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Signal dependent ER export of lemur tyrosine kinase 2

Background The membrane anchored kinase, LMTK2, is a serine/threonine kinase predominantly localized to endosomal compartments. LMTK2 has been shown to be involved in the trafficking of the CFTR ion channel, the androgen receptor, as well as modulating neurodegeneration. As a membrane anchored protein, LMTK2 must be exported from the ER, yet the mechanisms whereby LMTK2 is sequestered within the ER for efficient export are unknown. Methods Sequence analysis of the carboxyl tail of LMTK2 revealed a putative di-acidic ER export motif. Site-directed mutagenesis was utilized to ablate this potential motif. Subcellular fractionation, immunofluorescence microscopy, and transferrin recycling assays were used to determine the consequence of mutating LMTK2’s export motif. Results Mutation of the di-acidic export motif led to ER retention of LMTK2, and an increase in protein half-life and a concomitant loss of LMTK2 from its appropriate terminal destination. Loss of LMTK2 from endosomal compartments by preventing its release from the ER is linked to a reduction in transferrin recycling. Conclusions We have identified a di-acidic ER export motif within the carboxyl tail of the membrane anchored kinase LMTK2. This sequence is used by LMTK2 for its efficient export from the ER.

Background
Irrespective of the final destination, all integral membrane proteins are initially synthesized on ribosomes associated with the rough endoplasmic reticulum (ER). The first step in the exit of newly synthesized proteins from the ER, for subsequent trafficking to intacellular organelles or the cell surface, is the incorporation of nascent proteins is their incorporation into COP II transport vesicles. Initiated by the binding of GTP to the small GTPase Sar1, the association of other coat proteins (COPs) Sec23 and Sec24, forms a pre-budding complex that yields a concave surface enriched in basic residues [1][2][3]. Initially thought to be a bulk flow process [4], the efficient export of proteins from the endoplasmic reticulum (ER) is now thought to be a selective process [5], whereby the Sar1-Sec23/24 complex not only elicits membrane curvature, but also selectively enriches cargo proteins into the newly forming COP vesicle. Several groups have identified specific amino acid sequences within the cytoplasmic domains of newly synthesized (and properly folded) proteins that act as called ER export motifs [6][7][8]. One identified ER export motif consists of two adjacent bulky hydrophobic or aromatic residues, as seen in the FF motif of ERGIC53 [9] or the VV motif in the NMDA receptor [2]. The second class of ER export motifs is characterized by two acidic residues separated by a variable amino acid ([D/E]x[D/E]). Initially identified in the vesicular stomatitis virus glycoprotein (VSVG) ( 502 TDIE) [10]. this motif is now found in other mammalian proteins, including potassium channels (KAT1, 495 DTE; TASK-3, 252 EDE 257 DAE) [11][12][13] the cystic fibrosis transmembrane conductance regulator (CFTR; 565 DAD) [14,15] and the angiotensin II receptor ( 357 EME) [16]. Of note for VSV-G, an upstream tyrosine residue appears to enhance the activity of the di-acidic motif ( 501 YTDIE) [10].
Lemur tyrosine kinase 2 (LMTK2), also known as BREK, AATYK-2, cdk5, KPI-2 and Cprk [17,18] is a membrane anchored 1503 amino acid serine/threonine kinase. LMTK2 is not highly expressed in the plasma membrane, but rather is present on intracellular vesicles, where it has multiple functions depending upon the cell type in which it is expressed. Interestingly, although the molecular pathways between tissues differ, LMTK2 appears to play a role in regulating intracellular trafficking events. For example LMTK2 modulates the trafficking and surface expression of the cystic fibrosis ion channel, CFTR, in airway cells [19,20]. Similarly LMTK2 modulates the intracellular trafficking of the androgen receptor in prostate epithelia, where LMTK2 negatively regulates the expression of androgen dependent genes [21,22]. LMTK2 has also been shown to be involved in differentiation of tissues, where LMTK2 plays a role as a negative regulator of NGF-induced neuronal differentiation [17,23]. Male LMTK2 knockout mice are infertile due to lack of development and differentiation of gonadal tissue [17,24]. Several binding partners have been identified for LMTK2, including myosin VI [25,26], including PP1C [18] and cdk5/p35 [27]. It is likely that LMTK2 works in concert with myosin VI to modulate the trafficking events observed in various tissues. Moreover, the fact that LMTK2 is a kinase, and can also modulate the actions of phosphatases [18,20,28], argues that LMTK2 may also be an important mediator, integrating several intracellular signaling and trafficking pathways. LMTK2 contains two hydrophobic domains, which anchor the kinase in lipid bilayers, with a short amino and long carboxyl tail that reside in the cytosol [29,30]; it is within the long carboxyl tail that the catalytic activity of the kinase resides (Fig. 1a). Although there is a clear role for LMTK2 in regulating endocytosis and recycling through its presence in endosomal membranes [17,25,26], the pathways and mechanisms by which nascent LMTK2 exits the ER and enters endosomes is not known. The initial step in the trafficking of any membrane protein to its final destination is its efficient export from the ER. To this end, our results suggest that the di-acidic motif is a key determinant in the export of LMTK2 from the ER. Subsequently, it is likely that other, as yet undetermined, signals will be required for the final targeting of LMTK2 to its final endosomal destination.
Antibodies used were LMTK2 (Rabbit monoclonal, Sigma Aldrich, St Louis MO; note the antibody recognizes a region distal to the putative di-acidic motif [22,29]), TGN46 (Rabbit Polyclonal, Abcam, Cambridge MA), EEA1 (Rabbit monoclonal, Cell Signaling, CA), PDI (Rabbit polyclonal, Santa Cruz, CA), GAPDH (rabbit polyclonal; Santa Cruz). Secondary antibodies were goat anti-rabbit IRDye 680RD conjugates (Licor, Lincoln, NE), and all images were collected on a Licor Odyssey SA imager. For immunofluorescence microscopy, labeled secondary antibodies (cy3 and alexa 488 conjugates) were from Jackson Laboratories (West Grove, PA). All other reagents were obtained from Sigma and were of reagent grade. Topology and location of the predicted ER export motif in LMTK2. a The kinase domain (green) and predicted ER export motif (white) of LMTK2 are located on the cytosolic side of the ER membrane. The location of the ER export motif in the cytosol places it to interact with COPII vesicle components (adapted from [29]. b Alignment of the C-termini of LMTK2 orthologs from different species. The Di-acidic motif is shown in yellow. All sequences were obtained from NCBI website and aligned using VectorNTi software Cell culture CHO Cells [31] were maintained in DMEM/F12 (Life Technologies), and HeLa cells in Advanced DMEM (Life Technologies). All media was supplemented with 10 % FBS and 1 % penicillin/streptomycin, and cells grown in 5 % CO 2 at 37°C. Cell transfections were performed using Lipofectamine 2000™ according to the manufacturer's protocol. Selection of stable cells was achieved by growing cells in media supplemented with 500 μg/ml geneticin for LMTK2 constructs, 100 μg/ml neomycin for mEmerald-TfR, and 3 mg/ml puromycin for LMTK2 siRNA.

Constructs for LMTK2
shRNA against human LMTK2 was from Origene (Rockvile, MD) and contained a puromycin mammalian selection marker for stable selection. Human LMTK2 was a generous gift from Dr Tadashi Yamamoto (Tokyo University) and was expressed in the pCI vector. The LMTK2 A 1110 SA mutant (D 1110 ASE 1112 A) was generated using site-directed mutagenesis using the QuikChange II XL Site-Directed Muagenesis Kit (Agilent, Santa Clara, CA). shRNA resistant constructs were generated by introducing 4 silent mutations into the coding regions of wt and A 1110 SA LMTK2, that overlapped with the recognition sequence of the shRNA construct. LMTK2 constructs were transiently expressed.

