Serotonin Transporter Associated Protein Complexes Are Enriched in


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Serotonin transporter associated protein complexes are enriched in synaptic vesicle proteins and proteins involved in energy metabolism and ion homeostasis Jana Haase, Joanna Grudzinska-Goebel, Heidi Kaastrup Müller, Agnieszka Münster-Wandowski, Elysian Chow, Kieran Wynne, Zohreh Farsi, Johannes-Friedrich Zander, and Gudrun Ahnert-Hilger ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.6b00437 • Publication Date (Web): 31 Mar 2017 Downloaded from http://pubs.acs.org on April 1, 2017

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Serotonin transporter associated protein complexes are enriched in synaptic vesicle proteins and proteins involved in energy metabolism and ion homeostasis

Jana Haase1*, Joanna Grudzinska-Goebel1, Heidi Kaastrup Müller1,2, Agnieszka Münster-Wandowski3, Elysian Chow1, Kieran Wynne4, Zohreh Farsi5, Johannes-Friedrich Zander3, and Gudrun Ahnert-Hilger3

1

UCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin,

Ireland 2

Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Risskov, Denmark

3

Institute of Integrative Neuroanatomy, Charité University Medicine Berlin, Germany

4

Proteomic Core Facility, UCD Conway Institute, School of Medicine and Medical Sciences, University

College Dublin, Dublin, Ireland 5

Department of Neurobiology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany

* To whom correspondence should be addressed: Dr. Jana Haase, School of Biomolecular and Biomedical Sciences, UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland; Phone: +353 1 7166754; E-mail: [email protected]

Abbreviated Title: Serotonin transporter interactome

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Abstract The serotonin transporter (SERT) mediates Na+-dependent high-affinity serotonin uptake and plays a key role in regulating extracellular serotonin concentration in the brain and periphery. To gain novel insight into SERT regulation, we conducted a comprehensive proteomics screen to identify components of SERTassociated protein complexes in the brain by employing three independent approaches. In vivo SERT complexes were purified from rat brain using an immobilised high-affinity SERT ligand, amino-methyl citalopram. This approach was combined with GST pulldown and yeast two-hybrid screens using N- and Cterminal cytoplasmic transporter domains as bait. Potential SERT associated proteins detected by at least two of the interaction methods were subjected to gene ontology analysis resulting in the identification of functional protein clusters that are enriched in SERT complexes. Prominent clusters include synaptic vesicle proteins, as well as proteins involved in energy metabolism and ion homeostasis. Using subcellular fractionation and electron microscopy we provide further evidence that SERT is indeed associated with synaptic vesicle fractions, and co-localizes with small vesicular structures in axons and axon terminals. We also show that SERT is found in close proximity to mitochondrial membranes in both, hippocampal and neocortical regions. We propose a model of the SERT interactome, in which SERT is distributed between different subcellular compartments through dynamic interactions with site-specific protein complexes. Finally, our protein interaction data suggest novel hypotheses for the regulation of SERT activity and trafficking, which ultimately impact on serotonergic neurotransmission and serotonin dependent brain functions.

Keywords: Serotonin transporter, protein-protein interactions, proteomics, synaptic vesicle, mitochondria, hippocampus

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Introduction The serotonin transporter (SERT) mediates high-affinity uptake of serotonin (5-hydroxytryptamine, 5HT) in the brain and in the periphery. SERT plays a crucial role in regulating extracellular 5HT levels, and is a key target for the most-widely prescribed antidepressant drugs, namely selective serotonin reuptake inhibitors (SSRIs). SERT belongs to the superfamily of Na+-dependent neurotransmitter transporters, which also includes catecholamine transporters for norepinephrine (NET) and dopamine (DAT), gamma-aminobutyric acid (GABA) transporters (GATs), glycine transporters (GlyT1 and GlyT2) as well as the structurally distinct glutamate transporters, EAAT1-5 1-3. It has been well established that these transporters are critical for terminating synaptic transmission following neurotransmitter release. However, additional functions of these transporters beyond neurotransmitter uptake are beginning to emerge. These include the accumulation of neurotransmitter into neurons and other cells with limited or absent de-novo transmitter synthesis, ion transport which may directly or indirectly affect excitability, receptor-like functions, e.g. acting as sensors of neurotransmitter release, as well as crosstalk with other transporters and receptors (reviewed in 4). These different functions are likely to be regulated by dynamic interaction with other proteins, i.e. interactions between neurotransmitter transporters and distinct subsets of regulatory proteins that influence transport rates, affect substrate and ligand binding properties or induce differential targeting to specific locations 5-7. In recent years, a substantial number of studies have been conducted to identify neurotransmitter transporter interacting proteins that may be contributing to the modulation of transporter function and localization 8-14.

Invariably, the studies mentioned above used a single approach to screen for potential interacting proteins. However, each approach comes with different advantages and disadvantages and the inevitable identification of false-positives causes frustration during validation studies or biases the focus to the most obvious candidates. Combining the results of multiple independent approaches can instil greater confidence in the potential biological relevance if target proteins are identified by more than one method, a strategy successfully applied for the characterization of other neuronal multi-protein complexes 15, 16.

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Here we describe the identification of SERT interacting proteins using three independent proteomic screens as well as gene ontology analysis to gain advanced insight into the composition of putative multi-protein SERT complexes at distinct subcellular locations.

Results and discussion Identification of SERT interacting proteins using a combined approach of three independent proteomics screens We employed three independent approaches to identify SERT interacting proteins, (i) affinity purification (AP) of SERT associated protein complexes from rat brain using an immobilized high-affinity ligand, aminomethyl citalopram (AMC) followed by conventional one-dimensional gel electrophoresis and mass spectrometry (Fig. 1A), (ii) GST-pulldown assays using N- and C-terminal fragments of SERT (Fig. 1B) and rat brain tissue lysates followed by gel electrophoresis and mass spectrometry, and (iii) a series of yeast twohybrid (YTH) screens using N- and C-terminal domains of SERT (Fig. 1B). The affinity purification approach has the potential to isolate and characterize in vivo complexes associated with SERT, and thus, may yield proteins which interact with SERT both, directly and indirectly. We have previously shown that SERT is associated with lipid rafts 17 and we speculated that the enhancement of SERT activity within lipid rafts is at least in part due to the stabilization of critical protein-protein interactions. Thus, we aimed to apply a protein identification method that facilitates isolation of lipid raft associated protein complexes, and we anticipated that such complexes would contain a considerable number of integral membrane proteins. Affinity isolation using immobilized AMC has previously proven successful in achieving 200-300-fold purification of SERT from human blood platelets and rat brain 18, 19. Inspired by these studies, we exploited the enhanced reactivity of AMC compared to its parent compound citalopram to couple the ligand to surface-activated Dynabeads as described in the Method section. In order to stabilize protein interactions of SERT within lipid rafts 17 and retain ligand binding activity 20, rat brain lysate was prepared using the non-ionic detergent Brij-58. Under these relatively low stringency conditions, it is however likely that a considerable number of proteins attach non-specifically to the complex or the beads, for example due to post-solubilization aggregation and/or hydrophobic adsorption. 4 ACS Paragon Plus Environment

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To minimize non-specific binding, rat brain lysates were pre-cleared by incubation with control beads prior to binding to AMC beads.

SERT binds to and can be recovered from AMC beads, but was not detected in samples eluted from control beads, suggesting specific binding to AMC beads. Exact purification factors were not determined, but based on Western blot analysis (see also Fig. 3) we estimate that we recovered approximately 10-20% of total SERT from the lysate fraction, largely in agreement with yields reported previously 18, 19. Considering recent advances in our understanding of the structure of SERT and its ligand binding sites 21, 22, we suspect that the transporter most likely binds the affinity resin via the allosteric S2 site of SERT, and due to steric hindrance and insufficient spacer length is less likely to bind via the deeply buried primary S1 ligand binding site. Nonetheless, SERT and any bound proteins were recovered from the resin in elution buffer containing the highly selective SSRI citalopram, suggesting specific and physiologically relevant enrichment of the transporter. However, given the low yield of SERT recovery and uncertainties regarding the exact binding mode to the affinity resin, we cannot rule out a certain degree of bias in the isolation of a particular class of SERT complexes, for example subpopulations in which SERT adopts a particular conformation. GST pulldown assays allow the identification of strong, predominantly direct in vitro interactions, although the identification of indirect binding partners cannot be excluded. The YTH method is a high-throughput method that allows the genome-wide analysis of binary protein interaction, and is very powerful in detecting weak and transient interactions, a strength that may also cause false-positive identifications. Except for the two shorter YTH baits (NSERT1-87 and CSERT596-630), all other YTH baits as well as fusion protein constructs used for GST pulldown assays contained transmembrane domains (TM), i.e. TM1 or TM12 (Fig. 1B). In particular when testing GST fusion proteins, we noticed that constructs including these transmembrane domains seem to be more stable, i.e. less prone to proteolysis. Although we do not fully understand the reasons for this apparently enhanced stability, we think that perhaps the TM domains facilitate the folding of the cytoplasmic domains, which are thought to contain extensive regions of disordered residues 23. However, while the TM containing YTH and GST fusion proteins are likely to support the identification of SERT-interacting membrane proteins, we also have to consider the possibility that 5 ACS Paragon Plus Environment

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exposed hydrophobic domains may promote the non-specific binding of irrelevant proteins in our interaction screens.

