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. Author manuscript; available in PMC: 2019 May 20.
Published in final edited form as: Rev Neurosci. 2016 Aug 1;27(6):559–573. doi: 10.1515/revneuro-2016-0010

Role of hippocampal activity-induced transcription in memory consolidation

Andrew L Eagle 1, Paula A Gajewski 1, Alfred J Robison 1,*
PMCID: PMC6526723  NIHMSID: NIHMS1028864  PMID: 27180338

Abstract

Experience-dependent changes in the strength of connections between neurons in the hippocampus (HPC) are critical for normal learning and memory consolidation, and disruption of this process drives a variety of neurological and psychiatric diseases. Proper HPC function relies upon discrete changes in gene expression driven by transcription factors (TFs) induced by neuronal activity. Here, we describe the induction and function of many of the most well-studied HPC TFs, including cyclic-AMP response element binding protein, serum-response factor, AP-1, and others, and describe their role in the learning process. We also discuss the known target genes of many of these TFs and the purported mechanisms by which they regulate long-term changes in HPC synaptic strength. Moreover, we propose that future research in this field will depend upon unbiased identification of additional gene targets for these activity-dependent TFs and subsequent meta-analyses that identify common genes or pathways regulated by multiple TFs in the HPC during learning or disease.

Keywords: hippocampus, memory, plasticity, transcription

Introduction

The hippocampus (HPC) is critical for a variety of human behaviors, including episodic learning and responses to stress, and dysfunction or death of HPC neurons underlies diseases like Alzheimer’s dementia, major depressive disorder, and posttraumatic stress disorder. Proper function of the HPC relies upon discrete changes in gene expression driven by transcription factors (TFs) engaged by neuronal activity. However, as these TFs are also critical for the function of many other brain regions and nonnervous tissues, using them as pharmacological targets for the treatment of diseases involving the HPC is not feasible. We therefore propose that the future of research in this field will depend upon unbiased identification of gene targets for these activity-dependent TFs and subsequent meta-analyses that identify common genes or pathways regulated by multiple TFs in the HPC during learning or disease. Such research may uncover factors or pathways whose regulation is unique to the HPC and which may therefore serve as viable pharmacological targets for therapeutic intervention in neurological and psychiatric diseases involving HPC dysfunction. Here, we review the nature and mechanisms of activity-dependent TFs that are critical for HPC function, including their role in memory consolidation and long-term plasticity, as well as their currently known gene targets.

The HPC in memory consolidation

Memory consolidation underlies experience-dependent changes in our behavior (McGaugh, 2000), driving adaptation to novel circumstances and setting the stage for expected behavior in familiar environments. Experiences induce a cascade of events across brain regions, starting with sensory information processing in cortical regions. The HPC is a unique brain region that consolidates this experiential input into memory traces that can be shunted into other regions, such as the cortex, for long-term storage. HPC is particularly important for consolidation of explicit, declarative memories, such as contextual and spatial information.

A period of stabilization is required before a short-term memory is preserved for long-term storage. Synaptic plasticity within the HPC underlies this stabilization, or consolidation, of a labile memory. The consolidation of long-term memories requires connectivity within HPC subregions (dentate gyrus [DG], CA3, CA1) forming a trisynaptic DG–CA3–CA1 loop (Figure 1). Specifically, excitatory glutamatergic inputs convey experiential, sensory information into entorhinal cortex (EC), from both cortical and limbic regions, such as amygdala. EC’s primary projections are to DG, known as the perforant pathway, although EC also projects to CA3, CA1, and subiculum. Glutamatergic DG granule cells project to pyramidal neurons in CA3 (the mossy fiber pathway), which send glutamatergic Schaffer collateral projections to pyramidal neurons in CA1. Connectivity within the trisynaptic loop is modulated by enduring forms of activity-dependent synaptic plasticity called long-term potentiation (LTP) and long-term depression (LTD). Synaptic plasticity is hypothesized to encode a memory trace by forming networks of strongly connected neurons, or memory engrams (Govindarajan et al., 2006; Neves et al., 2008; Silva et al., 2009). There-after, the CA1 sends projections through subiculum and back to EC, where memories can be distributed throughout cortex for long-term storage. The trisynaptic loop of DG–CA3–CA1, as well as the plasticity that occurs in these HPC synapses, underlies nearly all forms of explicit memory consolidation, and these changes are driven by transactivation of gene expression.

Figure 1: Hippocampal synaptic plasticity relies on activity-dependent transcription.

Figure 1:

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(A) Depiction of bilateral location of dorsal (dHPC) and ventral (vHPC) mouse HPC (top) and of a coronal slice of dHPC (bottom) showing the connections between the subregions and the general direction of glutamatergic projections (red arrows). (B) Graphical representation of LTP (left) and LTD (right) induced by HFS or LFS, respectively. Gray region indicates long-lasting change in synaptic strength requiring activity-dependent transcription. (C) Select molecular mechanisms of LTP and LTD at CA3–CA1 glutamatergic synapses involving products of genes regulated by activity-dependent TFs (see Table 1).