Immunofluorescence micoscopy
Cells growing on coverslips to~60 % confluence were fixed with 4 % paraformaldehyde, permeabilized with 0.2 % Triton X-100, blocked with 1 % BSA in PBS and processed for indirect immunofluorescence using primary antibodies as described in Figure Legends. Secondary antibodies coupled to Alexa-Fluor-488 were used to visualize binding of the primary antibodies. Cells were visualized with an Olympus FluoView F10i confocal microscope (Olympus, Tokyo, Japan). For transferrin uptake experiments, cells were starved in RPMI media containing 0.2 % BSA for 2 h, loaded with 5 μg/ml Alex-Tf (Sigma) in RPMI-0.2 % BSA for 20 min at 37°C, washed in PBS and fixed. To calculate a Pearson's coefficient, multiple randomly selected fields from several experiments were collected, and ImageJ software (NIH, Bethesda MD) used to evaluate signal overlap.

Immunoblot analysis
Cells were lysed in TGH buffer (1 % Triton X-100, 10 % glycerol, 25 mM Hepes-Na, pH 7.4) and resolved by SDS-PAGE as previously described [29]. GAPDH was used as a loading control. Detection of primary antibody binding was performed using IRDye-conjugated secondary antibodies (LiCor Biosciences) followed by visualization on an Odyssey SA infrared imaging system (LiCor Biosciences).

FACS analysis of transferring recycling
Transferrin-uptake and recycling was performed as previously described [32]. CHO cells stably expressing the human transferrin receptor (TfR; to bind and internalize human transferrin) were subject to transient transfection with either wt or A 1110 SA LMTK2 . Briefly, cells were incubated with transferrin coupled to Alexa-Fluor 555 (Tf-Alexa-Fluor-555; Sigma) for 30 min at 4°C followed by internalization at 37°C in the continuous presence of Tf-Alexa-Fluor 555). Cells were then washed and incubated at 37°C in media supplemented with 100 μg/ml unlabeled transferrin for 30 min before fixation with 3.7 % PFA. Cell associated Tf-Alexa-Fluor 555 was determined by FACS analysis using a BD LSRII flow cytometer (BD Biosciences).

Subcellular fractination and organelle enrichment
Enrichment of major intracellular organelles was performed using a self-generated iodixanol (OptiPrep™) density gradient. Briefly, cells were homogenized in a sucrose-containing detergent-free buffer at 4°C using and Dounce-type homogenizer to maintain organelle integrity. The homogenate was subject to a series of low speed centrifugations to remove unbroken cells, nuclei, mitochondria and lipids to generate a post mitochondrial fraction. This fraction was adjusted to 20 % (w/v) OptiPrep and layered between 30 and 15 % (w/v) OptiPrep cushions. Samples were subject to centrifugation (3 h at 150,000 x g) at 4°C. Fractions were collected from the top using a syringe and 25G needle. Collected fractions were solubilized in Laemmli sample buffer and resolved by SDS-PAGE on a 4-12 % Bis-Tris gradient gel (Life Technologies). Proteins were transferred to PVDF membranes and probed with appropriate antibodies.

LMTK2 contains potential acidic ER export motifs
Alignment of the sequences of various mammalian orthologs of LMTK2 revealed the presence of a canonical diacidic motif in the distal portion of the C-terminal tail (Fig. 1a, b), irrespective of the overall length of each species LMTK2. Interestingly, as with the di-acidic export motif in VSV-G, a proximal upstream tyrosine residue is also seen. To explore the possible role acidic amino acids in the efficient export of LMTK2 from the ER, we studied the trafficking of wild-type (wt) and mutant LMTK2 ( A1110 SA), where we mutated the D 1110 SE of sequence of wild-type LMTK2 to A 1110 SA.

Co-localization of LMTK2 mutants with ER Markers
To investigate whether mutation of putative acidic ER export signals affects the subcellular distribution of LMTK2, Hela cell lines expressing either wt or A 1110 SA LMTK2 were evaluated. Endogenous LMTK2 was knocked down using a stable shRNA against LMTK2 (Fig. 2a), scrambled shRNA had no effect. shRNA revealed a knockdown of~80 % of endogenous LMTK2. Transient expression of shRNA resistant wt and A 1110 SA LMTK2 revealed expression of both constructs. Overexpression of shRNA resistant wt LMTK2 was performed to rule out any expression artefacts, and to be able to more accurately compare wt and A 111 0SA LMTK2 localization. Determination of the location of the endoplasmic reticulum was performed by Fig. 2 Mutation of the di-acidic export motif causes retention of LMTK2 within the ER. a HeLa cells stably expressing shRNA against LMTK2 were transiently transfected with siRNA resistant constructs for either WT LMTK2 or A1110SA LMTK2. b Following immunofluorescence labeling, LMTK2 was visualized with secondary antibodies conjugated to Alexa 488 dyes (green) and calreticulin observed as the transiently expressed mRFP fusion protein (red). Nuclei are stained blue using DAPI. Bar = 10 μm. c Pearson's coefficients were determined for HeLa cells by imaging at least 30 cells from three independent experiments, encompassing randomly selected fields of view. *p < 0.01 for difference by Student's t-test transient co-expression of mFRP calreticulin (Fig. 2b). Wt LMTK2 signal was observed in discrete puctate structures towards the periphery of the cells, with some signal also seen in the perinuclear region. In contrast, A 1110 SA-LMTK2 displayed a more prominent perinuclear staining pattern, with reduced peripheral vesicular staining. Confirmation that the perinuclear staining overlapped with the endoplasmic reticulum, was determined by observing colocalization of A 1110 SA LMTK2 with the ER marker calreticulin. A Pearson co-efficient analysis revealed a significantly higher co-localization (p < 0.01) between A 1110 SA LMTK2 and calreticulin, compared to wt LMTK2 and calreticulin, arguing for reduced ER export of the A 1110 SA mutant compared to wt LMTK2.
To further elucidate the relative subcellular distributions of wt and A 1110 SA LMTK2, and to evaluate ER retention of the A 1110 SA mutant, cells expressing wt or A 1110 SA LMTK2 were subject to homogenization in a Dounce-type homogenizer in detergent-free buffer, to retain organellar integrity. Post nuclear crude microsomes were subject to separation on a self-generating iodixanol (Optiprep™) gradient medium. Fractions containing enriched subcellular organelles were subject to immunoblot analysis. Several antibodies for ER markers (PDI), Golgi (TGN46), and endosomes (EEA1) were used to probe the various fractions, as well as antibodies against LMTK2. Immunoblot analysis of fractions from the Optiprep™ gradients revealed wt LMTK2 to be found predominantly towards the lighter fractions, with signal also co-fractionating with endosomal markers (Fig. 3). A small signal was also identified in denser ER fractions, consistent with the synthesis of LMTK2 as a membrane protein synthesized within the ER. In contrast to WT LMTK2, A 1110 SA LMTK2 displayed a shift in buoyant density away from lighter regions towards heavier and denser fractions. This was seen as a reduction in LMTK2 content from endosomal fractions and a greater preponderance of A 1110 SA LMTK2 in ER enriched fractions compared to wt LMTK2. No large steady-state levels of LMTK2 in TGN enriched fractions were observed.
One study evaluating the role of acidic export motifs has suggested a tri-acidic sequence to be present in the inwardly rectifying potassium channel, KAT1 [11]. Since there is an acidic amino acid upstream of D 1110 at position D 1108 , we evaluated the possible role of this amino acid by constructing a triple Asp → Ala construct (D 1108 NDSE → A 1108 NA1110SA). Transient expression of WT, A1110SA and ANA1110SA LMTK2 was performed and coexpressed with mRFP-calreticulin (Fig. 4a). As before, WT LMTK2 was found in discrete punctate structures extending past the ER into the cytoplasm. In contrast, both A1110SA and ANA1110SA LMTK2 were observed predominantly in perinuclear regions, which overlapped with calreticulin staining. Peason's coefficient analysis (Fig. 4b) showed a significantly greater overlap between A1110SA and ANA1110SA LMTK2 compared to WT LMTK2 (p < .001 n = 30 cells for each condition). When the overlap of calreticulin with A1110SA and ANA1110SA LMTK2 was compared however, no significant difference in localization between the two mutants was observed (p >0.8; n = 30 cells for each condition).

