use statistical methods, confirm that the following items are present in relevant figure legends (or in the
Methods section if additional space is needed).
Software
Policy information about availability of computer code
7. Software
Describe the software used to analyze the data in this
study.
ImageJ64. Prism 6. Origin 2015G. MaxQuant 1.5.3.8. Perseus 1.5.5.3.
For manuscripts utilizing custom algorithms or software that are central to the paper but not yet described in the published literature, software must be made
available to editors and reviewers upon request. We strongly encourage code deposition in a community repository (e.g. GitHub). Nature Methods guidance for
providing algorithms and software for publication provides further information on this topic.
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Materials and reagents
Policy information about availability of materials
8. Materials availability
Indicate whether there are restrictions on availability of
unique materials or if these materials are only available
for distribution by a for-profit company.
No unique materials are used.
9. Antibodies
Describe the antibodies used and how they were validated Mouse anti-biotin (IF and IB, 1:1000, Sigma, cat:033700). Rabbit anti-biotin (IF and
for use in the system under study (i.e. assay and species). IB, 1:1500, Cell Signaling, cat:5567). Rabbit anti-GFP (IF and IB 1:750, Invitrogen,
cat:A11122). Chicken anti-GFP (IF, 1:500; IB: 1:1000; Aves,cat:1020). Gp anti-MAP2
(1:1000, SYSY,cat:188004).
Antibodies used for the PLA experiments: rabbit anti-Lamin 1:1000 (abcam,
cat:ab16048), rabbit anti-Debrin 1:500 (sigma, cat:d3816), rabbit anti-GluA1 1:500
(abcam, cat:ab31232). Mouse anti-far red (1:100, abcam, cat:ab52060 ).
Secondary antibodies
Goat anti-chicken Alexa 647 (IF, 1:750; IB, 1:7500; Invitrogen, a21449). Goat antirabbit Rhodamine RRX (IF, 1:800, Jackson laboratory, cat:711295152). Goat antirabbit FITC (IF, 1:800, Jackson laboratory, cat:111095003). Goat anti-mouse or
anti-rabbit IR680 or IR800 (IB, 1:10.000, Licor,cat:296-32213 and 296-32211).
Antibody specificity was evaluated using the proper negative controls.
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`
a. State the source of each eukaryotic cell line used.
Hek, HeLa and Cos7 were obtained from ATCC.
b. Describe the method of cell line authentication used.
None of the lines have been authenticated.
c. Report whether the cell lines were tested for
mycoplasma contamination.
Lack of cell line contamination with mycoplasma was checked by PCR (eMyco
detection kit, Intron Biotechnology).
d. If any of the cell lines used are listed in the database
of commonly misidentified cell lines maintained by
ICLAC, provide a scientific rationale for their use.
No commonly misidentified cell lines were used.
Animals and human research participants
Policy information about studies involving animals; when reporting animal research, follow the ARRIVE guidelines
11. Description of research animals
Provide details on animals and/or animal-derived
materials used in the study.
All the mice used in this study were C57BL/6 from Jackson Laboratory. Animals
used were 6 weeks old at the beginning of the experiments. Both males and
Females were used.
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10. Eukaryotic cell lines
Policy information about studies involving human research participants
12. Description of human research participants
Describe the covariate-relevant population
characteristics of the human research participants.
Study did not involved humans.
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