LTP at CA3–CA1 synapses occurs via postsynaptic signaling mechanisms, resulting in a long-lasting increase in the amplitude of the excitatory response in the postsynaptic cell (Figure 1). This process is dependent on activation of ionotropic N-methyl-d-aspartate receptors (NMDARs), and the subsequent influx of Ca2+ results in an increased synaptic response mediated by changes in the surface expression and function of a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) and/or structural alterations in the postsynaptic element, the dendritic spine. LTP can be further divided into an early phase (that does not require gene transcription) and a transcription-dependent late phase. The process of LTD also contributes to memory consolidation and occurs in both an N-methyl-d-aspartate-dependent manner and/or through a process requiring postsynaptic metabotropic glutamate receptors (mGluRs). Whereas LTP is induced in CA3–CA1 synapses by high-frequency stimulation (HFS), LTD is induced by low-frequency stimulation (LFS) or stimulation of mGluRs. The postsynaptic signaling induced by LFS leads to AMPAR endocytosis, and like LTP, late phases of LTD are also dependent on gene expression (Huber et al., 2000; Manahan-Vaughan et al., 2000). Thus, the long-term changes in synaptic strength underlying memory result from changes in HPC transcription.

Transcription in the HPC

Transcription is a complex process whereby RNA polymerase II (RNApolII) transcribes a sequence of DNA into corresponding messenger RNA (mRNA). An assortment of molecular machinery regulates transcription: promoter regions that direct transcription; TFs that are bound to DNA and facilitate RNApolII binding to promoter regions; coregulators that act to promote or suppress transcription via their interaction with TFs; cofactors that mediate protein–protein interactions between TFs and coregulators; and chromatin regulators that act to remodel chromatin to enhance or suppress TF binding to DNA. The products of transcription include mRNAs that encode proteins and noncoding RNAs that can contribute to cellular complexes (like ribosomes), regulate the translation of mRNAs (i.e. microRNAs), or perform other less well-characterized functions. While each aspect of this complex transcriptional regulatory machinery may contribute to HPC function and learning, here, we will describe the specific role of TFs induced by cellular activity in the HPC and their role in memory consolidation.

Activity-dependent TFs are induced by repeated action potentials that drive the expression of immediate early genes (IEG), many of which encode TFs. Because many of these TFs have additional mechanisms of induction that do not rely on cell activity (Wisden et al., 1990), we will focus on two states: (1) a basal condition in which these TFs are regulating mRNA synthesis to prepare neurons for rapid RNA translation in response to activity and (2) activity-dependent induction of TFs leading to down-stream synthesis of mRNA from genes that are critical for long-term changes in neuronal function and connectivity underlying memory formation, such as potentiation or depression of synaptic activity. This system is complex, tightly regulated, and stable.

Activity-dependent gene transcription is necessary for the consolidation of memories (Alberini, 2009). Transcriptional regulation underlies cellular changes induced by de novo protein and mRNA synthesis critical for memory consolidation (Alberini and Kandel, 2014), and indeed, we have known for decades that infusion of transcriptional inhibitors into HPC prevents late-phase LTP (Nguyen et al., 1994). Specifically, this decrease occurs only when inhibitors are administered during the induction of LTP, and not after induction, e.g. during late phase. This highlights that early-phase LTP is de novo mRNA synthesis independent, whereas late-phase LTP requires transcription to induce RNA synthesis for later translation. It has been recently hypothesized that transcriptional regulation controls the expression of many synaptic proteins that support plasticity (Alberini and Kandel, 2014), and it appears likely that activity-dependent transcription regulated by a subset of TFs is necessary for plasticity underlying the consolidation of an active memory trace. A series of activity-dependent TFs have been described that are critical for this transcription-dependent HPC plasticity and learning. We have divided these into (1) extracellular signal-activated TFs, including cyclic-AMP (cAMP) response element binding protein (CREB), serum-response factor (SRF), and E26 (Ets)-like TF 1 (Elk-1), and (2) IEG TFs associated with plasticity and learning.