Mutation of acidic export motifs increases the half-life of LMTK2
Pulse-chase experiments were performed to determine the kinetic effects of the A1110SA mutation on LMTK2 degradation, and the life-time of the protein once it is formed (Fig. 5). Both proteins exhibited fairly short halflives with t 1/2 for both constructs being less than 5 h. Interestingly, the A 1110 SA mutation yielded a protein that exhibited a small but significant (p <0.05) increase in the stability of the protein, with wt LMTK2 having a Fig. 3 Gradient fractionation of cellular organelles shows a retention of A1110SA LMTK2 within the ER. HeLa cells expressing either WT LMTK2 of A1110SA LMTK2 were subject to homogenization in a detergent free buffer, using a Dounce-type homogenizer. Post-nuclear supernatants were applied to an Optiprep™ gradient and resolved by centrifugation. a Fractions were collected and proteins resolved by SDS-PAGE on a 4-12 % gradient gel prior to immunoblotting. b Comparison of relative band intensities of LMTK2 in each fraction (mean data from 4 separate experiments) half-life of~2.5 h and A 1110 SA LMTK2 having a half-life of~3.5 h.

Mutation of acidic export motifs alters transferrin recycling
It has been previously shown that LMTK2 is involved in endosomal recycling [25]. We hypothesized that ablation of the ER export signal for LMTK2 would reduce LMTK2 levels within endosomal membranes and yield a similar phenotype to LMTK2 knockdown. To test this hypothesis, cells were pulsed with fluorescently labeled transferrin to facilitate uptake of transferrin into endosomal components of the endosomal recycling complex (ERC). The ERC is a perinuclear collection of tubulevesicular membranes containing Rab11 [33,34]. CHO cells were utilized due to the absence of detectable LMTK2 [26], which despite knock down in HeLa cells was still present. To evaluate the functional effects of LMTK2 ER exit on transferring recycling, in the absence of a potentially confounding LMTK2 background, we elected to express wt and A 1110 SA in CHO cells, along with the human transferrin receptor. To follow the uptake of transferrin in wt and A 1110 SA LMTK2 expressing cells, cells were pulsed for 20 min with fluorescently labeled transferrin (Alexa-546 transferrin, Molecular Probes). As shown in Fig. 6a, in WT-LMTK2 expressing Fig. 4 Lack of evidence for a tri-acidic export signal for LMTK2. a Cells stably expressing either WT, di-acidic mutants (A1110SA) or tri-acidic mutants (ANA1110SA) of LMTK2 (green), along with mRFP calreticulin (red), were fixed and imaged using immunofluorescence miscroscopy. Nuclei are stained blue using DAPI. Bar = 10 μm. b Pearson's coefficients were determined for cells by imaging at least 30 cells from various randomly selected fields of view. *p < 0.01 for difference by Student's t-test. n.s. = not significantly different cells, internalized transferrin is present in the cell periphery, but also smaller amounts within a perinuclear region. In contrast, in A 1110 SA-LMTK2 expressing cells, transferrin was trapped within a swollen perinuclear recycling compartment. We used FACS analysis to quantify the intracellular trafficking of transferrin in wt-LMTK2 and A 1110 SA-LMTK2 expressing cells (see details in Materials and Methods). To determine if loss of LMTK2 from its appropriate cellular location inhibited recycling of transferrin we pulsed cells with fluorescently labeled transferrin, followed by a chase of 30 min in the presence of excess unlabeled transferrin to facilitate recycling. Both wt-and A 1110 SA-LMTK2 expressing cells took up transferrin to similar levels (Fig. 6b). However, comparing the remaining amount of transferrin in cells, following a 30 min chase, revealed a small but consistent defect in transferrin recycling in A 1110 SA-LMTK2 expressing cells (Fig. 6b, c).

Discussion
The role of LMTK2 in cells is just beginning to be unraveled, but appears to play important roles in ion channel trafficking [19], androgen signaling in prostate cancer [22] and neuro-degeneration [23]. We have previously shown that the long carboxyl tail, as well as the short amino terminus, of LMTK2 are located within the cytosol [29,30]. Moreover, LMTK2 appears to be an important binding partner of other trafficking and signaling molecules, including myosin VI [25], protein phosphatase 1/inhibitor 2 [18], CFTR [19], and the androgen receptor [21,22]. Given these manifold functions and accessory proteins, it is clear that the appropriate subcellular localization of LMTK2 is critical to its cellular physiology. As with all membrane proteins, LMTK2 is initially synthesized within the endoplasmic reticulum, prior to its export within COPII coated vesicles. Rather than bulk flow exit, many proteins contain key regions within their amino acid sequence that facilitate their efficient export from the ER. Di-acidic sequences have been shown to function as ER export motifs in several membrane proteins [10,12,15,[35][36][37]. Among such di-acidic sequences, the DXE sequence is the best characterized, in which both acidic acid residues are required. Comparison of amino acid sequences from LMTK2 orthologs, we identified a stretch of amino acids containing a potential diacidic export motif that is present in all species of LMTK2 identified. Such amino acid identity conserved across various species is usually indicative of that site playing a key role in the function of the protein. Moreover, the potential di-acidic motif is localized within the cytosolic domain of the protein, where it has the potential to interact with COPII components.
Normally LMTK2 is present within the endosomal compartment of cells, where it regulates trafficking events. Mutation of the di-acidic code at asparate 1110 and glutamate 1112 to alanines caused a marked retention of LMTK2 within the ER, as determined by colocalization with the ER marker calreticulin. We documented such ER retention by both immunofluorescence microscopy and by iodixanol enrichment of subcellular membrane compartments. The finding that ablation of a di-acidic code leads to ER retention of LMTK2 is finding not confined to LMTK2, but also observed in many other proteins bearing a di-acidic ER export motif, including vesicular stomatitis virus protein G [10], G protein coupled receptors [16], potassium channels [38,39], and anion channels [15]. A small amount of mutant LMTK2 is likely to undergo export from the ER, as the di-acidic signal facilitates efficient ER export, rather than an all or none signal; thus bulk flow export continues unimpeded. We were unable to completely ablate ER export of LMTK2 through mutation of the acidic code, however this is also true for mutation of the di-acidic code in many other proteins, including CFTR [40], the TASK-3 potassium channel [12] and ERGIC-53 [41]. The inability to completely knock out ER export, may be due to several reasons. For example, in addition to the di-acidic code, other signals may also be present in proteins. In several cases, this is due to a tyrosine residue. For example, a conserved tyrosine residue in the transmembrane domain of CASP is needed for its export from the ER to the Golgi [42]. In plants, mutation of the tyrosine residue alone in CASP does not impair ER export, however it can support a degree of ER export in the absence of the di-acidic code [43]. In the present manuscript we did not focus on the potential role of tyrosine residues. In addition, it is unlikely that we were able to completely Fig. 6 Loss of LMTK2 ER export impairs transferrin recycling. a Cells were loaded with Tf-Alexa-Fluor 555 before fixation. Images are confocal z-projections. Bar 10 μm. b Cells were starved of transferrin in serum free media for 30 mins, followed by exposure to fluorescently labeled transferrin (Tf-Alexa 546) for 30 mins at 4°C, followed by an additional 30 mins at 37°C. Cells were rinsed in Tf-Alexa 546 free media supplemented with unlabeled transferrin, and stained using antibodies against LMTK2 (green). Red (Tf Alexa 546), blue (nuclei stained with DAPI). c Flow cytometry shows the total amount of transferrin taken up by cells at time t = 0 min (grey rectangle) and time t = 30 min chase (white rectangle). Data are mean ± SD from three independent experiments. *p <0.05 for difference between wt and A 1110 SA LMTK2 knock down LMTK2 using shRNA. Thus there is likely some residual endogenous LMTK2 that is still present and confounding our data. Nonetheless, despite the observation that we were not able to have complete colocalization of A 1110 SA LMTK2, our results were nonetheless consistent in showing a significant difference between wt and mutant LMTK2. Moreover, the consistency in our findings using two independent methologies (i.e., immunofluorescence microscopy and subcellular fractionation) supports the notion that our results are valid. Although we have not formally ruled out any major structural changes associated with our mutagenesis, the fact that the EX export motif is considerably downstream to the catalytic domain and membrane spanning regions suggests that the protein may fold appropriately. If this is the case, the protein should not be major substrate for ERAD, and could accumulate rather than being degraded. This being the case, we might anticipate that the overall half-life of the protein would be increased. Indeed, this appears to be the case for the anion channel CFTR, where blockade of its ER export (in this case an entirely wild-type CFTR protein) leads to a small but clear increase in CFTR stability [15].
The functional consequences of our preventing the efficient ER export of LMTK2 are reminiscent of studies reducing endosomal LMTK2 through siRNA mediated knock down of LMTK2 [25]. Thus although A 1110 SA LMTK2 is functionally intact (we have no formal evidence in support of this, but our mutations are in regions distinct from the catalytic domain and protein binding regions) the lack of protein in appropriate endosomal regions, due to ER retention, affects membrane trafficking. Loss of endosomal LMTK2 has no marked impact upon transferrin endocytosis, a finding also seen for LMTK2 knock down [25]. However the efficient recycling and loss of transferrin from the cell is impeded in A 1110 SA LMTK2 expressing cells. Although not a complete loss of transferrin recycling, inhibition of LMTK2 export resulted in a similar degree of transferrin retention as that observed for RNAi knockdown of LMTK2 [25]. Although some studies have suggested that blocking TfR delivery from early endosomes to the ERC might increase a direct fast recycling pathway [44], knock down of total LMTK2 does not induce such a pathway [25]; thus it is unlikely that such a pathway would be induced when endosomal LMTK2 levels are depleted through inhibition of efficient ER export. Whilst the first step in targeting LMTK2 to endosomal compartments of necessity is the export of membrane anchored LMTK2 from the ER, it is likely that other signals (i.e., not a di-acidic motif) are responsible for post ER trafficking of LMTK2 to endosomes; such signals remain to be identified. Thus, the di-acidic motif is likely only required to allow LMTK2 to exit the ER efficiently.
Here, we have established that efficient anterograde tranposer of LMTK2, from the site of its synthesis in the ER to its destination in endosomal compartments, requires an acidic ER export motif for its initial exit from the ER. LMTK2 plays an important role in modulating the physiological function of a number of organs, including the airways [19], prostate gland [22] and brain [17,27], as well as in the development of various human cancers [22,45,46]. As we begin to elucidate the cellular and organismal physiology of LMTK2, LMTK2 may provide a novel target for the treatment of human diseases in which LMTK2 is involved.