Taken together, each of the interaction methods has distinct advantages but also limitations. However, given that the probability of detecting the same false-positive interactions in different screens is low, confidence in potential interacting protein is substantially increased when a protein is identified in more than one screen. Thus, in an attempt to overcome the limitations commonly associated with each of the respective screening methods we opted for a combined approach in this study. [insert Fig. 1 here]

Composition of SERT associated protein complexes We identified a total of 382 potential SERT interacting proteins by affinity purification, 408 using GST pulldown assays and cDNAs encoding 128 different proteins in the YTH screens. When comparing these protein lists, we were able to identify 98 proteins that were detected by at least two approaches (Fig. 2). In addition, we identified 7 proteins that were detected in only one of the screens, but were identical or closely related to proteins previously characterized as SERT interacting proteins. Thus, we compiled a highconfidence list of 105 putative SERT interacting proteins for further analysis (Table 1). For any previously identified SERT interacting proteins references are also given in Table 1. As outlined above, one of our aims was to identify proteins that interact with SERT within lipid rafts and indeed, approximately one third of the identified proteins are integral membrane proteins, i.e. they contain at least one putative transmembrane helix (Table 1).

For all GST pulldown and YTH interactions, Table 1 also lists the cytoplasmic domain of SERT for which the interaction was observed, i.e. either N- or C-terminus. We noticed that some proteins were found to interact with both termini in one of the screens, and for other proteins the two interaction screens did not correspond. We suspect that a considerable number of these reflect non-specific interactions, which have to be interpreted with caution. However, from recent analysis of the structure and conformational changes 6 ACS Paragon Plus Environment

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associated with the transport cycle, we know that the cytoplasmic domains of SERT come into close contact, in particular in the outward facing conformation of the transporter 23, 24. Thus, it is possible that the binding domain for some proteins spans both termini, and different in vitro methods may preferentially detect interaction with one or the other part of the interaction domain. Such proteins may even be instrumental in stabilizing particular conformational states of SERT, offering intriguing possibilities how these proteins may be able to influence transport kinetics. Therefore, without further validation, we decided not to dismiss these proteins as non-specific interactors.

As already mentioned above, we identified a number of previously characterized SERT interacting proteins in our screens (referenced in Table 1), but failed to isolate some other known SERT interactors. For example, while we did not identify HSP70-1A 25, we did find two proteins, HSP7C and GRP75, belonging to the same protein family, i.e. heat shock protein family A (Hsp70). Proteomics screens in general not only suffer from false-positive, but also false-negative identifications. The limited overlap between interaction screens has frequently been noted, and this may be due to various factors, including sampling and assay sensitivity as well as screening completeness and precision 26.

Figure 3 shows Western blot confirmation of the specific interaction of selected proteins with SERT using AMC affinity purification. [insert Fig. 2 here] [insert Table 1 here] [insert Fig. 3 here]

Only three proteins were identified in all three of the protein interaction screens, suggesting that these are prominent regulators of SERT function. SERT appears to robustly interact with the non-catalytic β1 subunit of Na+/K+-ATPases. The β2 subunit was also identified, albeit only in two screens (AP and YTH). The likely reason for the close link between the transporter and the Na+/K+-ATPase is to ensure that the Na+-gradient is restored following the local increase in intracellular Na+ concentrations as a result of transporter activity. 7 ACS Paragon Plus Environment

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Other transporters have also been shown to interact directly with Na+/K+-ATPase subunits, i.e. glutamate transporters Glt and GLAST 10, 27, 28 as well as the glycine transporter GlyT2 29, suggesting that complex formation between these transporters and Na+/K+-ATPase is an essential pre-requisite for efficient neurotransmitter uptake across the plasma membrane. It should also be noted that recent evidence suggests that Na+/K+-ATPase acts as a “docking station” for protein complexes in the plasma membrane, facilitating additional functional roles through multiple interaction partners, including signaling molecules and other plasma membrane proteins30. Thus, we speculate that SERT may be part of such Na+/K+-ATPase anchored complexes at the presynaptic plasma membrane, and SERT activity may also be subject to regulation by signaling pathways triggered downstream of Na+/K+-ATPase.

Interestingly, another class of plasma membrane P-type ATPases has recently been identified as regulatory proteins for neurotransmitter transporters, namely members of the Ca+-ATPase family, PMCAs, which have been found to associate with GlyT2 in lipid microdomains31. Our screens revealed three isoforms, PMCA2, 3, and 4 (AT2B2, 3, and 4 in Table 1) that are associated with SERT, suggesting common mechanisms for the local regulation of ion homeostasis at pre-synaptic neurotransmitter uptake sites.

We also identified members of the 14-3-3 protein family among prominent SERT-interacting proteins, 14-33 theta (all three screens, see also reference 8), as well as 14-3-3 zeta and 14-3-3 beta (AP and GST pulldown). 14-3-3 proteins were also identified as NET-interacting proteins11. Using a heterologous expression system we were able to show that 14-3-3 overexpression results in a reduction of SERT activity8, however, to-date we still know very little about how these proteins regulate SERT or related transporters in vivo. Since 14-3-3 proteins bind the majority of their partners in a phosphorylation-dependent manner32, 33, we speculate that these proteins are involved in one or more of the protein kinase/phosphatase signaling pathways identified to regulate SERT activity under various conditions (reviewed in 34). It should be noted that our high-confidence set of SERT interacting proteins does not contain any Ser/Thr kinases, which could phosphorylate SERT and generate sites for 14-3-3 binding. Most likely irrelevant to 14-3-3 proteins, we did however identify the tyrosine kinase Fyn as a novel putative SERT regulatory protein kinase (Table 1). 8 ACS Paragon Plus Environment

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Tyrosine phosphorylation has previously been implicated in SERT regulation 35-38. Further studies are required to clarify the role of Fyn kinase in SERT regulation.

Two additional proteins could be considered in the category of prominent SERT interactors, namely two members of the proteolipid protein family, the highly related GPM6a and GPM6b. Although neither of the two proteins were identified in all three screens, both were co-purified with SERT using AMC beads, and GPM6b was also identified in one of our YTH screen (see also 39), while GPM6a was detected by GST pulldown (Table 1). GPM6b is expressed in both, neurons and glial cells, while GPM6a is thought to be mostly neuronal. The functions of GPM6a/b are not well understood. GPM6a is a stress-responsive gene and was found to be down-regulated in chronic stress models of depression 40, 41 and has also been implicated in a depression subtype of schizophrenia 42. In addition, GPM6b was shown to regulate serotonergic functions 43. In a follow-up study, we have gathered further in vitro and in vivo evidence that GPM6a, and distinct splice variants of GPM6b regulate SERT activity (manuscript in preparation).

Functional cluster analysis of SERT associated proteins To gain further functional insight into protein complexes associated with SERT, we performed functional cluster analysis using the DAVID platform applying the search criteria described in the Method section 44. The DAVID algorithm maps gene lists to gene ontology (GO) terms in three categories, i.e. biological process, cellular component and molecular function, and identifies GO terms that are overrepresented in the gene list with respect to the entire genome of the respective organism. Functional cluster annotation combines similar GO terms with overlapping members and thus, enables a focus on major, biologically relevant functions associated with gene lists. [insert Table 2 here]

Table 2 shows identified GO clusters with enrichment scores over 3 and the associated proteins from our list of 105 potential SERT interacting proteins. Not unexpectedly, in the biological process category SERT associated proteins are enriched for protein transport and localization (Cluster A) as well as synaptic 9 ACS Paragon Plus Environment

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transmission (Cluster C). In addition, we identified clusters of proteins associated with energy metabolism, i.e. ATP biosynthesis (Cluster B) and carbohydrate metabolism (Cluster D), the former is paralleled by molecular function clusters I and J, purine nucleotide binding and ATPase activity, respectively. As mentioned above, transport of serotonin and other neurotransmitters is Na+-dependent, and hence relies on the activity of the Na+/K+-ATPase, which in turn requires a constant supply of ATP. Synapses have high demands for metabolic energy, which are met by activity-driven ATP synthesis as a result of both, glycolysis and mitochondrial oxidative phosphorylation 45. Dhar-Chowdhury et al. proposed a key role for glycolysis in fueling transporter and ion channel activity 46, while others found that synaptic ATP is predominantly generated by oxidative phosphorylation 47. Similar to our findings, the glutamate transporters Glt and GLAST were found to be associated with both glycolytic and mitochondrial proteins, and follow-up experiments revealed that astrocytic glutamate transport requires both, glycolysis and oxidative phosphorylation 10, 27. Here we identified several glycolytic enzymes as well as mitochondrial proteins (see also below) among SERT associated proteins, suggesting a close link to ATP generating complexes in synapses.