Extracellular signaling-activated TFs associated with hippocampal plasticity and learning

CREB

CREB is one of the most well-characterized TFs in learning and memory. It was originally described due to its association with the cAMP response element (CRE) DNA sequence (Montminy and Bilezikjian, 1987), and it is widely expressed throughout the brain, playing a critical role in plasticity in many brain regions, including HPC. There are multiple CREB proteins, most notably CREB1 and CREB2 (activating TF 4; ATF4), which may have opposing actions on plasticity, with CREB1 associated with enhancement or facilitation of long-term plasticity (see below) and ATF4/CREB2 associated with constraints on plasticity (Chen et al., 2003). However, the remainder of this section will focus solely on CREB1, hereafter referred to solely as CREB. CREB activity is mediated by its phosphorylation state (Bito et al., 1996), which lends to its stability, as unphosphorylated CREB is targeted for degradation (Mouravlev et al., 2007). CREB is induced in HPC during spatial learning (Mizuno et al., 2002) and HPC NMDAR-dependent avoidance learning (Cammarota et al., 2000) and is critical for LTP (Yin et al., 1994). Furthermore, HPC CREB inhibition disrupts long-term memory consolidation (Bourtchuladze et al., 1994; Kida et al., 2002; Pittenger et al., 2002), and constitutively active CREB over-expression in HPC increases contextual memory (Restivo et al., 2009). CREB transcriptional activity is also mediated by its binding partners, including CREB binding protein (CBP) (Chrivia et al., 1993), which is important for spatial and contextual learning and dopamine-specific LTP in the HPC (Wood et al., 2005, 2006). It appears, therefore, that CREB is necessary for late-phase or long-term memory consolidation, which is dependent on gene expression underlying de novo protein synthesis. Specifically, CREB may act as the transcriptional switch between protein synthesis-independent short-term memory and protein synthesis-dependent long-term memory.

CREB is regulated by multiple signaling cascades downstream of neuronal activity, including cAMP and Ca2+ (Figure 2) (Wheeler et al., 2012). Specifically, CREB phosphorylation occurs in conjunction with stimuli that induce LTP, and not simply with repeated neuronal firing (Deisseroth et al., 1996), indicating that signaling from the synapse is specifically required for CREB activation in the nucleus. Many molecules have been implicated in this signaling, including the cAMP-dependent protein kinase (PKA), extracellular signal-regulated kinase (ERK), and calmodulin-dependent protein kinases such as CaMKI, CaMKII, and CaMKIV (Bito et al., 1996; Benito and Barco, 2010). Many players in this signaling cascade leading to CREB phosphorylation are crucial for LTP (Malinow et al., 1989; Frey et al., 1993) and HPC transcription (Bading et al., 1993). Supporting this idea, constitutively active CREB (which contains mutations mimicking phosphorylation) primes hippocampal synapses for plasticity, thereby lowering the threshold for long-lasting, late-phase LTP (Barco et al., 2002) and leading to enhanced memory consolidation. Knockout (KO) of specific CREB isoforms impaired HPC LTP in mice (Bourtchuladze et al., 1994), although other studies have failed or only very weakly replicated this effect (Gass et al., 1998; Pittenger et al., 2002), which may be attributed to a different genetic background or that prior studies used a mutant that only knocked out specific isoforms and not other CREB related genes. A dominant negative-inhibitor of CREB (KREB) disrupts learning, and some Ca2+-dependent forms of LTP are impaired by this CREB KO (Pittenger et al., 2002). Additionally, constitutively active CREB overexpression in HPC leads to increases in NMDAR-dependent LTP and silent synapse formation (Marie et al., 2005) and also enhances LTP and memory consolidation (Suzuki et al., 2011), while dominant negative CREB expression impairs memory consolidation (Kathirvelu et al., 2013). CREB has also been shown to regulate intrinsic plasticity, such as cell excitability (Dong et al., 2006; Lopez de Armentia et al., 2007; Benito and Barco, 2010), which supports the premise that CREB activity may confer a competitive advantage allowing for the recruitment of CREB-induced cells during the formation of a memory trace (Han et al., 2007; Benito and Barco, 2010), a hypothesis corroborated experimentally in the amygdala (Kim et al., 2014; Yiu et al., 2014). Finally, a plethora of CREB target genes play a significant role in synaptic, structural, and intrinsic plasticity and signaling (Table 1), and newer studies are beginning to reveal the full complement of basal and memory-related genes that are targeted by CREB (Lakhina et al., 2015).

Figure 2: Common signaling cascades leading to activity-dependent TF activation.

Figure 2:

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Extracellular signals and changes in membrane potential can lead to increases in second-messenger (cAMP and Ca2+) or ERK signaling that converge on kinase activity within the nucleus resulting in phosphorylation and activation of CREB and SRF complexes. These bind to specific elements in promoter regions to regulate transcription of a variety of genes, including IEGs that encode other activity-dependent TFs, like c-fos and FosB.

Table 1:

Known gene targets of individual activity-dependent TFs.