Conclusion
In conclusion, our results provide evidence for the presence of a di-acidic ER export motif in LMTK2, and provide evidence that the export of LMTK2 from the ER occurs through a selective mechanism. Since LMTK2 plays a pivotal role in a number of human diseases, targeting LMTK2 and its trafficking may provide a novel foundation for designing drugs to treat diseases impacted by LMTK2.


extfieldsofstudy: Physics Medicine Chemistry

text:
The physical size of transcription factors is key to transcriptional regulation in chromatin domains

Genetic information, which is stored in the long strand of genomic DNA as chromatin, must be scanned and read out by various transcription factors. First, gene-specific transcription factors, which are relatively small (∼50 kDa), scan the genome and bind regulatory elements. Such factors then recruit general transcription factors, Mediators, RNA polymerases, nucleosome remodellers, and histone modifiers, most of which are large protein complexes of 1–3 MDa in size. Here, we propose a new model for the functional significance of the size of transcription factors (or complexes) for gene regulation of chromatin domains. Recent findings suggest that chromatin consists of irregularly folded nucleosome fibres (10 nm fibres) and forms numerous condensed domains (e.g., topologically associating domains). Although the flexibility and dynamics of chromatin allow repositioning of genes within the condensed domains, the size exclusion effect of the domain may limit accessibility of DNA sequences by transcription factors. We used Monte Carlo computer simulations to determine the physical size limit of transcription factors that can enter condensed chromatin domains. Small gene-specific transcription factors can penetrate into the chromatin domains and search their target sequences, whereas large transcription complexes cannot enter the domain. Due to this property, once a large complex binds its target site via gene-specific factors it can act as a ‘buoy’ to keep the target region on the surface of the condensed domain and maintain transcriptional competency. This size-dependent specialization of target-scanning and surface-tethering functions could provide novel insight into the mechanisms of various DNA transactions, such as DNA replication and repair/recombination.

Introduction
Genetic information, which is three-dimensionally (3D) organized as chromatin in the cell, is scanned and read out by transcription. Although the way that protein factors search and reach their target sequence is not well understood, organization of genomic DNA to govern accessibility to the target is a critical factor.
Despite the irregularity of nucleosome fibres, chromatin nevertheless assembles into higher order structures that can be detected by imaging modalities as well as methods that capture chromosome conformation (e.g. [19]). Such studies have revealed that genomic DNA forms numerous packed domains, called 'topologically associating domains' (TADs) [20,21] (or 'topological domains' [22] or 'physical domains' [23]). TADs with hundreds of kilobases in size have been identified in fly, mouse, and human cells, suggesting that domain structure could be a universal building block of chromosomes [20,22,23]. X-ray scattering analysis has revealed condensed domain features of interphase chromatin up to ∼275 nm [14,17,18]. These studies suggest that interphase chromatin domains are highly condensed as 'chromatin liquid drops' [11,17,18], which could be formed by the macromolecular crowding effect [24]. Similar condensed chromatin features with a megabase-sized genomic DNA have been also observed using pulse labelling as DNA replication foci [25][26][27][28] that were retained stably during the cell cycle and subsequent cell generations [29][30][31]. This condensed feature likely hinders accessibility of macromolecular complexes mediating various DNA transactions to the inner core of chromatin domains.
A potential solution to the accessibility issue is to position the target DNA segment at the surface of the condensed chromatin domains. Indeed, transcription seems to occur outside the chromatin domains (figure 2) [32][33][34], raising the possibility that genes to be transcribed are relocated to the domain surface upon demand. Such relocation of DNA segments takes advantage of the flexible and dynamic nature of chromatin, enabled by the irregular folding of nucleosome fibres [35][36][37]. Single nucleosome imaging of live mammalian cells has revealed local nucleosome fluctuations of ∼50 nm/30 ms [35,37]. Relatively large displacement of specific chromatin regions that encompass 20-50 nucleosomes has also been observed in various cells and organisms using LacO array/LacI-GFP system [38][39][40][41][42][43][44]. These extensive chromatin dynamics could facilitate exposure of genomic DNA sequences to the surface of chromatin domains; thereby, increasing accessibility of the DNA for template-directed biological processes such as transcription.
Thus, a critical question in genome organization is how can a specific gene be relocated to, and maintained on, the domain surface for transcription. An as-yetunexplored possibility is that positioning of the transcriptional template depends on factors that mediate the transcriptional process itself. Transcription by RNA polymerase II involves two distinct sequences, regulatory elements and the core promoter, which bind different classes of proteins [45][46][47][48]. Regulatory elements are recognized by sequence-specific DNA-binding proteins, collectively called 'gene-specific transcription factors' (e.g. forkhead family proteins, nuclear receptors, and GATA family in the online supplementary table 1 stacks.iop.org/JPCM/27/064016/mmedia) [49][50][51]. As shown in figure 1, gene-specific transcription factors are relatively small (∼50 kDa).
These factors recruit various complexes to the core promoter, including Mediator, general transcription factors (GTFs), and RNA polymerase II to carry out mRNA synthesis using the DNA template [45,[52][53][54][55][56][57]. Gene-specific transcription factors also recruit various nucleosome remodellers and/or histone-modifying enzymes, which somehow facilitate transcription [58,59]. Notably, most of these factors recruited to DNA at later steps exist as protein complexes and are more than an order of magnitude larger than gene-specific transcription factors (figure 1 and the online supplementary table 1). Whether this size difference among factors mediating transcription simply reflects the degree of complexity of their functions or whether there is a specific requirement for size itself is unknown.
Here, we present a new model of the mechanism by which the physical size of various transcription factors contributes to transcriptional regulation, reflecting their accessibility to condensed chromatin domains. Based on Monte Carlo computer simulation results, we demonstrate that gene-specific transcription factors can dive into chromatin domains and scan the genome for their target sequences. When the target gene has a chance of being exposed on the domain surface, these factors then act as a tag or a 'lifesaving light' to recruit large protein complexes. Due to their large size, such complexes prevent the site from moving back to the inner region of chromatin domains; they act as a 'buoy' to keep the bound regions at the domain surface. This buoyancy mechanism could maintain transcriptional competency and facilitate transcription.