An additional molecular function cluster indicates enrichment of GTP binding activity (Cluster H) among SERT interacting proteins. This cluster contains Rab proteins involved in protein trafficking in accordance with Cluster A. Other GTP binding proteins include various tubulin subunits as well as septins suggesting an association of SERT with the cytoskeleton, which is perhaps a reflection of the prominent axonal localization of SERT (see also below). Rather unexpectedly, among the GTP binding proteins we also identified three α subunits of heterotrimeric G proteins as well as the Gβ1 and Gβ2 subunits as potential SERT binding proteins, suggesting that SERT might be regulated by G proteins. We have further in vitro and in vivo evidence that Gαq interacts with SERT and inhibits transport activity (manuscript in preparation).

The top ranked cellular component cluster comprises mitochondrial membrane proteins (Cluster E, Table 2). The physical and functional interaction between neurotransmitter transporters and mitochondria has previously been demonstrated for glutamate transporters Glt and GLAST 10, 27, 48, 49. The close association of 10 ACS Paragon Plus Environment

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SERT with mitochondria could be important for ensuring local ATP supply required for the regeneration of the Na+ gradients essential for 5HT uptake, as outlined above. However, perhaps this interaction also serves to closely link SERT to the location where transmitter metabolism takes place, i.e. serotonin and other monoamines transported by SERT are metabolized by monoamine oxidases located in the outer mitochondrial membrane. A link between the glutamate transporter GLAST and mitochondria to support the metabolism of glutamate taken up into astrocytes has previously been proposed 27.

Another cellular component cluster indicates enrichment in vesicle associated proteins (Cluster F), suggesting co-localization and interaction of SERT with vesicular proteins in intracellular organelles. This finding is not unexpected, as SERT is known to be regulated by subcellular distribution, which is dependent on the activation of various protein kinases and phosphatases 34, 50. Interestingly, we found a very pronounced relative enrichment (over 35-fold) for proteins associated specifically with the synaptic vesicle (SV) membrane (GO term: GO:0030672, cluster G in Table 2). In fact, this GO term represents the highest fold enrichment we found in our analysis, strongly suggesting that SERT forms a complex with membrane associated SV proteins. Previous studies have identified two of the proteins in this cluster as SERT regulatory proteins, i.e. syntaxin 1A and VAMP2/synaptobrevin 8, 51-53. In addition, this cluster contains SCAMP1 and 5, which are closely related to the previously characterized SERT interacting protein, SCAMP254. There are two possible arrangements that could account for these interactions, (i) plasma membrane-bound SERT may be physically associated with docked SVs, or (ii) SERT localizes to or traffics with synaptic or synaptic-like vesicles. The former possibility has been proposed for DAT, which was found to directly interact with synaptogyrin 55. Transporter trafficking via synaptic vesicles or synaptic-like vesicles has previously been suggested for the choline transporter (CHT)56, the GABA transporter GAT1 57 as well as the glycine transporter GLYT2 58. To further test the hypothesis that SERT localizes to SVs we performed subcellular fractionation and electron microscopy studies.

SERT co-fractionates with synaptic vesicles

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Efficient biochemical methods for the isolation of SVs are well established 59, 60. As described in the Method section, crude synaptic vesicles, i.e. LP2 fractions can be isolated from brain tissue following homogenization in sucrose solution through a series of differential centrifugation steps. Figure 4A shows Western blot analysis of fractions obtained from rat brain. Subcellular fractionation of mouse brain tissue was also carried out giving comparable results (Supplementary Fig. S1). Resident SV proteins, such as synaptophysin, synaptobrevin (VAMP2) or the vesicular monoamine transporter VMAT2, are enriched in the LP2 fraction relative to P2 and are less abundant in LP1 (Fig. 4A, see also 60). Typical plasma membrane proteins, such as the NMDA receptor subunit NR1 and Glt, are de-enriched in LP2 relative to P2, and more abundant in LP1. However, P2 and LP2 fractions contain similar amounts of SERT (Fig.4A), in some fractionations SERT even appears enriched in LP2 relative to P2 (Fig. 4B). The LP2 fraction contains heterogeneous small vesicular structures. Thus, in order to determine whether SERT may indeed be associated with SV, we analyzed a highly purified SV fraction isolated after size exclusion chromatography as previously described 60. Two main fractions are obtained from this additional purification step, i.e. the so-called Peak 1 fraction, which contains membrane vesicles of various sizes above a diameter of 100nm, and the highly purified SV fraction containing uniformly shaped small vesicles of 40-50nm diameter60. As shown in Figure 4B, SV proteins such as synaptophysin, synatobrevin (VAMP2), synaptogyrin and SCAMP1 are enriched in the SV fraction relative to LP2. In contrast, plasma membrane proteins, such as the NMDA receptor NR1 subunit, are effectively lost during the final purification step. The SERT interacting protein GPM6a appears to be associated with SVs, but is not enriched in the SV fraction, and is found at slightly higher concentration in the Peak 1 fraction. GPM6a has previously been identified in purified SVs by mass spectrometry, but its subcellular distribution had not been analyzed in detail 60. SERT was detected in the highly purified SV fraction, but was not enriched, while the highest concentration of SERT was detected in the Peak 1 fraction, suggesting that the transporter might predominantly associate with larger vesicular structures. It should be noted that the SERT distribution pattern does not match that of the NMDA receptor, nor that of syntaxin 1A, which shows a more or less uniform distribution across all fractions, and also not that of a typical endocytic protein, endophilin, which is consistently de-enriched from P2 via LP2 to SV. Rather, the SERT distribution pattern most closely resembles those of GPM6a and VMAT2, although the 12 ACS Paragon Plus Environment

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relative amounts of SERT in the SV fraction is somewhat lower. The high abundance of VMAT2 in the Peak 1 fraction suggests localization in larger membrane vesicles, possibly dense core vesicles (80-120 nm in diameter), consistent with previous findings 61. [insert Fig. 4 here]

Ultrastructural localization of SERT to axons and presynaptic terminals – association with small vesicles and mitochondria Our biochemical analysis suggests that SERT partially co-fractionates with SVs and may be associated with larger vesicular compartments, and perhaps, similar to VMAT2, with dense core vesicles. In order to confirm the subcellular localization of SERT protein in brain tissue sections of mouse (Fig. 5) and rat (Supplementary Fig. S2), we carried out electron microscopy of freeze substituted brain thin sections, subjected to low temperature embedding and postembedding immunogold labeling. The antibody used for immunogold labeling recognizes SERT with high specificity. When used in Western blotting this antibody detects SERT-specific bands in mouse brain samples, which are absent from samples derived from SERT knockout mice. The antibody is somewhat less sensitive in rat brain samples, which may explain the less intense immunogold labeling compared to sections obtained from mouse brain (Supplementary Fig. S2). No cross-reaction with other, non-specific protein bands was detected by Western blotting (Supplementary Fig. S3). We assume similar specificity of the antibody in tissue sections.

Putative serotonergic axons and their terminals or varicosities identified as immunoreactive for SERT (immunogold labelled) were found in both brain regions explored, i.e. hippocampus and neocortex (Fig. 5). We found labeling of serotonergic projection in the stratum radiatum and moleculare of the CA1 region in dorsal hippocampus in both species. A very small fraction of axon terminals were labeled, as opposed to the majority of unlabeled nerve terminals in the surrounding hippocampal and cortical neuropil. The identified SERT-immunoreactive profiles were small unmyelinated axons and axon terminals or varicosities of different size and morphological features. The SERT-immunoreactive axon terminals formed asymmetric contacts with spines and dendrites (Fig. 5B, C, E). Postsynaptic compartments, dendrites and spines were 13 ACS Paragon Plus Environment

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not labeled. These findings agree with published data showing at the ultrastructural level SERT-containing terminals forming asymmetric synapses onto unlabeled dendritic shafts or spines 62. SERT labeling was previously also detected in serotonergic axon terminals that make symmetric contacts to dendrites as well as axons of target neurons in the limbic brain 63, 64.