TF Target gene References
CREB BDNF Tao et al., 1998; Lonze and Ginty, 2002; Suzuki et al., 2011
c-fos Sheng and Greenberg, 1990; Sheng et al., 1990; Bito et al., 1996; Suzuki et al., 2011
VMAT Lonze and Ginty, 2002
C/EBP Lonze and Ginty, 2002
iNOS/nNOS Lonze and Ginty, 2002
Egr1 Lonze and Ginty, 2002
JunD Lonze and Ginty, 2002
TrkB Lonze and Ginty, 2002
α1-GABAAR Lonze and Ginty, 2002
Nurr1 Lonze and Ginty, 2002
SGK Lonze and Ginty, 2002
Cdk5 Mayr and Montminy, 2001
somatostatin Montminy and Bilezikjian, 1987; Bito et al., 1996; Lonze and Ginty, 2002
Elk-1 c-fos Hipskind et al., 1991;Janknechtand Nordheim, 1996; Cesari et al., 2004
pip92 Latinkic et al., 1996
SRF MAP1B LI et al., 2014
Arc Ramanan et al., 2005; Etkin et al., 2006; Knöll and Nordheim, 2009; Stritt and Knöll, 2010; Li et al., 2014
c-fos Treisman, 1987; Ramanan et al., 2005; Etkin et al., 2006; Stritt and Knöll, 2010
BDNF Etkin et al., 2006; Knöll et al., 2006
FosB Ramanan et al., 2005; Etkin et al., 2006
NGF Etkin et al., 2006
Nurr1 Etkin et al., 2006
Egr1 Ramanan et al., 2005; Etkin et al., 2006; Stritt and Knöll, 2010; LI et al., 2014
c-jun Etkin et al., 2006
clathrin heavy chain Etkin et al., 2006
Cdk5 Etkin et al., 2006
P35 Etkin et al., 2006
Inh1 Etkin et al., 2006
IP3R1 Etkin et al., 2006
RyR1 Etkin et al., 2006
RyR3 Etkin et al., 2006
Sema3c Knöll et al., 2006; Knöll and Nordheim, 2009
Actin, Actal, Actb, Actg2 Ramanan et al., 2005; Knöll et al., 2006; Miano et al., 2007; Knöll and Nordheim, 2009; Stritt and Knöll, 2010; Li et al., 2014
Rho-GEF5 Knöll etal., 2006
Pak3 Knöll etal., 2006
EphA4/A7 receptor Knöll etal., 2006
Arc Knöll and Nordheim, 2009; Stritt and Knöll, 2010; Li et al., 2014
PSD95 Knöll and Nordheim, 2009
NPAS4 Knöll and Nordheim, 2009
SRF Ramanan et al., 2005; Knöll and Nordheim, 2009; Stritt and Knoll, 2010; Li et al., 2014
Egr1/zif268 Fra1 James et al., 2005
c-jun James et al., 2005
SGK James et al., 2005
GSK3B James et al., 2005
Synapsin, syntaxin, synaptotagmin Knapska and Kaczmarek, 2004; James et al., 2005; Penke et al., 2014
Agrin, gephyrin James etal.,2005
PSD95 Qin et al., 2015
GABAA receptor subunits GABRA2, GABRA4, GABRQ Mo et al., 2015
Arc Penke et al., 2011
cdc20 Conway et al., 2007
Glutamate dehydrogenase, glutamic acid decarboxylase Knapska and Kaczmarek, 2004
FosB/ΔFosB GluA2 Kelz et al., 1999; Vialou et al., 2010
CaMKIIα Robison et al., 2013; Robison et al., 2014
Cdk5 Chen et al., 2000
SPARC-like 1 Vialou et al., 2010
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A list of validated targets of some of the activity-dependent TFs is discussed here, along with references to supporting studies. Neither the gene list nor the references are comprehensive but are rather meant to illustrate (1) the existence of common targets and (2) the fact that many of the known gene targets are directly involved in the molecular mechanisms of synaptic plasticity (see Figure 1C).

SRF

SRF is a member of the MADS-box (MCM1, Agamous, Deficiens, SRF) family of TFs that share a conserved sequence motif and tend to recruit other TFs in multiregulatory complexes but have different DNA binding properties and heterodimer partners (Shore and Sharrocks, 1995). SRF binds the serum-response element (SRE) in many genes, including c-fos (Treisman, 1987), and is integral for IEG induction through Elk-1-dependent (see below) and -independent mechanisms (Xia et al., 1996). Binding to the SRE is dependent on SRF phosphorylation, which is downstream of some of the same signaling cascades that activate CREB (Figure 2), including ERK (Xia et al., 1996).

SRF is highly expressed in all subregions of HPC (Herdegen et al., 1997; Ramanan et al., 2005), where it plays an important role in plasticity and learning. SRF has many gene targets (Table 1), including IEGs and other genes associated with synaptic plasticity, and gene targeting appears to be regulated by various cofactors and phosphorylation states (Knöll and Nordheim, 2009). For example, the CCAAT-enhancer binding protein (C/EBP-β) gene requires SRF binding to SRE for transactivation of SRE-associated genes (Sealy et al., 1997) and Elk-1 contributes to SRF induction of c-fos (Marais et al., 1993), although SRF transcriptional activity may also be Elk-1-independent (Miranti et al., 1995).