Methods
Expected sizes (diameters) of the transcription factors in the online supplementary table 1 and figure 1 were calculated based on the formula Rn(N ) = 2.24N 0.392 , where N is the number of amino acids in the protein and Rn is given in angstroms [60]. The total number of amino acids in the protein complex was used for the calculation.
All molecules in the simulations were treated as spherical hard-bodies. A Metropolis Monte Carlo method without long-range potentials and hydrodynamic interactions was employed to determine diffusive motion of all molecules [61]. The diffusion coefficients (Ds) of the molecules were determined by the Stokes-Einstein relationship based on parameters from the EGFP monomer, the diameter and D of which were 3.8 nm and 23.5 µm 2 s −1 , respectively [35]. To realize a volume equivalent to that of a nucleosome [62], the diameter and Ds of spheres representing nucleosomes were 10.3 nm and 8.68 µm 2 s −1 . The D values of 5 nm, 10 nm, 15 nm, 20 nm, 25 nm and 30 nm spheres were 18 µm 2 s −1 , 9 µm 2 s −1 , 6 µm 2 s −1 , 4.5 µm 2 s −1 , 3.6 µm 2 s −1 and 3 µm 2 s −1 , respectively.
Simulations were conducted in a 215 nm cubic box with periodic boundaries (figure 5). Initially, 1500 copies of 10 nm spheres (nucleosomes; corresponding to 0.5mM) were randomly placed in the right half region ('chromatin domain') of the box with respect to the x-axis, and 50 spheres of their respective sizes (5-30 nm) were placed in the left half region (figure 3). Motion of the molecules was iteratively simulated under the following procedures: (1) for each sphere, displacements along three axes ( r = ( x, y and z)) were drawn from the normal distribution with zero mean and 2D t variance using a pseudo random number generator; (2) a putative position after the step was computed (r new = r + r), where r is the current position; (3) If the new putative position of the sphere overlapped with any other sphere (collision), the move was rejected; (4) if the moving sphere was a nucleosome, moves that lead to displacements longer than the mobility length (for example, 20 nm) were rejected (the 'dog on a leash' model; see also [35]); Furthermore, moves out of the chromatin domain were rejected (x-coordinate <108 nm or >215 nm) to keep the nucleosome concentration within the domain constant; (5) steps 1-4 were repeated for all spheres in a random order newly determined for each step; (6) time is incremented by t. Results were obtained by averaging 500 samples from 10 independent trials. The simulation time step, t, was 1 ns.

A 'buoy' model of transcriptional regulation
Condensed chromatin domains (figure 2) provide a novel mechanism for transcriptional regulation. As transcription in cell nuclei seems to occur outside of chromatin domains [32][33][34], we imagine that transcription is prevented inside the chromatin domains (inside region with yellow line in figure 2(a)). The transcriptional competency of genes could thus be regulated by changing their 'buoyancy' towards the chromatin domain surfaces [11]. We propose that buoyancy is provided by factors (or complexes) that mediate the transcriptional process itself. While large proteins (green spheres and pink ovals in figures 2(a)-(c)), such as large transcription complexes and RNA polymerase II, cannot enter the condensed chromatin domains, small proteins (yellow spheres) penetrate into the domains to search for their target sequence (red nucleosomes). Once the small protein-target complex is formed (figure 2(b)), the complex moves around and, by chance, ends up on the domain surface (figure 2(c)). This step largely depends on local nucleosome movement (fluctuation) in the domains, presumably driven by Brownian motion [35,37]. The small protein can then act as a tag, or a 'lifesaving light', to recruit large transcription complexes. As shown in figure 2(d), binding of large transcription complexes (green spheres) keeps the transcriptional regions (red nucleosomes) on the surface of the chromatin domain like a 'buoy'. RNA polymerase II (pink oval) then transcribes the region (figures 2(e) and (f )). This buoyancy mechanism could maintain transcriptional competency and facilitate transcription.

Monte Carlo simulation of the transcriptional activation model
To determine the physical size limit of transcription factors (or complexes) that can enter condensed chromatin domains, we reconstructed the chromatin environment in silico using the Metropolis Monte Carlo method [61,63]. In the simulation, transcription factors and nucleosomes were represented as diffusing spherical particles with diameters of 5-30 nm and mobile spherical particles of 10 nm hydrodynamic diameter ( figure 3). The nucleosomes were placed in the right half of the simulation space ('chromatin domain') at a concentration of 0.5mM (figure 3; online supplemental movie stacks.iop.org/JPCM/27/064016/mmedia). The 0.5mM condition corresponds to interphase dense chromatin or mitotic chromosomes [64,65]; for review, see [66]. The nucleosomes are mobile but their movements are restricted to a certain range, resembling 'a dog on a leash' situation [35]. In the left half of the space, which is free from nucleosomes, some spheres of various sizes were placed and moved around freely (figure 3; online supplemental movie). The diffusion coefficients of the spheres were determined based on the Stokes-Einstein relationship (see section 2 for details).
We examined how many spheres were found in the chromatin domain for each sphere type. Figure 4 shows the fraction of each sphere type localized in the chromatin domain as a function of time. After ∼1 ms, ∼40% of the 5 nm spheres moved around in the chromatin domain. The 10 nm spheres had a similar tendency with much lower (∼15%) efficiency. The mean square displacements profiles of these spheres show their apparent free diffusion in the millisecond range (see the online supplementary figure S1 stacks.iop.org/JPCM/27/064016/mmedia). However, we rarely found spheres >15 nm (15-30 nm spheres) in the chromatin domain. The 2D and 3D trajectories in figure 5 demonstrate almost free diffusion of the 5 nm spheres and constrained movement of the 10 nm spheres. Spheres >15 nm were confined outside the chromatin domains.
These simulation results indicate that the chromatin domains have a potential barrier for spheres with diameters >15 nm. Importantly, we also found that the potential barrier of the chromatin domains was effective not only at a highly crowded 0.5mM of nucleosomes, but also under the 0.3mM condition, which is a rather open chromatin state (figure 6). and spherical particles of 10 nm diameter (blue spheres), respectively. The mobile nucleosomes were placed in the right half of the simulation space ('chromatin domain') at a concentration of 0.5mM. Some spheres of various sizes were placed and moved around freely in the left half of the space, which is free from nucleosomes. Note that the small yellow spheres can move in the chromatin domain but not the large green spheres. See section 2 for details.
As previously suggested [35,37,67,68], once proteins can go into the dense domains, they can move around with help of the nucleosome fluctuation. However, the proteins outside the domains tend to keep staying there because they have more space to go. We assume that this tendency generates a potential barrier of the chromatin domain.