Here in this study, we observed SERT labeled serotonergic terminals that were filled with small clear SVs, many of which also contained mitochondria. SERT-bound gold particles were localized mainly to vesicle membranes in presynaptic compartments (Fig. 5B, C, E, F) and were also localized, albeit less frequently, to the terminal plasma membrane (Fig. 5C, E, F). The association of SERT with SV away from the presynaptic plasma membrane argues against a prominent co-localization of plasma membrane bound SERT with docked SV in the active zone at transmitter release sites.

Based on our biochemical data we speculated that SERT might also associate with dense core vesicles (DCV, see section above), as previously proposed63, 65. DCV are found in various populations of hippocampal neuronal endings, such as glutamatergic, GABA-ergic or peptidergic terminals 66-69. However, in our study, SERT-terminal profiles only occasionally show large DCV, similar to what has previously been observed70. The low number of DCV hampered the detection of SERT on these structures, and thus, we did not find clear evidence for a prominent localization of SERT to DCVs. Taken together, the findings presented in this study, suggest that a significant portion of SERT is associated with membranes of small clear SV. Given our biochemical data and the finding that SERT co-fractionates extensively with larger vesicular membranes in the Peak 1 fraction, it may also be possible that SERT co-localizes with SV proteins on large endocytic vesicles generated by ultrafast endocytosis after SV fusion, which have been characterized recently 71. However, the probability of capturing images of such endocytotic intermediates using the method employed here is very low. Thus, some uncertainty remains regarding the type of vesicles SERT is localized to.

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In unmyelinated axons the SERT labeling was distributed mostly throughout the cytoplasm (Fig. 5A, D, F). In axon projections and terminals gold labeling patterns indicate association with mitochondrial membranes, while mitochondria themselves were not labeled (Fig. 5A, C, D, F). Interestingly, when reviewing electron microscopic images shown in two previous publications 63, 65, we noticed that SERT is seen in close proximity to mitochondria also in the rat prelimbic prefronal cortex and the nucleus accumbens, although the authors of these publications did not comment on this. These findings are consistent with our protein interaction data, suggesting that SERT may indeed be physically linked to mitochondria in serotonergic axons and terminals. [insert Fig. 5 here]

Model of the SERT interactome Figure 6 summarize the results of this study and visualizes the proposed constitution of SERT complexes in the brain. The model indicates that SERT is associated with several functional complexes through a limited number of direct protein interactions. For example, SERT is associated with a cluster of proteins involved in carbohydrate metabolism (Fig. 6, light blue nodes), comprising mostly glycolytic enzymes. One of these proteins, PGM1 was identified in one of the YTH screens to interact directly with SERT, while several other proteins were identified by GST pulldown (as well as AP). Thus, based on our results it appears that one or more proteins bind directly to SERT and anchor the glycolytic enzyme complex to sites where the transporter is located. Similarly, the association of SERT with mitochondria is likely to be facilitated by direct or indirect interaction with a small number of proteins. It is unlikely that SERT itself is a mitochondrial protein, and thus, the physical link is probably mediated by proteins located in the outer mitochondrial membrane, such as TOM70 and VDAC2. VDAC2 spans the outer mitochondrial membrane and forms a complex with numerous proteins, including several proteins of the electron transport chain located in the inner mitochondrial membrane, which could explain the identification of these proteins in this study (Fig. 6, purple nodes). Our electron microscopy analysis supports the idea that a subpopulation of plasma membrane or synaptic vesicle associated SERT co-localizes with mitochondria. A similar association between mitochondria and neurotransmitter transporters has been proposed for Glt and GLAST 10, 27. The 15 ACS Paragon Plus Environment

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interaction of SERT with vesicle proteins (Fig. 6, yellow nodes) is supported by co-fractionation and colocalization data presented in this study as well as previously published work (see previous paragraph).

We predict that the association of SERT with functionally distinct protein complexes is temporally and spatially restricted, and perhaps in some cases mutually exclusive. For example, in axon terminals a portion of transporter molecules are localized to small vesicle membranes and interact with SV proteins, while an apparently smaller number of transporters are embedded in the presynaptic plasma membrane, where they potentially interacts with and are regulated by Na+/K+-ATPase and are perhaps linked to glycolytic enzyme clusters and/or mitochondria. Axonal location probably involves interaction with cytoskeletal proteins, while other proteins may be regulating the association of SERT with lipid microdomains. So, dependent on regulatory inputs SERT is distributed between different cellular compartments through dynamic interactions with site-specific protein complexes. Ultimately, these protein interactions modulate transporter activity and availability at or near transmitter release sites, and therefore govern SERT mediated control of extracellular serotonin concentrations and thus, critically impact on the regulation of serotonergic transmission. [insert Fig. 6 here]

Methods Affinity purification. A schematic presentation of the workflow for affinity purification of SERT complexes followed by mass spectrometry analysis is shown in Figure 1A. In adaptation of a previous published method18, amino-methyl citalopram (AMC, provided by Ove Wiborg, Aarhus) was covalently coupled to M280 Tosyl-activated DynabeadsTM in 0.5 M NaHCO3, pH 10.7. Following completion of the reaction, beads were washed extensively to remove unbound ligand, i.e. three times in 2% SDS and 5-10 times in phosphate-buffered saline (PBS). Beads were resuspended in PBS and stored at 4°C for up to four weeks until use. Control beads were treated exactly the same way except for omitting AMC during the reaction step. Total brain tissue (minus cerebellum) from male Wistar rats was homogenized in ice-cold 1xTNE buffer (50 mM Tris HCl pH 7.4, 150 mM NaCl, 5 mM EDTA) using a Dounce homogenizer. The homogenate 16 ACS Paragon Plus Environment

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was centrifuged at 2,000 g for 10 min at 4 °C. The supernatant was transferred to a new tube and centrifuged at 17,000 g at 4 °C for 20 min. The resulting pellet was resuspended in 1% Brij-58, 1x TNE, pushed five times through a 27G syringe to aid lysis and incubated for 1h at 4°C, then briefly centrifuged at 2,000g to remove large debris. Lysates were pre-cleared by incubation with control beads to minimize nonspecific binding. Aliquots of the supernatant (270µl) were then combined with 30µl of AMC or control beads, incubated at 4°C overnight with constant mixing. Beads were collected using a magnetic minifuge holder, the supernatants were discarded, beads were washed three times with 1ml 1% Brij-58, 1x TNE, and bound protein complexes were then eluted with 50 µl TNE containing 1 mM citalopram and 1% digitonin. For mass spectrometry analysis 20-30 aliquots of eluate were combined, samples were concentrated by methanol/chloroform precipitation, and the pellet was resuspended in 50 µl 1x SDS sample buffer. Proteins in control and AMC samples were separated by gel electrophoresis using 4-20% SDS polyacrylamide gradient gels (Pierce). Entire individual lanes were cut into 24 slices. Gel slices were transferred to minifuge tubes, washed and subjected to in-gel digest using trypsin (sequence grade modified, Promega) overnight at 37°C under constant shaking. Peptides were extracted in acetonitrile and dried by vacuum centrifugation. Large scale affinity purification with subsequent mass spectrometry analysis was carried out twice and results were combined for gene ontology analysis. For Western blot analysis small scale purifications were carried out as described above, but samples were directly eluted in SDS sample buffer (equal to lysate volume) prior to gel electrophoresis.

GST pulldown. Glutathione S-transferase (GST) pull-down assays were carried out as described 54. Briefly, PCR fragments corresponding to N- or C-terminal domains of rat SERT (for schematic presentation of constructs see Figure 1B) were fused to GST by subcloning into the pGEX-KG bacterial expression vector (Amersham Biosciences). The GST fusion proteins were expressed in Escherichia coli and purified by affinity chromatography using glutathione-agarose (Sigma). 20 µg of GST (control) or GST fusion protein, immobilized to glutathione-agarose, were incubated with 500 μg of protein lysate from total male rat brain (prepared in PBS containing 5 mM CHAPS and protease inhibitors) for 3 h at 4°C rotating. Unbound proteins were removed by centrifugation, the agarose beads were washed three times in lysis buffer and bound 17 ACS Paragon Plus Environment

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proteins were then eluted in SDS-sample buffer. For mass spectrometry, gel electrophoresis, tryptic digest and peptide extraction were carried out as described above for affinity purification.