SRF has been widely implicated in plasticity and learning. For example, SRF KO mice display impaired IEG induction, mild deficits in LTP (for discussion, see Etkin et al., 2006), and robust deficits in LTD in CA1 neurons, while displaying no change in basal excitatory signaling (Ramanan et al., 2005; Etkin et al., 2006). SRF appears especially important for structural plasticity that may underlie neuronal circuit remodeling; its expression closely follows neuronal development (Stringer et al., 2002), and its deletion produces profound structural changes in HPC (Knöll et al., 2006; Stritt and Knöll, 2010). In particular, SRF regulates neurite outgrowth and proper axonal guidance (Knöll et al., 2006; Li et al., 2014), in addition to dendritic spine development and neuronal migration (Stritt and Knöll, 2010). These functions appear to be mediated by SRF’s regulation of actin cytoskeletal genes (Table 1), and this regulation is associated with a host of outcomes including cell differentiation and development, intracellular trafficking, and synapse remodeling. SRF may also affect axonal development indirectly, as SRF deletion decreases myelination by reducing oligodendrocyte differentiation via paracrine signaling (Stritt et al., 2009). Despite SRF’s importance in actin cytoskeletal organization associated with circuitry remodeling and spine morphogenesis, it does not appear to be necessary for neuronal survival (Ramanan et al., 2005). These findings support the hypothesis that SRF translates synaptic activity into neuronal connectivity in HPC via actin cytoskeletal reorganization (Knöll and Nordheim, 2009).

Elk-1

Elk-1 is a member of the Ets family of oncogenes (Rao et al., 1989) and modulates HPC plasticity and memory consolidation through its interactions with other TFs, such as SRF. While Elk-1 is expressed in many cell types throughout the body, in the brain, it is exclusively expressed in neurons (Sgambato et al., 1998), with strong expression in both DG and CA regions of HPC. Elk-1 mRNA can be found in soma, dendrites, and axons, suggesting that it may play a role in local activity-dependent translation, in addition to its role in transcription. Elk-1 transcriptional activity is induced by growth factors (Marais et al., 1993) and glutamatergic signaling (Vanhoutte et al., 1999) through phosphorylation by the MAPK/ERK cascade (Figure 2). Elk-1 transcriptionally targets SRE to drive SRE-associated gene expression, such as IEGs (Hipskind et al., 1991; Janknecht and Nordheim, 1993). Elk-1 dimerizes with other cofactors and TFs, including SRF and CBP, to regulate gene expression (Hipskind et al., 1991; Janknecht and Nordheim, 1992, 1996). Unlike SRF, which can act in an Elk-1-independent manner (Miranti et al., 1995), there is scant evidence that Elk-1 can regulate gene expression without this dimerization.

Both LTP and LTD in HPC neurons induce MAPK/ERK-dependent Elk-1 phosphorylation (Davis et al., 2000; Thiels et al., 2002), and mGluR-induced LTD requires SRF/Elk-1 for induction of IEGs (Lindecke et al., 2006). Elk-1 KO mice, while displaying normal development and few abnormal phenotypes, show no change in basal c-fos expression but a decrease in kainite-induced seizure induction of c-fos in HPC (Cesari et al., 2004). However, early growth response protein 1 (egr1)/zinc finger protein 268 (zif268) induction by seizures was normal in Elk-1 KO mice, suggesting that induction of IEGs may be compensated by other TFs, e.g. SRF, in Elk-1-deficient mice. This is in line with evidence indicating that activity-dependent induction of SRF-mediated transcription of IEGs acts in both an Elk-1-dependent and independent manner, with Elk-1 enhancing SRF-SRE transcriptional activation (Xia et al., 1996).

Although Elk-1 is induced by learning (Cammarota et al., 2000; Sananbenesi et al., 2002), to date, no study has identified a specific and critical role for HPC Elk-1 in memory formation. Indeed, SRF but not Elk-1 inhibition impairs spatial learning (Dash et al., 2005). Similarly, no impairments in learning have been observed in Elk-1 KO mice (Cesari et al., 2004). Delineating the function of Elk-1 in plasticity and learning is further complicated by its close association with SRF, which is uniquely important for HPC plasticity and learning (see above). This makes it difficult to accurately identify Elk-1 gene targets that are not directly transcribed by SRF (Table 1). However, given the critical role of MAPK/ERK signaling in synaptic plasticity and learning (Davis et al., 2000; Sweatt, 2004), it is likely Elk-1 is involved in some aspect of HPC plasticity and learning that remains to be determined.