Functional relationship between transcription factors (or complexes) and their size
The 5 nm spheres in silico corresponded to gene-specific transcription factors, which bind to their regulatory elements prior to recruitment of other larger transcription complexes. seems to cause isolation of nucleosome fibres by repulsion forces and stabilizes the region on the domain surface ( figure 2(e)). Such nucleosome modification or eviction to increase negative charge could function as a buoy to keep the regions on the chromatin domain surface (figures 2(e) and (f )). As mRNAs are negatively charged polymers, they also might act as a buoy. Taken together, the in silico results support our hypothetical buoy model: the physical size of the transcription factors (complexes) matters in transcriptional regulation. Small proteins can reach the target region inside the chromatin domains and then act as a tag or a 'lifesaving light' to recruit large transcription complexes. The large transcription complexes, which cannot penetrate the condensed chromatin domains, function as a buoy to keep the regions to be transcribed on the domain surfaces.

Discussion
We have emphasized the importance of the physical size of transcription factors and complexes. The large size of transcription complexes allows themselves (or them) to process multiple regulatory inputs (whether from proteins or nucleic acids) simultaneously. In addition to these plausible known functions, our 'buoy' model provides novel insight into transcriptional regulation, particularly in the condensed chromatin domains that have been investigated extensively: small transcription factors such as gene-specific transcription factors are used to search for regulatory elements on the genomic DNA, even in the condensed chromatin domains. The large transcription complexes, including GTFs, Mediator, RNA polymerase, nucleosome remodellers, and histone modifiers are used to tether the target region to the surface for efficient transcription. We also propose that large transcription complexes (green spheres) can stabilize the condensed chromatin domains (figure 7). The boundaries between the domains are highly transcribed as housekeeping genes, tRNAs, and SINE elements [22,69]. As shown in figure 7, in case of housekeeping genes, binding of large transcription complexes, such as GTFs, RNA polymerase II, and Mediator, to the boundaries prevents the boundaries from embedding in the chromatin domains. To transcribe tRNA genes and SINE elements by RNA polymerase III (pol III) [70], highly stable and large (∼1.5 MDa) transcription complex comprising TFIIIB, TFIIIC, and pol III forms at the promoter of these genes [71,72]. This large complex should also stabilize the boundary structures. Again, nucleosome eviction (figure 7(a)), nucleosome modification ( figure 7(b)) and RNAs to increase negative charge could function to stabilize the boundary regions. Binding of specific proteins including histone subtypes to the boundary regions may also function in a similar way (figure 7(c)) . Establishing these boundaries helps to maintain the chromatin domains by avoiding fusion. Since the condensed chromatin domains such as TADs seem to be evolutionally conserved from flies to humans [20,22,23], it is reasonable to consider that the domains have some selective advantages. One possibility is that the condensed chromatin could be more resistant to DNA damage [73]. Another is the benefit in the transcriptional regulation [21,74]. The regulatory mechanism using large and small protein complexes should also be widely used in these species. Our 'buoy' model is applicable not only for transcriptional regulation but also for other genome functions such as DNA replication and DNA repair/recombination.
For example, the pre-replication complex (pre-RC) for initiating eukaryotic DNA replication is a huge complex. Eukaryotic DNA replication is initiated by formation of the pre-RC at the origin of replication. The pre-RC is generated by the ordered assembly of many replication factors, including the origin recognition complex (ORC), Cdc6 protein, Cdt1 protein, and Mcm2-7 (e.g. [75]. The 3 D structure of the ORC has dimensions of ∼16× ∼ 13× ∼ 10 nm. The dimer structure of Mcm2-7 has dimensions of ∼23× ∼ 15× ∼ 15 nm [76,77]. Besides multi-regulatory functions, the physical size of the pre-RC might contribute to maintain the origin sequence to the chromatin domain surface for efficient DNA replication. Some DNA repair proteins also have large dimensions. Another example is the DNA-PK complex, which is required for the non-homologous end-joining pathway that re-joins double-strand breaks (e.g. [75]). The complex is large (∼12× ∼ 15 nm for DNA-PKcs) and binds to the DNA break ends [78,79]. To complete the DNA repair process, such large complexes may move the DNA break ends outside the chromatin domain to avoid losing the ends. BRCA1-PALB2-BRCA2, involved in the homologous recombination repair pathway (e.g. [75]), is also a large protein complex that may have a similar function.
So far chromatin environment in live cells has been observed by various imaging methods.
For instance, fluorescence correlation spectroscopy (FCS) detects Brownian motion of fluorescence probe molecules in a small detection volume generated by confocal microscopic illumination [80,81]. This approach, which is often combined with computer simulation, demonstrated anomalous diffusion of fluorescent probes in crowded environment inside live cell nuclei [82][83][84][85]. Because the FCS detection regions, which are ∼0.4 µm in diameter ×∼1-2 µm in height, are much larger than the typical condensed chromatin domains discussed in this paper (∼100-300 nm in diameter), FCS provides rather macroscopic view on chromatin environment. Singlemolecule imaging can directly reveal the dynamics of specific molecules ( [86][87][88]; for review, see [89]) including nucleosomes [35,36], and can also reveal cellular structures at high resolution sufficient to visualize the chromatin domains in live cells [90,91]. Live cell imaging with dual labelling of chromatin domains and specific transcription factors/complexes at such a super resolution would be able to prove our proposed buoy model.
In conclusion, the physical size consideration of the protein complexes and geometric constraints in the environment bring novel insights into the functions of the chromatin domains and various protein complexes.


extfieldsofstudy: Psychology Medicine

s2fieldsofstudy: Biology Psychology

text:
Effect of dentate gyrus disruption on remembering what happened where

Our previous studies using Bax knockout (Bax-KO) mice, in which newly generated granule cells continue to accumulate, disrupting neural circuitry specifically in the dentate gyrus (DG), suggest the involvement of the DG in binding the internally-generated spatial map with sensory information on external landmarks (spatial map-object association) in forming a distinct spatial context for each environment. In order to test whether the DG is also involved in binding the internal spatial map with sensory information on external events (spatial map-event association), we tested the behavior of Bax-KO mice in a delayed-non-match-to-place task. Performance of Bax-KO mice was indistinguishable from that of wild-type mice as long as there was no interruption during the delay period (tested up to 5 min), suggesting that on-line maintenance of working memory is intact in Bax-KO mice. However, Bax-KO mice showed profound performance deficits when they were removed from the maze during the delay period (interruption condition) with a sufficiently long (65 s) delay, suggesting that episodic memory was impaired in Bax-KO mice. Together with previous findings, these results suggest the role of the DG in binding spatial information derived from dead reckoning and nonspatial information, such as external objects and events, in the process of encoding episodic memory.