Mass spectrometry. Peptides were identified by liquid chromatography tandem mass spectrometry (LCMSMS) using either a Thermo Finngan LTQion trap mass spectrometer or a Thermo Scientific LTQ Orbitrap XL mass spectrometer. For samples run on the Thermo Finigan LTQ Ion Trap the mass spectrometer was connected to a Dionex Ultimate chromatography system. Tryptic peptides were resuspended in 0.1% formic acid. Each sample was loaded onto a Biobasic C18 PicofritTM column (100mm length, 75mm ID) and was separated by an increasing acetonitrile gradient, using a 60 or 72 min reverse phase gradient at a flow rate of 300nL min-1. All data were acquired with the mass spectrometer operating in automatic data dependent switching mode (Nth Order Triple Play). A parent ion scan (400-2000m/z) or (450-1600m/z) was performed to select the top 10 or 5 most intense ions prior to MS/MS analysis using the ion trap. For samples run on the Thermo Scientific LTQ Orbitrap XL the mass spectrometer was connected to an Dionex Ultimate 3000 (RSLCnano) chromatography system or an Eksigent Nano LC 1D Plus chromatography system. Tryptic peptides were resuspended in 0.1% formic acid. Each sample was loaded onto a Biobasic C18 PicofritTM column (100 mm length, 75 mm ID) and was separated by an increasing acetonitrile gradient, using a 60 min reverse phase gradient at a flow rate of 300-400 nL min-1. A high resolution MS scan (3002000 m/z) was performed using the Orbitrap to select the top 5 or 7 most intense ions prior to MS/MS analysis using the ion trap.

Yeast two-hybrid analysis. A total of five yeast two-hybrid screens were conducted as described 8, 54, SERT constructs used are illustrated in Fig. 1B. The first screen was performed with an N-terminal fragment of rat SERT using the interaction trap method 72. The fusion of the DNA binding protein LexA with NSERT115 was used as the bait to screen a rat brain cDNA library fused to the B42 transcription activation domain. Four additional screens were performed using the MATCHMAKER GAL4 system as recommended by the manufacturer (Clontech). cDNA fragments encoding N-terminal and C-terminal domains (Fig. 1B) of human SERT were amplified by PCR and cloned in-frame with the GAL4 DNA-binding domain in pGBKT7-BD and 18 ACS Paragon Plus Environment

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transformed into the yeast strain AH109. AH109 expressing the bait was then mated with the Y187 yeast strain pre-transformed with a human brain cDNA library constructed in the pACT2-AD vector. The identities of positive clones were determined by automated DNA sequencing and compared against the National Center for Biotechnology Information (NCBI) database using the BLAST search program. Encoded proteins were mapped to Uniprot/SwissProt protein IDs to allow comparison with mass spectrometry derived data sets.

Protein identification and selection criteria. Raw mass spectrometry data was de novo sequenced and searched against the rodentia subset of the Uniprot/Swissprot database (March 2013) using the search engine PEAKS Studio 6.0, for peptides cleaved with trypsin. Each peptide used for protein identification met specific Peaks parameters, i.e. only peptide scores that corresponded to a false discovery rate (FDR) of ≤1% and only proteins with at least 1 unique peptide were accepted from the Peaks database search. Proteins identified in control samples were eliminated from sample lists. Thus, only proteins specifically binding to SERT or its fragments were included in further analysis. Protein lists for each analysis type were combined, i.e. total protein lists for each yeast two-hybrid analysis, GST pulldown and affinity purification, respectively, were generated and then compared using Microsoft Excel to identify 98 proteins that were detected with at least two independent methods. Our consolidated list (Table 1) also includes 7 proteins detected in only one screen, for which identical or closely related proteins had been identified and characterized as SERT interacting proteins in previously published studies (referenced in Table 1).

DAVID gene ontology analysis. Based on the criteria described above, a list of 105 proteins (Table 1) was compiled and mapped to corresponding NCBI gene IDs. The gene list was subjected to gene ontology (GO) analysis and functional annotation clustering using the DAVID platform 44. The entire rat genome was selected as the population background. Functional Annotation Clustering was performed using highstringency custom settings as follows: Kappa Similarity: Similarity Term Overlap = 3, Similarity Threshold = 0.9; Classification: Initial Group Membership = 3, Final Group Membership = 3, Multiple Linkage Threshold = 0.5; Enrichment Thresholds: EASE = 0.1. So-called EASE scores (p-values) are a modified Fisher Exact P19 ACS Paragon Plus Environment

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Value, and p-values of lower than 0.05 indicate that any given GO term is significantly enriched relative to the population background, here the entire rat genome. The enrichment score for an annotation cluster is calculated as the geometrical mean (expressed as –log) of all enrichment p-values (EASE scores) associated with this cluster. Following analysis, all clusters with less than three members, with an enrichment score of less than 1.3 (equivalent to geometric mean of p values =0.05) as well as those with non-significant corrected enrichment values (p-values > 0.5, Benjamini correction method) were eliminated. In addition, clusters with overlapping gene lists were combined and a combined enrichment score was calculated manually. In cases were clusters were subclusters of others, only the highest scoring cluster is reported. For presentation (Table 2), gene IDs were converted back to protein IDs.

Western blotting. Standard Western blot analysis was carried out as previously described 54. Primary antibodies used were as follows: CSERT (Santa Cruz Biotechnology, sc-1458, 1:1000), NSERT (Sigma, SAB4200039, 1:5000), ATPase β1 (Millipore, 05-382, 1:1000), M6a (Synaptic Systems, 238003, 1:5000), Gαq (Santa Cruz, sc-393, 1:1000), Gβ (BD Biosciences, 610287, 1:1000), Fyn (Cell Signaling, 4023, 1:1000), Syntaxin-1A (Synaptic Systems, 110001, 1:5000), STXB1/Munc18 (BD Biosciences, 610337, 1:5000), SV2a (Synaptic Systems, 119002, 1:5000), VAMP2/synaptobrevin (Synaptic Systems, 104 211, 1:5000), SCAMP1 (Synaptic Systems, 121 003, 1:5000), synaptophysin (Synaptic Systems, 101 011, 1:5000), synaptogyrin (Synaptic Systems, 103 003, 1:5000), VMAT2 (Santa Cruz Biotechnology, sc-7721, 1:1000), SNAP25 (Synaptic Systems, 111 002, 1:5000), NMDA receptor (GluN1/NR1 subunit, Synaptic Systems, 114011, 1:5000), Glt (Millipore, AB1783, 1:4000), and endophilin (Synaptic Systems, 159002, 1:5000).

Subcellular fractionation and preparation of synaptic vesicles. Synaptic vesicles were prepared according to the method described by Huttner et al. 59. In brief, rat brain was homogenized in homogenization buffer (320 mM Sucrose, 4 mM Hepes, pH 7.4) containing a protease inhibitor cocktail (Sigma). The homogenate (H) was centrifuged for 10 min at 1,300 g at 4°C to obtain pellet fraction 1 (P1) and supernatant (S1). S1 was transferred to a fresh tube and centrifuged for 15min at 14,000 g, 4°C to obtain supernatant fraction S2 and pellet P2. S2 was recovered and further fractionated into S3 and P3 by centrifugation at 350,000 g for 30 20 ACS Paragon Plus Environment

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min, 4°C. The P2 pellet representing the crude synaptosomal fraction was resuspended in homogenization buffer and subsequently subjected to osmotic and mechanic lysis by incubation in 10 volumes hypotonic lysis buffer (10 mM Hepes, pH7.4 containing protease inhibitors) for 20 min with repeated vigorous shaking. The resulting lysate fraction (LSO) was centrifuged at 32,000 g for 20 min, 4°C. The pellet obtained (LP1) contains heavy plasma membrane fragments and large vesicular structures. The supernatant LS1 was subjected to centrifugation at 350,000 g for 30 min, 4°C to separate the crude SV fraction LP2 from the synaptosomal cytosol LS2. The LP2 fraction can be further purified by size exclusion chromatography producing a Peak1 fraction (heterogenous membranes with diameter >100 nm) and the SV fraction, representing highly purified small SVs with a diameter of 40-50 nm 60. Equal amount of protein for each fraction was loaded onto standard SDS-polyacrylamide gels and Western blot analysis was carried out for SERT, SV markers, and plasma membrane protein markers.