IEG TFs associated with hippo-campal plasticity and learning

Egr1/Zif268/NGFI-A/Krox-24

Egr1, which is also known as zif268, nerve growth factor-induced A, and Krox-24, is an IEG encoded by the EGR1 gene. It shows rapid, robust induction following neuronal activation that return to basal levels within 24 h (Knapska and Kaczmarek, 2004). Egr1 expression is induced by NMDAR activation (Worley et al., 1993) but is also widely regulated by a number of different signaling cascades, including trophic factors, membrane-depolarization-induced glutamate signaling, and Ca2+ signaling (Condorelli et al., 1994; Ghosh et al., 1994; Knapska and Kaczmarek, 2004). The promoter region of EGR1 includes six SRE sites, a CRE site, and an activator protein 1 (AP1) binding site (Veyrac et al., 2014), indicating that its induction is downstream of CREB, SRF, Elk-1, and Fos TFs, and it is induced by MAPK/ERK signaling via Elk-1, SRF, and CREB (Davis et al., 2000), suggesting that egr1 is a nexus for activity-dependent gene expression.

EGR1 KO mice show decreased long-term in vivo LTP and impairment in long-term memory formation (Jones et al., 2001), as well as destabilized place cell representations (Renaudineau et al., 2009). Conversely, inducible overexpression of egr1 enhances long-term spatial memory and LTP in DG neurons (Penke et al., 2014), although egr1 may play a larger role in reconsolidation of a memory, rather than its initial consolidation (Lee et al., 2004). Although egr1 appears to be necessary for plasticity, few gene targets supporting this have thus far been uncovered. Nevertheless, NMDAR-dependent induction of egr1 leads to the subsequent repression of the synaptic structure protein PSD-95; this is followed by endocytosis of AMPA receptors and robust LTD (Qin et al., 2015). The majority of gene targets of egr1 have been identified in cancer studies and include genes involved in cell proliferation, differentiation, and survival, as well as apoptosis (Veyrac et al., 2014); however, preliminary microarray studies have further implicated additional target genes of egr1 in the brain (James et al., 2005). Notably, this included genes previously associated with plasticity, such as synapsin II and gephyrin, as well as serum/glucocorticoid regulated kinase and c-Jun (Table 1). Thus, although it is clear that egr1 is critical for learning, the mechanisms by which it controls synaptic function remain to be fully revealed.

AP1

AP1 is a TF complex composed of heterodimers between Fos family proteins, Jun family proteins, Jun dimerization proteins, and/or ATF proteins. A typical AP1 complex consists of Fos-Jun heterodimers that utilize leucine zippers present in both proteins for dimerization and a basic region that interacts with DNA. Because of the variety of AP1 complexes that can form, they are associated with diverse induction stimuli, a number of coactivators/corepressors, and a wide variety of gene targets. For the sake of brevity, we will focus mainly on the Fos family of TFs due to their well-known role in HPC plasticity and learning; however, the remaining members are also important for HPC function (Minatohara et al., 2015).

c-fos

The Fos family of TFs is comprised of c-fos, FosB (and its splice variants, ΔFosB and Δ2ΔFosB), Fra1, and Fra2. While not completely reliant upon neuronal activity (for example, see Wisden et al., 1990), the induction of these TFs is directly associated with neuronal activity, to the point that c-fos staining is commonly used as a marker of neuronal activity (Sagar et al., 1988). The list of environmental and cellular stimuli, signaling pathways, proteins, induction protocols, growth factors, etc., that have been implicated in the regulation of c-fos are too broad a subject for the current review, but it is clear that neurons produce c-fos in response to any activity-inducing stimulus. However, there is scant evidence investigating the gene targets of c-fos and their role in cellular function, specifically in memory consolidation and plasticity. The majority of its known gene targets come from studies in cancer, inflammation, and bone development (Grigoriadis et al., 1993; Matsuo et al., 2000, 2004; Matthews et al., 2007), while its targets in neurons are largely unknown. Many have made the claim that c-fos is merely induced by neuronal activity and does not contribute to long-term cellular changes. We propose here that c-fos is particularly important for plasticity and initial memory consolidation. This is based on preliminary studies described in more detail below showing a correlation between c-fos induction and plasticity, newer studies implicating a role for c-fos in plasticity and learning, and studies showing c-fos may represent aspects of activity associated with a memory engram.

c-fos plays a key role in downstream gene expression underlying neuronal activity (Dragunow and Robertson, 1987; Kaczmarek et al., 1988; Sheng et al., 1990); however, it may also underlie plasticity and learning (Kaczmarek, 1993) by regulating gene expression, including the expression of other TFs associated with plasticity (Sheng and Greenberg, 1990). c-fos is regulated by a variety of factors including SRF/Elk-1 and CREB (Sheng and Green-berg, 1990; Sheng et al., 1990; Hipskind et al., 1991) and is repressed by other factors, such as ΔFosB (Nakabeppu and Nathans, 1991; Renthal et al., 2008). c-fos is transiently and robustly induced, with a half-life ranging from minutes up to a couple hours (Sheng and Greenberg, 1990; Kovács, 1998; Ferrara et al., 2003). It is hypothesized to target a wide variety of genes associated with cell differentiation, cell and synapse development, synaptic plasticity, and learning (Alberini, 2009; West and Greenberg, 2011); however, conclusive evidence for c-fos-specific gene targets, especially those involved in HPC plasticity, has not yet been provided.