Although the hippocampal role in encoding episodic memory is well established, it is unclear how spatial and nonspatial information are integrated in the hippocampus. Entorhinal cortex (EC), which consists of medial and lateral divisions, provides major inputs to the hippocampus (van Strien et al., 2009). Characteristics of grid cells found in the medial EC (Hafting et al., 2005;Sargolini et al., 2006) suggest representation of the internally-generated spatial map (i.e., spatial map generated by dead reckoning) in this brain structure (Leutgeb et al., 2005;O'Keefe and Burgess, 2005;Fuhs and Touretzky, 2006;McNaughton et al., 2006;Witter and Moser, 2006;Gorchetchnikov and Grossberg, 2007). By contrast, neurons in the lateral EC show little spatiallyselective, but object-dependent firing (Hargreaves et al., 2005;Yoganarasimha et al., 2011), suggesting segregation of spatial and nonspatial information processing in the medial and lateral EC, respectively (Knierim et al., 2006;Eichenbaum et al., 2007;Kerr et al., 2007;Deshmukh and Knierim, 2011). Because inputs from the medial and lateral EC converge in the dentate gyrus (DG) and CA3, it has been proposed that the internally-generated spatial map is associated with external landmarks in the DG-CA3 network, forming a distinct spatial context for each environment (Redish and Touretzky, 1997;Hafting et al., 2005;O'Keefe and Burgess, 2005;Knierim et al., 2006Knierim et al., , 2014Witter and Moser, 2006;Gorchetchnikov and Grossberg, 2007;Leutgeb and Leutgeb, 2007).
In this regard, we have shown previously that hippocampal spatial firing is dissociated from external landmarks in Bax knockout (Bax-KO) mice (Lee et al., , 2012b, in which newly generated granule cells continue to accumulate, disrupting neural circuitry specifically in the DG (Sun et al., 2004;Kim et al., 2009). Behaviorally, Bax-KO mice were impaired in finding a target location based on visual landmarks when target locations predicted by dead reckoning and visual landmarks were made incongruent . These results suggest the involvement of the DG in binding the animal's internal spatial map with the sensory information on external landmarks in forming a distinct spatial context for each environment. However, considering that the EC provides major cortical inputs to the hippocampus (van Strien et al., 2009), it is likely that the DG plays a more general role in encoding episodic memory than merely forming a distinct spatial context for each environment (Kesner, 2007). In the present study, we examined whether intact DG is necessary for remembering ''what happened where'' (i.e., spatial mapevent association) in addition to remembering ''what is where'' (i.e., spatial map-object association) using a delayed-nonmatch-to-place task. We obtained results that are consistent with a general role of the DG in binding spatial and nonspatial information in the process of forming episodic memory.

Subjects
Five Bax-KO mice and five wild-type littermates (C57BL/6J genetic background) were used in the present study. Homozygous Bax-KO and wild-type littermate mice were obtained by crossing heterozygous males and females as previously described (Sun et al., 2004). All animals were waterdeprived with free access to food (maintained >80% of ad libitum body weight) and handled extensively before behavioral training began. They were maintained at a 12-h light/dark cycle and performed the behavioral task in the dark phase. The experimental protocol was approved by the Institutional Animal Care and Use Committee of the College of Medicine, Korea University.

Behavioral Task
The animals were tested in a delayed-non-match-to-place task in an open eight-arm radial maze (central platform, diameter: 20 cm; arms, length: 35 cm, width: 5 cm; height of walls along the arms: 20 cm) that was placed near one corner of the testing room (3 × 4 m) containing rich visual cues. A trial began by placing an animal at the central platform and opening the door of a randomly chosen arm (sample arm) with all of the other doors closed. The animal was rewarded with 15 µl of water at the end of the sample arm (sample phase). The door of the sample arm was closed when the animal came back to the central platform, which marked the beginning of a delay period. The animal was either allowed to stay in the maze during the delay period (no interruption condition) or placed in its home cage (located ∼50 cm away from the maze; the same location throughout the experiment), and then placed back on the central platform immediately before the end of the delay period (interruption condition). The doors of the sample arm and a randomly-chosen adjacent arm were open at the end of the delay period (test phase; Figure 1). The animal was rewarded with 15 µl of water by visiting an arm other than the sample arm. Each daily session consisted of a total of six trials with 2 min inter-trial intervals.

Statistical Analysis
Two-way ANOVA (repeated measure), linear regression analysis, and Student's t-tests (two-tailed) were used for statistical comparisons of the animal's performance. A p value < 0.05 was used as the criterion for a significant statistical difference. All data are expressed as mean ± S.E.M.

Results
The animals were initially trained with a 15 s delay under the interruption condition (i.e., they were removed from the maze during the delay period; phase 1 training). The number of correct choices gradually increased over 6 days of training in wild-type littermates (linear regression analysis, slope = 0.429, t-test, p = 4.9 × 10 −4 ), but not Bax-KO mice (slope = −0.051, p = 0.616; Figure 2A). Twoway ANOVA indicated a trend for significant group × day FIGURE 1 | Behavioral task. The animals were tested in a delayed non-match-to-place task in an eight-arm radial maze. They were forced to visit one of the eight arms (sample phase) that was presented with a randomly-chosen adjacent arm (test phase) with a delay. The animals either remained in the maze (no interruption condition) or were removed from the maze (interruption condition) during the delay period.
When the delay duration was reduced to 2 s with no interruption (i.e., the animals were allowed to stay in the maze; phase 2 training), both groups performed well. As the delay duration increased to 15 s and then to 5 min, Bax-KO mice performed comparably to the control group (2 s delay: t (8) = 0.447, p = 0.667; 15 s delay: t (8) = 0.756, p = 0.471; 5 min delay: t (8) = 0.258, p = 0.803), although the level of performance dropped progressively as the delay duration increased ( Figure 2B). These results show that Bax-KO mice, as long as there was no interruption, could retain working memory of a previously visited location for a relatively long period of time.
When the animals were re-trained with a 15 s delay with the removal from the maze during the delay (interruption condition; phase 3 training), both wild-type littermates and Bax-KO mice showed significant enhancement of behavioral performance (the number of correct choices) over 7 days of training (linear regression analysis, wild-type littermates, slope = 0.207, t-test, p = 0.026; Bax-KO mice, slope = 0.200, p = 0.046). Two-way ANOVA also indicated a significant main effect of training day (F (6,48) = 5.140, p = 3.8 × 10 −4 ) without a significant main effect of animal group (F (1,8) = 0.371, p = 0.559) or group × day interaction (F (6,48) = 0.961, p = 0.462; Figure 2C). These results suggest that the initial learning deficit of Bax-KO mice was likely due to a problem in representing the relationship between actions and outcomes or learning a task rule. This pattern persisted up to 35 s delay (phase 4 training; comparison between Bax-KO and wild-type mice, day 17, t (8) = 0.343, p = 0.740, Figure 2D). However, as the delay duration increased to 65 s (animals removed from the maze), the performance of Bax-KO mice was dramatically impaired compared to the wild-type littermates (day 18, t (8) = 4.025, p = 0.004; day 19, t (8) = 2.646, p = 0.029, Figure 2D). The impairment at 65 s delay persisted even when the correct arm was the opposite of the sample arm, instead of an adjacent arm (day 20, t (8) = 2.887, p = 0.020, Figure 2D).