Electron microscopy. Tissue preparation: The animals were anesthetized with a mixture of ketamine 50 mg/kg (Actavis) and xylazine (Rompun) 20 mg/ml (Bayer Health Care, Berlin, Germany) and perfused transcardially with fixative containing 4% paraformaldehyde (PFA, Electron Microscopy Sciences, Hatfield, PA) with 0.2% picric acid (Fluka Chemie, Buchs, Switzerland) and 0.05% glutaraldehyde (GA, Electron Microscopy Sciences) in a phosphate buffered solution (PB, 0.1M, pH 7.2). The brains were removed and dissected into blocks containing the hippocampus and cortex using a coronal rodent brain matrix (ASI Instruments, Warren, USA) and were processed for electron microscopy. Freeze substitution embedding: Hippocampal and cortical coronal slices were cut from previously perfused brains and washed repeatedly in 0.1 M PB, pH 7.4. The slices were cryoprotected with increasing concentrations of buffered sucrose. The tissue was subsequently shock frozen in liquid nitrogen. The samples were then transferred into cold methanol (-90°C) in a freeze-substitution chamber (Leica EM AFS). The methanol was exchanged three times before the specimens were immersed overnight in anhydrous methanol at 90°C, containing 2% (w/v) uranyl acetate (Merck, Darmstadt, Germany). After rinsing several times with methanol, the temperature was gradually raised to -50°C and left overnight. The tissue was then infiltrated with mixtures of Lowicryl HM20 resin (Polysciences, Hirschberg, Germany) and methanol and 21 ACS Paragon Plus Environment

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finally left in pure resin overnight at -50°C. The samples were transferred to flat embedding molds containing freshly prepared resin at -50°C. UV polymerization was started at -50°C (overnight) and then continued for several days at temperatures gradually increasing from -50°C to 20°C. Ultrathin sections (70 nm) were cut on an ultra-microtome (Reichert Ultracut S) and mounted on 200-mesh formvar-coated nickel grids (Plano, Wetzlar, Germany). Postembedding immunogold labeling: All postembedding steps except for the incubation with primary antibodies were performed at room temperature. For single immunolabeling with SERT antibody (Synaptic Systems, Göttingen, Germany), sections were first incubated twice for 5 min in 0.1 M PBXT (PBS, 0.001% Triton X-100, 0.001% Tween 20, pH=7.4), followed by 2 h incubation in PBXT supplemented with 2% BSA (bovine serum albumin, Sigma-Aldrich, Darmstadt, Germany) and 5% NGS (normal goat serum, PAN Biotech) at room temperature. The sections were then incubated with primary antibodies (rabbit anti-SERT) diluted in the same buffer overnight at 4°C in a humid chamber. After rinsing several times with PBXT, the primary antibody was visualized by following incubation with 10 nm gold-conjugated secondary antibody (goat anti-rabbit; British BioCell International, Cardiff, UK) in PBXT supplemented with acetylated BSA (Aurion, Wageningen, The Netherlands), for 60 min in a humid chamber. Grids were rinsed several times in PBXT, PBS, and finally in water. Ultrathin sections were then stained with aqueous uranyl acetate (Merck, Darmstadt, Germany) and lead citrate. Sections were examined using a Zeiss Transmission electron microscope (TEM-912) equipped with a digital camera (Proscan 2K Slow-Scan CCD-Camera, Zeiss, Oberkochen, Germany).

Supporting Information The supporting information contains additional figures and a table accessory to the data presented. Table S1: Extended data table listing detailed mass spectrometry results of affinity purification and GST pulldown screens Fig. S1: Subcellular fractionation using mouse brain tissue Fig. S2: Ultrastructural localization of SERT in rat hippocampus Fig. S3: Western blot verification of SERT antibody specificity 22 ACS Paragon Plus Environment

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Abbreviations SERT, serotonin transporter, AP, affinity purification, GST, glutathione-S-transferase, YTH, yeast two-hybrid, AMC, amino-methyl citalopram, SV, synaptic vesicle, DCV, dense core vesicle

Author Information Current address: Correspondence to Dr. Jana Haase, School of Biomolecular and Biomedical Sciences, UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland; Phone: +353 1 7166754; E-mail: [email protected] Author contribution: JH conceived the project, JH, JGG and HKM designed the study, JH, JGG, HKM, and EC carried out the experiments and analyzed the data, AMW carried out electron microscopy analysis, KW carried out the mass spectrometry analysis and provided advice on MS data analysis, ZF provided highpurity synaptic vesicle samples, JFZ and GAH provided advice and assistance for subcellular fractionation and synaptic vesicle analysis. JH carried out bioinformatics analysis and wrote the manuscript with input from HKM, AMW and GAH. Funding sources: This study was supported by the following grants to JH: Science Foundation Ireland (05/RFP/BIM0033), and Health Research Board Ireland (RP/2005/172, RP/2007/214, HRA/2009/303) and to GAH: Deutsche Forschungsgemeinschaft (GAH 67-7/1,2). Conflict of interest: The authors declare no competing financial interest.

Acknowledgement We thank Ove Wiborg (Aarhus University) for the generous gift of amino-methyl citalopram, Patricia Maguire and Martina Foy (University College Dublin) for advice on mass spectrometry analysis in the early stages of this study as well as Dominika Czernik (Max-Planck-Institute for Biophysical Chemistry, Göttingen) for preparing synaptic vesicle fractions. We are very grateful for expert technical assistance by Marion Möbes and Antje Dräger (Institute for Integrative Neuroanatomy Berlin).

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Table 1: Identified serotonin transporter interacting proteins* Prot ID AT1B1 1433T PPIA GPM6B CNTN2 AT1B2 FYN CNRP1 PGM1 STXB1 TBB2A ACTB EAA2 GBB1 TBB3 TBA4A GRP75 SYT1 DPYL2 TBB6 AT2B4 GBB2 AT2B3 DDAH2 VAMP2 1433Z S6A11 STX1B GNAI2 SNP25 NIPS1 GPM6A SEPT7 SHPS1 VPP1 ODPA ADT1 NIPS2 SV2A CMC1 ATPO GNAQ STX1A GNAI1 AT2B2 COX41 CH60 RTN1 NOMO1 COF1 ATP5H TOM70 CAMKV SNAB VISL1 S12A5

Protein name

AP Score • Sodium/potassium-transporting ATPase subunit beta-1 109.84 14-3-3 protein theta 101.02 Peptidyl-prolyl cis-trans isomerase A 81.54 Neuronal membrane glycoprotein M6-b 132.5 • Contactin-2 110.98 77 • Sodium/potassium-transporting ATPase subunit beta-2 Tyrosine-protein kinase Fyn 72.66 CB1 cannabinoid receptor-interacting protein 1 66.2 Phosphoglucomutase-1 25.84 272.48 • Syntaxin-binding protein 1 Tubulin beta-2A 259.3 Actin, cytoplasmic 1 247.02 245.64 • Excitatory amino acid transporter 2 Guanine nucleotide-binding protein subunit beta-1 242.3 Tubulin beta-3 chain 237.8 Tubulin alpha-4A chain 223.12 Stress-70 protein_ mitochondrial 223.01 219.38 • Synaptotagmin-1 Dihydropyrimidinase-related protein 2 212.69 Tubulin beta-6 chain 209.25 203.92 • Plasma membrane calcium-transporting ATPase 4 Guanine nucleotide-binding protein subunit beta-2 202.62 197.53 • Plasma membrane calcium-transporting ATPase 3 Dimethylarginine dimethylaminohydrolase 2 189.03 188.89 • Vesicle-associated membrane protein 2 14-3-3 protein zeta/delta 184.03 170.08 • Sodium- and chloride-dependent GABA transporter 3 169.07 • Syntaxin-1B Guanine nucleotide-binding protein G(i) subunit alpha-2 167.32 161.02 • Synaptosomal-associated protein 25 Protein NipSnap homolog 1 159.45 155.63 • Neuronal membrane glycoprotein M6-a Septin-7 154.96 • Tyr-protein phosphatase non-receptor type substrate 1 150.4 148.04 • V-type proton ATPase 116 kDa subunit a isoform 1 Pyruvate dehydrogenase E1 component subunit alpha 147.35 146.73 • ADP/ATP translocase 1 Protein NipSnap homolog 2 145.91 Synaptic vesicle glycoprotein 2A 142.69 142.59 • Calcium-binding mitochondrial carrier protein Aralar1 136.85 • ATP synthase subunit O_ mitochondrial Guanine nucleotide-binding protein G(q) subunit alpha 135.11 134.72 • Syntaxin-1A Guanine nucleotide-binding protein G(i) subunit alpha-1 132.82 132.73 • Plasma membrane calcium-transporting ATPase 2 Cytochrome c oxidase subunit 4 isoform 1 129.42 60 kDa heat shock protein_ mitochondrial 119.89 118.98 • Reticulon-1 117.89 • Nodal modulator 1 Cofilin-1 116.87 ATP synthase subunit d_ mitochondrial 116.83 114.6 • Mitochondrial import receptor subunit TOM70 CaM kinase-like vesicle-associated protein 113.92 Beta-soluble NSF attachment protein 109.8 Visinin-like protein 1 107.38 107.15 • Solute carrier family 12 member 5

UP 4 1 2 7 1 2 2 1 1 30 4 1 18 1 3 3 1 10 16 1 3 4 3 8 3 7 2 8 3 9 10 8 7 10 11 5 3 5 4 3 2 5 6 1 1 5 6 1 4 3 2 1 4 4 4 3