Correlative and some preliminary causal evidence suggest that c-fos is important for memory consolidation. In particular, c-fos is induced in the HPC by memory tasks, including spatial learning and a brightness discrimination form of associative learning (Tischmeyer et al., 1990; Guzowski et al., 2001), and inhibition of c-fos impairs memory for the brightness discrimination (Grimm et al., 1997). c-fos is also induced in HPC by LTP (Dragunow et al., 1989; Fleischmann et al., 2003) and has been found to be necessary for induction of LTP (Fleischmann et al., 2003) and LTD (Kemp et al., 2013). Furthermore, brain-specific KO of c-fos produces marked impairments in learning and memory and HPC plasticity (Fleischmann et al., 2003). Recent evidence using manipulations of c-fos to inactivate neuronal ensembles, reactivate consolidated memories, or generate false memory traces suggests a role for c-fos in more than just neuronal activation (Garner et al., 2012; Liu et al., 2012; Cruz et al., 2015). Thus, c-fos is required for transcription-dependent changes in HPC neurons underlying memory consolidation. Future studies examining c-fos gene targets and any link between c-fos and synaptic plasticity will reveal the full extent of its functions underling HPC memory consolidation.

FosB

FosB is encoded by the FosB gene and shares many characteristics and gene targets with c-fos. Like c-fos, FosB has low basal expression in HPC (Herdegen et al., 1995) and is transiently and robustly induced by neuronal activity (Nestler et al., 1999), with a similar half-life in cells (Dobrazanski et al., 1991; Ferrara et al., 2003; Ulery et al., 2006). FosB KO mice show decreased neurogenesis in DG (Yutsudo et al., 2013) and impairment in rearing pups but have normal spatial learning and olfactory discrimination (Brown et al., 1996). Nevertheless, FosB gene targets and its role in plasticity and learning remain unknown; however, other FosB gene products (detailed below) may provide a novel mechanism for chronic activity-dependent gene expression associated with plasticity and learning.

ΔFosB

Splice variation of FosB gene transcripts produces a premature stop codon resulting in the truncated ΔFosB protein. The splice variant lacks two c-terminal degron domains lending it increased stability (Carle et al., 2007); most other Fos TFs have a half-life of a few hours, while ΔFosB has an unusually long-half life, up to 7 days in vivo (Hope et al., 1994; Andersson et al., 2003; Ulery-Reynolds et al., 2009). In addition, Ca2+-signaling may contribute to this stability, as CaMKII has been shown to phosphorylate ΔFosB at Ser27, thereby enhancing its stability (Ulery-Reynolds et al., 2009; Robison et al., 2013). While ΔFosB has a well-characterized role in the nucleus accumbens (NAc) in stress-and reward-related behavior (Robison and Nestler, 2011; Nestler, 2015), more recent evidence suggests that it is induced by a variety of stimuli in HPC, including ischemia (McGahan et al., 1998), drugs of abuse (Perrotti et al., 2008), stress (Perrotti et al., 2004; Vialou et al., 2015), antidepressants (Vialou et al., 2015), and spatial learning (Eagle et al., 2015). While the mechanism for the induction of HPC ΔFosB is unknown, ΔFosB is induced by SRF and CREB in NAc (Vialou et al., 2012). Engram-specific induction of ΔFosB may under-lie memory consolidation, as specific ΔFosB inhibition in HPC impairs multiple forms of learning (Eagle et al., 2015). Interestingly, ΔFosB overexpression in HPC also impaired memory consolidation, perhaps due to dysregulation of preferential connectivity underlying memory engrams (Eagle et al., 2015). While its gene targets are not well known in HPC, studies in other brain regions show that ΔFosB regulates a number of genes associated with plasticity, including c-fos, cdk5, CaMKII, and glutamate receptors, such as GluA2 (Nakabeppu and Nathans, 1991; Kelz et al., 1999; Chen et al., 2000; Robison et al., 2014). Moreover, ΔFosB overexpression regulates syn-apses in both NAc (Grueter et al., 2013) and HPC (Yutsudo et al., 2013) and induces immature spine formation in HPC CA1 pyramidal neurons (Eagle et al., 2015) and D1R-expressing medium spiny neurons of the NAc (Grueter et al., 2013).

Because of its unusual stability, ΔFosB is a unique target for studies examining long-term plasticity or learning in response to chronic environmental changes. This is especially relevant considering that other activity-dependent TFs, such as c-fos, homeostatically decrease expression in HPC after repeated daily trials of learning (Nikolaev et al., 1992; Hess et al., 1995; Bertaina-Anglade et al., 2000), which, interestingly, may even be regulated by ΔFosB (Renthal et al., 2008). Therefore, ΔFosB is an attractive target for further investigation into chronic HPC activity-dependent gene expression driving long-term behavioral adaptations or disease.