Discussion
We have shown previously that spatial firing of hippocampal neurons in Bax-KO mice was dissociated from an external landmark, and that Bax-KO mice followed dead reckoning instead of landmarks when there was a mismatch between dead reckoning-and landmark-based prediction of a goal location (Lee et al., , 2012b. These results provide empirical evidence for the involvement of the DG in aligning the internally-generated spatial map to external landmarks. The present study shows that Bax-KO mice are impaired not only in using external sensory stimuli, but also in remembering a previously visited location in navigating toward a rewarding location. Performance of Bax-KO mice was intact even with a long (up to 5 min) delay, as long as there was no interruption during the delay. However, Bax-KO mice were profoundly impaired when the delay was sufficiently long (65 s) and there was an interruption during the delay, suggesting that the nature of the deficit is not the inability to hold information on-line as working memory, but more likely to be impaired episodic memory. These results suggest a broader role of the DG in associating spatial (''where'') and nonspatial information (objects and events; information on ''what'') that are required for encoding episodic memory (Figure 3). A recent study that created false fear memory by activating neutral context-associated DG neurons during fear conditioning in a different context (Ramirez et al., 2013) is also consistent with the role of the DG in binding spatial and nonspatial information. In addition, context learning is correlated with synaptic plasticity in the EC-DG pathway, which has a different time course from synaptic plasticity in intrahippocampal circuits during associative learning (Gruart et al., 2014;Carretero-Guillén et al., 2015). Future studies should investigate whether the DG is generally involved in binding spatial and nonspatial information across different experimental settings.
A previous study tested the behavioral performance of mice lacking an N-methyl-D-aspartate (NMDA) receptor subunit in the DG in a six-arm radial maze (Niewoehner et al., 2007). In this study, three arms were always baited, and the other three were never baited. Thus, the animals had to remember which three arms to visit to obtain rewards (spatial reference memory). In addition, in each trial, the animals had to remember which arm to visit next (spatial working memory). On the one hand, the NMDA-receptor mutant mice showed intact reference memory, which is consistent with our previous findings that Bax-KO mice showed intact performance in spatial reference memory tasks as long as there was no mismatch between dead reckoning and visual landmarks ). On the other hand, the NMDA-receptor mutant mice were impaired in the working memory component of the task. It is difficult FIGURE 3 | A model for the role of the dentate gyrus (DG) in binding spatial and nonspatial information in encoding episodic memory. The schematic diagram shows simplified functional connections between the entorhinal cortex (EC) and DG. The DG receives converging inputs from the medial and lateral EC. The medial EC carries spatial information derived from dead reckoning (internally-generated spatial map), and the lateral EC carries nonspatial information (sensory information on external objects and events). The two streams of information are combined in the DG in the process of encoding episodic memory.
to directly compare this result with ours because the task structures are different. It is worth noting, however, that this task is similar to the interruption condition of our task in that the mice had to remember multiple visited locations with intervening behavior. Previous studies have also shown that the hippocampus is required for intact performance in multiplelocation spatial working memory tasks (Olton et al., 1979;Murray et al., 2011). Thus, neural processes supporting online working memory, such as persistent neural activity (Fuster and Alexander, 1971;Kubota and Niki, 1971;Funahashi et al., 1989), might be insufficient to keep track of multiple locations that the animal has visited. Instead, it is more likely that the episodic memory function of the hippocampus is required to solve the three-arm working memory task. Although there exists uncertainty regarding the nature of impaired neural processes underlying impaired performance in a spatial working memory task, these and our results are in line with the requirement of the DG in forming memories of ''what happened where''.
Because the medial and lateral EC send converging projections to the DG and CA3, it has been proposed that spatial and nonspatial information are combined in the DG-CA3 network (Redish and Touretzky, 1997;Hafting et al., 2005;O'Keefe and Burgess, 2005;Knierim et al., 2006;Witter and Moser, 2006;Gorchetchnikov and Grossberg, 2007;Kesner, 2007;Leutgeb and Leutgeb, 2007). Previous DG-manipulation studies (Lee et al., , 2012bDees and Kesner, 2013;Morris et al., 2013) and the current study are consistent with this proposal. However, a recent study (Tang et al., 2014) has raised the possibility that layer II grid cells in the medial EC might be pyramidal neurons that do not project to DG/CA3, but rather project to CA1 (Kitamura et al., 2014). If this is the case, then the DG might have no access to the dead reckoning map. Contrary to this possibility, however, an in vivo intracellular recording study in mice engaged in a virtual navigation task has shown grid cell activity in both stellate and pyramidal cells in the medial EC layer II (Domnisoru et al., 2013). Moreover, a neural network simulation study has shown that physiological properties and connectivity of stellate cells can give rise to stable grid firing (Tamamaki and Nojyo, 1993;Couey et al., 2013). Clearly, additional studies are needed to clarify what type of information is provided from the EC to the DG and CA3. Nevertheless, previous empirical studies (Lee et al., , 2012bDees and Kesner, 2013;Morris et al., 2013) and the current one provide evidence for a role of the DG in combining spatial and nonspatial information. Underlying neural mechanisms could be very different, however, depending on whether or not grid cells project to the DG.
A number of candidate functions have been proposed for the DG, and ''pattern separation'' in particular has garnered much attention, as well as empirical support (Kesner, 2007;Treves et al., 2008). In the present study, however, performance of Bax-KO mice was impaired at a 65 s delay even when the correct arm was the opposite of the sample arm, instead of an adjacent one, suggesting that behavioral impairment of Bax-KO mice was not due to reduced capability for spatial pattern separation (Gilbert et al., 2001;McHugh et al., 2007;Neunuebel and Knierim, 2014). It is worth noting that binding of spatial and nonspatial information and pattern separation are not incompatible functions of the DG. Pattern separation can also be achieved (or facilitated, at least) by conjunctive spatial and nonspatial coding (Kesner, 2007;Morris et al., 2013). Formation of a detailed spatial map of an environment and associating important events/objects with the map will allow fine discrimination of spatial locations where important events took place. In this regard, behavioral studies demonstrating impaired spatial discrimination following DG manipulation (Gilbert et al., 2001;Morris et al., 2012) might as well be explained by impaired spatial-nonspatial conjunctive coding. Likewise, impaired discrimination of similar contexts following DG manipulation (McHugh et al., 2007;Eadie et al., 2012) might also be explained by impaired spatial-nonspatial conjunctive coding. It would be difficult to discriminate two similar contexts solely based on nonspatial cues. Adding additional information that two contexts are located at two different places, which can be achieved by incorporating dead reckoning information in normal animals, might facilitate discrimination of two similar contexts. It remains to be determined whether the pattern separation function of the DG is a natural outcome of spatial-nonspatial conjunctive coding or represents a separate neural process.
It should be noted that we cannot completely rule out other deficits than impaired place-event association as the source for impaired performance of Bax-KO mice in the present task. Bax-KO mice might be impaired in remembering the temporal order of visited arms rather than place-event association. Because the animals were tested multiple times (20 days of training; six trials per day; total 120 trials per animal), they visited all arms multiple times over 20 days of training. If Bax-KO mice were impaired in discriminating between the time that a sample arm was visited (the arm visited in the current trial) and the time that an adjacent arm was visited (the arm that was visited a day ago, for example), then both will be recognized simply as previously visited arms. Although we cannot rule out this possibility, the finding that the hippocampus is not necessary for familiaritybased discrimination (Eichenbaum et al., 2007;Squire et al., 2007) argues against this possibility. Another possibility is that Bax-KO mice were impaired in processing spatial information (information on ''where'') rather than place-event association. This is not likely, either, because the performance of Bax-KO mice was as good as that of wild-type mice in the Morris water maze task as long as goal locations predicted by dead reckoning and landmarks were congruent . Moreover, DG granule cells in Bax-KO mice showed locationspecific discharges, albeit with lower spatial selectivity , indicating that the DG of Bax-KO mice represents spatial information. In addition, that Bax-KO mice were similarly impaired in the current task even when the correct arm was the opposite of the sample arm (day 20) also argues against impaired spatial information processing as the underlying cause for impaired performance of Bax-KO mice in the current task. As another possibility, the DG might process ''what'' information separately from spatial information in normal animals (with spatial-nonspatial conjunction occurring elsewhere, such as in CA3) and, in Bax-KO mice, ''what'' information may not be maintained when the delay is long (65 s) with an interruption. Although we cannot rule out this possibility, converging inputs from the lateral and medial EC to individual granule cells Moser et al., 2014) suggest that diverse types of information are integrated rather than processed separately in the DG. This possibility can be rejected if granule cells are found to concurrently code spatial and nonspatial information, as CA1 cells do Frank et al., 2000;Ferbinteanu and Shapiro, 2003), which remains to be determined. Finally, we cannot rule out the possibility that the DG might be involved in transforming working memory into long-term memory regardless of its content (spatial or nonspatial of information). Information that exceeds working memory capacity might be stored temporarily in the DG before it is stored as a long-term memory, which remains to be tested.

Author Contributions
WRK, JWL and MWJ designed the study; WRK and WS produced animal subjects; WRK, JWL and S-HL collected behavioral data; WRK, JWL, J-SC and MWJ analyzed the data; JWL and MWJ wrote the manuscript with inputs from all other authors.