GST Score UP N/C 68.32 1 N 106.02 2 N 157.55 6 N

104.11 221.69 219.09 31.96 124.74 217.74 155.97 217.31 150.37 210.43 159.48 145.16 112.01 36.8 32.64 108.98 115.25 48.66 28.47 98.92 77.36 125.96 60.67 43.88 53.73 33.45 68.51 154.09 92.24 46.81 45.37 136.39 55.51 46.08 72.78 165.87 135.22 140.65 35.43 46.04 99.44 92.87 103.54 126.27 142.93 36.23 48.84

7 3 6 3 2 2 2 2 8 20 1 1 2 1 2 2 5 4 1 2 2 5 1 1 1 3 1 12 2 3 1 3 2 1 1 6 3 6 2 4 3 2 1 7 4 1 1

C N N C N+C N N C C C N C N N C N N N+C N C N N N C N C N C N N+C N N C N N C N N+C C C N N N C N N N

YTH N/C N N C N N N N N N

Ref

a b

c

d

a,e

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Table 1 continued… Prot ID

Protein name

AP Score 106.24 103.69 96.96 93.33 89.4 84.85 83.88 81.45 81.31 79.04 79.04 76.68 76.33 75.16 74.47 72.09 67.17 65.66 63.21 60.69 56.81 56.29 54.12 52.63 49.8 49.67 49.61 47.9 45.19 44.75 42.94 41.4 38.98 38.63

UP 1 3 3 1 1 3 4 1 1 1 2 2 2 2 1 1 1 2 2 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1

GST YTH Score UP N/C N/C 155.38 2 N 208.91 1 C 128.02 4 N+C 48.44 1 N 164.28 3 N 101.46 1 N 28.07 1 N 88.9 1 N 67.96 3 C 109.7 1 N 133.11 6 N 53.78 1 N 101.77 5 C 82.55 4 N+C 28.33 1 N 66.16 1 N 49.36 1 N 88.96 2 N 52.93 3 C 47.16 1 N 131.54 2 N 164.83 5 N 53.54 8 C 154.88 8 C 41.06 1 N 77.04 2 N 119.07 6 C 86.09 1 N 222.31 6 N 95.78 1 C 53.7 2 C 40.21 9 C 82.65 2 C 30.99 2 C 209.62 3 N C 117.38 4 N C 116.16 4 N C 88.83 9 C C 66.71 1 C N+C 65.29 2 N C 64.44 2 C C 28.15 1 N C

Ref

G3P Glyceraldehyde-3-phosphate dehydrogenase ODPB Pyruvate dehydrogenase E1 component subunit beta RAB2A Ras-related protein Rab-2A PYGM Glycogen phosphorylase_ muscle form BDH D-beta-hydroxybutyrate dehydrogenase RAB1B Ras-related protein Rab-1B RL12 60S ribosomal protein L12 RTN3 • Reticulon-3 SEP11 Septin-11 1433B 14-3-3 protein beta/alpha PHB Prohibitin KPYM Pyruvate kinase isozymes M1/M2 SYNPO Synaptopodin CAZA2 F-actin-capping protein subunit alpha-2 HPCA Neuron-specific calcium-binding protein hippocalcin PRDX1 Peroxiredoxin-1 HCD2 3-hydroxyacyl-CoA dehydrogenase type-2 VAPA • VAMP-associated protein A MPP2 MAGUK p55 subfamily member 2 H2A2B Histone H2A type 2-B SNAA Alpha-soluble NSF attachment protein SDHB Succinate dehydrogenase iron-sulfur subunit PP14C Protein phosphatase 1 regulatory subunit 14C SYN2 Synapsin-2 NDUB5 NADH dehydrogenase 1 beta subcomplex subunit 5 SNG1 • Synaptogyrin-1 ODO1 2-oxoglutarate dehydrogenase RAP1B Ras-related protein Rap-1b TPIS Triosephosphate isomerase OS MPCP • Phosphate carrier protein SIR2 NAD-dependent protein deacetylase sirtuin-2 EVX2 Homeobox even-skipped homolog protein 2 SYNJ1 Synaptojanin-1 d RP3A Rabphilin-3A HSP7C Heat shock cognate 71 kDa protein NDUA4 NADH dehydrogenase 1 alpha subcomplex subunit 4 VDAC2 • Voltage-dependent anion-selective channel protein 2 DYHC1 Cytoplasmic dynein 1 heavy chain 1 MAP1A Microtubule-associated protein 1A COX2 • Cytochrome c oxidase subunit 2 MCCB Methylcrotonoyl-CoA carboxylase beta chain PDIA3 Protein disulfide-isomerase A3 NSF Vesicle-fusing ATPase 158.37 1 d MARCS Myristoylated alanine-rich C-kinase substrate 89.94 2 f SCAM5 • Secretory carrier-associated membrane protein 5 64.77 2 g, k SCAM1 • Secretory carrier-associated membrane protein 1 37.3 1 g, k SC24A Protein transport protein Sec24A 31.88 1 h NOS2 Nitric oxide synthase, inducible (iNOS) 23.72 1 i PP2BA Serine/threonine-protein phosphatase 2B alpha 106.94 4 N+C j * Protein interaction screens were carried out as described in the Method section. Abbreviations: Prot ID, UniProt Knowledgebase (UniProtKB) protein identifier; AP, affinity purification; GST, GST pulldown screen; YTH, yeast twohybrid screen; Score, protein identification confidence score, weighted sum of -10lgP scores of all supporting peptides; UP, unique peptides; N/C, N- or C-terminal domain of SERT; bullet points • identify integral membrane proteins; boldface indicates that these proteins were identified in both AP runs, score listed for AP run with highest number of unique peptides. References (Ref): a: 8, b: 39, c: 53, d: 12, e: 51, f: 73, g: 54, h 74, i: 75, j: 76, k: 14

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Table 2: Protein function analysis* Annotation Cluster

Score

Prot No.

Protein IDs

GO Terms

a

pValue

Fold Enrich

Biological Process A

Protein transport 7.71 and localisation

20

1433B, 1433T, 1433Z, COF1, GRP75, SNAB, NSF, PP2BA, RAB1B, RAB2A, RP3A, SCAM1, SCAM5, SNAA, SNG1, STX1A, STX1B, STXB1, TOM70, VAMP2

GO:0015031 GO:0045184 GO:0008104

7.13E-09 8.27E-09 1.29E-07

5.06 5.02 4.22

B

ATP/nucleotide biosynthesis

5.19

9

AT1B1, AT1B2, AT2B2, AT2B3, AT2B4, ATP5H, ATPO, KPYM, VPP1

GO:0006754 GO:0009206 GO:0009145

3.46E-07 8.65E-07 9.29E-07

13.17 11.69 11.58

C

synaptic transmission

4.89

11

ADT1, NSF, PP2BA, S12A5, SNP25, STX1A, GO:0007268 STX1B, SYN2, SYNJ1, SYT1, VAMP2 GO:0007267 GO:0019226

3.29E-06 2.08E-05 3.10E-05

6.98 5.05 5.40

3.95

8

G3P, KPYM, ODO1, ODPA, ODPB, PGM1, PYGM, TPIS

GO:0044275 GO:0006096 GO:0006007

1.24E-05 1.67E-05 5.36E-05

13.36 18.32 14.46

D carbohydrate metabolism Cellular Component E

Mitochondrial membrane

6.60

17

ADT1, ATP5H, ATPO, NDUA4, BDH, CH60, GO:0031966 COX41, NDUB5, MPCP, HCD2, ODO1, PHB, GO:0005743 NIPS1, COX2, SDHB, TOM70, VDAC2 GO:0019866

6.81E-08 1.24E-07 2.65E-07

5.38 6.08 5.71

F

vesicle proteins

6.33

21

1433B, 1433Z, CAMKV, CH60, GNAI1, HSP7C, PDIA3, PRDX1, RAB2A, RP3A, SCAM1, SCAM5, SNG1, STX1A, STXB1, SV2A, SYN2, SYT1, VAMP2, VAPA, VPP1

GO:0031982 GO:0016023 GO:0031410

3.12E-07 3.75E-07 5.82E-07

3.82 4.19 3.85

G synaptic vesicle membrane

5.52

8

RP3A, SCAM1, SNG1, STX1A, SV2A, SYN2, GO:0030672 SYT1, VAMP2 GO:0030665 GO:0008021

1.63E-09 1.15E-07 3.58E-07

35.27 19.94 13.06

4.75

12

GNAI1, GNAI2, GNAQ, RAB1B, RAB2A, RAP1B, SEP11, SEPT7, TBA4A, TBB2A, TBB3, TBB6

GO:0005525 GO:0032561 GO:0019001

1.36E-05 2.05E-05 2.05E-05

5.29 5.06 5.06

I

purine nucleotide 4.70 binding

28

ACTB, AT2B2, AT2B3, AT2B4, CAMKV, GO:0017076 CH60, DYHC1, FYN, GNAI1, GNAI2, GNAQ, GO:0032555 GRP75, HSP7C, KPYM, MCCB, NOS2, NSF, GO:0032553 PYGM, RAB2A, RAB1B, RAP1B, SEP11, SEPT7, SYN2, TBA4A, TBB2A, TBB3, TBB6