C/EBP-B, ATF, others

C/EBP-βb is expressed in adult, but not fetal, brain, primarily in HPC, cerebellum, and cortex (Kuo et al., 1990), where it binds the CCAAT box motif to regulate gene expression. C/EBP is induced in HPC by learning and is required for long-term memory consolidation (Taubenfeld et al., 2001a,b). It has been shown to colocalize with phosphorylated CREB, and CRE-mediated gene expression is required for its induction during memory formation (Athos et al., 2002). C/EBP also appears to be regulated by cAMP and mediates long-term facilitation in Aplysia (Alberini et al., 1994), but its role in HPC plasticity has yet to be established. C/EBP acts as a positive feedback mechanism for brain-derived neurotrophic factor (BDNF) by potentiating BDNF upregulation leading to further C/EBP induction (Bekinschtein et al., 2007; Bambah-Mukku et al., 2014), and BDNF strongly induces HPC LTP (Ying et al., 2002).

ATF4/CREB2, or ATF4, regulates CRE-mediated gene expression and has been hypothesized to act as a transcriptional repressor of plasticity and memory consolidation (Guan et al., 2002). Supporting this, ATF4 inhibition was shown to enhance HPC-dependent memory consolidation and LTP (Chen et al., 2003). Conversely, new evidence demonstrates that ATF4 knockdown decreases dendritic spines, glutamatergic neurotransmission, and expression of synaptic GluA1 and PSD95. Moreover, this decreases LTP and LTD in HPC CA1, impairs long-term memory formation, and is rescued by ATF4 overexpression (Liu et al., 2014; Pasini et al., 2015). Thus, ATF4 appears critical for memory formation, but its precise role in HPC function remains debatable.

More recently, a host of additional activity-dependent TFs important for plasticity and memory consolidation have begun to emerge. For example, the myocyte enhancer factor-2 family of TFs has been shown to act as a critical negative regulator of synaptic plasticity and learning (Rashid et al., 2014). Interestingly, stress may also be associated with HPC plasticity, with glucocorticoid and mineralocorticoid receptors having diverse roles in HPC plasticity in response to stress (Kim and Diamond, 2002; Avital et al., 2006; Berger et al., 2006; Gray et al., 2013). Finally, NF-kB, or nuclear factor kappa-B, which has a wide variety of functions in the brain and other tissues, may play a significant role in HPC plasticity and learning (Albensi and Mattson, 2000; Meffert et al., 2003; Kaltschmidt et al., 2006) through changes in synapse function and synaptogenesis (Boersma et al., 2011). The identification of these and other activity-dependent TFs and their associated gene targets illustrates the complexity of HPC transcription and its role in synaptic, structural, and intrinsic plasticity underlying learning, a knot that must be untangled in order to advance the science of learning and the treatment of diseases involving HPC dysfunction.

Pushing the field forward: uncovering novel pathways

As catalogued in brief above, the role of activity-dependent TFs in HPC function has been extensively studied, and this has greatly advanced the learning and memory field. However, in order for future studies of these TFs to directly impact the treatment of neurological and psychiatric disorders involving dysfunction of the HPC, it will be necessary to determine novel HPC genes and pathways that are common targets of multiple TFs during learning and/or in models of disease. Such advances may arise from comparing data sets generated by mRNA sequencing (RNAseq) experiments on HPC tissue after learning or in a disease model. Overlaying such data sets generated from animals in which select TFs have been overexpressed or silenced could reveal common genes regulated in HPC by multiple activity-dependent TFs under relevant conditions (Figure 3A), many of which may become pharmacologically feasible therapeutic targets. Similarly, using chromatin immunoprecipitation (ChIP) for specific TFs followed by unbiased sequencing approaches will reveal direct binding targets (Figure 3B), and meta-analyses combining all of these approaches should uncover common path-ways whose dysfunction drives disease. Such ‘big data’ approaches are already underway in many labs, and the coming decade should give rise to a host of advances in the field of HPC gene expression that will impact both the science of learning and the treatment of disease.

Figure 3: Identifying novel genes and pathways regulated by activity-dependent HPC gene transcription.

Figure 3:

Open in a new tab

(A) Hypothetical heat plots of RNAseq and proteomic experiments in which individual activity-dependent TFs are genetically or pharmacologically manipulated to reveal genes whose expression is directly or indirectly regulated by each TF. Comparing the unbiased output of such experiments will reveal common potential gene targets that may underlie learning or disease (orange boxes). (B) Similarly, ChIPseq experiments using antibodies against individual activity-dependent TFs to precipitate bound chromatin from HPC of mice undergoing learning or models of disease will reveal common gene targets for activity-dependent TF binding (orange box). Combining the data from such experiments will produce new molecular models of learning and disease.

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