1.71E-05 2.17E-05 2.20E-05

2.36 2.38 2.38

J

ATPase activity

6

AT1B1, AT1B2, AT2B2, AT2B3, AT2B4, ATPO

1.34E-04 6.55E-04 6.88E-04

11.96 8.51 12.28

Molecular Function H GTP binding

3.20

GO:0042625 GO:0042626 GO:0015662

* Gene ontology analysis using the DAVID platform was carried out as described in the Method section. Score, enrichment score for each cluster, i.e. geometrical means of all enrichment p-values (EASE scores, -log scale) for each annotation term associated with the gene members in each cluster; Prot No., number of proteins from gene list a associated with each cluster; Prot ID, UniProt Knowledgebase (UniProtKB) protein identifier; GO, gene ontology, for each cluster only top three GO terms are listed; p-Value or EASE Score, a modified Fisher Exact p-Value; Fold Enrich, fold enrichment of proteins in each annotation cluster relative to population background (entire rat genome).

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Figure 1: Experimental strategies for identification of SERT interacting proteins. A: Schematic presentation of affinity purification of SERT complexes using amino-methyl citalopram (AMC) covalently coupled to surface-activated Dynabeads. B: Schematic presentation of fragments of cytoplasmic SERT domains used for GST pulldown and yeast two-hybrid screens, respectively. TM, transmembrane domain; numbers refer to amino acid positions of SERT

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Figure 2: Identification of high-confidence SERT interacting proteins. The proportional Venn diagram illustrates protein identifications using three independent protein interaction screens, indicating the total number of proteins in each screen as well the number protein in overlapping sections.

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Figure 3: Western blot confirmation of co-purified SERT interacting proteins. Affinity purification of SERT was carried out using control or AMC-coupled Dynabeads as described in the Method section. Equal volumes of control and AMC elution samples approximately equivalent to 3 volumes of respective lysate samples were analysed by Western blotting using the indicated antibodies. Abbreviations used are as follows: SERT, serotonin transporter; ATPase β1, β1 subunit of Na+/K+-ATPase; M6a, glycoprotein M6a; Gαq, α subunit q of heterotrimeric G proteins; Gβ, β subunit of heterotrimeric G proteins; Fyn, tyrosineprotein kinase Fyn; STXB1/Munc18, syntaxin-binding protein 1; SV2a, synaptic vesicle glycoprotein 2A; VAMP2/synbrev, vesicle-associated membrane protein 2 (synaptobrevin); SCAMP1, secretory carrierassociated membrane protein 1. Positions of molecular weight markers are indicated on the left. Blots shown are representatives of 2-3 independent experiments.

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` Figure 4: Detection of SERT in synaptic vesicle fractions. A: Subcellular fractionation using rat brain tissue with LP2 (crude synaptic vesicle fraction) as endpoint was carried out as described in the Method section. For each fraction 10µg of protein was loaded onto SDS-polyacrylamide gels. Western blot analysis was carried out using the antibodies indicated. The fractionation was repeated once with rat brain tissue and twice with mouse brain tissue (see supplementary Fig. S1), each time giving similar results. B: Rat brain tissue was fractionated as described in the Method section including a size exclusion chromatography step generating highly purified synaptic vesicles (SV). Abbreviations for other protein fractions are as follows: H, homogenate; P2, pellet 2 fraction (crude synaptosomes); S2, supernatant 2; P3 pellet 3 fraction; LSO, hypotonic lysate of P2 pellet; LP1, lysate pellet 1 (plasma membrane fragments, large vesicular structures); LP2, lysate pellet 2 (synaptic vesicle enriched fraction). Western blot analysis was carried out as in (A). Protein/antibody abbreviations used are as follows: SERT, serotonin transporter (antibodies against N- or Cterminal domain); synphys, synaptophysin; VAMP2/synbrev, vesicle-associated membrane protein 2 (synaptobrevin), syngyr, synaptogyrin; VMAT2, vesicular monoamine transporter 2; SCAMP1, secretory carrier-associated membrane protein 1, SNAP25, synaptosomal associated protein 25; NMDA (NR1), Nmethyl-D-aspartate receptor, NR1 subunit; Glt, glutamate transporter (excitatory amino acid transporter 2); M6a, glycoprotein M6a (GPM6a). Positions of molecular weight markers are shown on the left. Blots shown are representatives of three independent fractionations analyzed.

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Figure 5. Immuno-electron microscopy of SERT in neocortex area and hippocampus of the mouse A-C: Postembedding immunogold labeling for SERT in neocortex cortex area of the mouse brain, D-F: Postembedding immunogold labeling for SERT in CA1 area of the mouse hippocampus. A: Axonal (a) localization of SERT (10 nm immunogold particles, forked arrowheads) to the axon profile and axonal nonsynaptic varicositiy (v). B: Immunogold labeling (10 nm gold; forked arrowheads) is preferentially localized to the serotonergic axon terminal (at) forming synaptic asymmetrical contact to the spine (s). Note that the putative glutamatergic asymmetric axon terminal (at) is not labeled. C: A serotonergic axon terminal (at) forming asymmetric contact onto the dendritic shaft (d). The postembedding immunogold labeling for SERT (10 nm gold; forked arrowheads) was preferentially found presynaptically on small SV membranes and at lower level in the plasma membrane of the axon terminal. Note that the gold labeling in the axon terminal (at) is also in close apposition to the mitochondrial membrane (m). D: Axonal (a, longitudinal section) localization of SERT (10 nm immunogold particles, forked arrowheads) in the CA1 area of the mouse hippocampus. Immunogold labeling for SERT was also found in the close apposition to the mitochondrial membrane (forked arrowheads). Note that transversally sectioned unmyelinated axon (a) shows circular 36 ACS Paragon Plus Environment

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gold labeling on vesicular structure (arrow). Glutamatergic terminals (at) making asymmetric contacts with spines (s) are not labeled. E: Forked arrowheads indicate strong immunogold labeling for SERT (10 nm gold) found on the vesicular membrane in the serotonergic axon terminal (at) making asymmetric contact to the spine (s). F: Serotonergic axon (a) and axon terminals (at) in the CA1 area of the mouse hippocampus with immunogold labeling for SERT (10 nm gold; forked arrowheads) found on axon profile and in axonal varicosities (v) on small SV membranes and at lower level in the plasma membrane of the axon varicosities (v). Note the circular gold labeling on bigger vesicular structure in the boutons (v) and close to the axonal membrane (a; arrows). The immunogold labeling in the axon (a) is also in close apposition to the mitochondrial membrane (m). Scale bar, A-F: 200 nm. Abbreviations: a, axon; at, axon terminal; d, dendritic shaft; m, mitochondrion; s, spine; v, axonal varicosity/bouton.

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Figure 6: Model of the SERT interactome. A list of known binary protein interactions between the highconfidence SERT binding proteins listed in Table 1 was generated using the String database 77. Only protein interactions supported by experimental evidence and curated databases were included. To this list we added selected direct interactions involving SERT that are supported by this study or by published work (see Table 1 for references), but to facilitate greater clarity some isolated interactions were omitted. The consolidated interaction data was then used to generate a protein network model using Cytoscape 78. Node colors relate to selected GO clusters listed in Table 2 as follows: light blue, carbohydrate metabolism (Cluster D); purple, mitochondrial membrane (Cluster E); yellow, vesicle proteins (Cluster F); pink, GTP binding (Cluster H); green, ATPase activity (Cluster J), white, various clusters or proteins not associated with clusters listed in Table 2.

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"For Table of Contents Use Only" Manuscript ID: cn-2016-00437e Serotonin transporter associated protein complexes are enriched in synaptic vesicle proteins and proteins involved in energy metabolism and ion homeostasis Authors: Jana Haase, Joanna Grudzinska-Goebel, Heidi Kaastrup Müller, Agnieszka Münster-Wandowski, Elysian Chow, Kieran Wynne, Zohreh Farsi, Johannes-Friedrich Zander, and Gudrun Ahnert-Hilger

Table of Contents Graphic

cytoskeleton

G proteins 14-3-3 proteins ATPases

SERT mitochondrial proteins

synaptic vesicle proteins

glycolysis

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