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The Acute Stress Response in the Multiomic Era

  • Amalia Floriou-Servou
    Affiliations
    Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Switzerland

    Neuroscience Center Zurich, ETH Zurich and University of Zurich, Zürich, Switzerland
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  • Lukas von Ziegler
    Affiliations
    Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Switzerland

    Neuroscience Center Zurich, ETH Zurich and University of Zurich, Zürich, Switzerland
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  • Rebecca Waag
    Affiliations
    Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Switzerland

    Neuroscience Center Zurich, ETH Zurich and University of Zurich, Zürich, Switzerland
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  • Christa Schläppi
    Affiliations
    Computational Neurogenomics, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Switzerland

    Neuroscience Center Zurich, ETH Zurich and University of Zurich, Zürich, Switzerland
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  • Pierre-Luc Germain
    Correspondence
    Pierre-Luc Germain, Ph.D.
    Affiliations
    Computational Neurogenomics, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Switzerland

    Neuroscience Center Zurich, ETH Zurich and University of Zurich, Zürich, Switzerland

    Laboratory of Statistical Bioinformatics, Department for Molecular Life Sciences, University of Zürich, Zürich, Switzerland
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  • Johannes Bohacek
    Correspondence
    Address correspondence to Johannes Bohacek, Ph.D.
    Affiliations
    Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zürich, Switzerland

    Neuroscience Center Zurich, ETH Zurich and University of Zurich, Zürich, Switzerland
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Open AccessPublished:January 13, 2021DOI:https://doi.org/10.1016/j.biopsych.2020.12.031

      Abstract

      Studying the stress response is a major pillar of neuroscience research not only because stress is a daily reality but also because the exquisitely fine-tuned bodily changes triggered by stress are a neuroendocrinological marvel. While the genome-wide changes induced by chronic stress have been extensively studied, we know surprisingly little about the complex molecular cascades triggered by acute stressors, the building blocks of chronic stress. The acute stress (or fight-or-flight) response mobilizes organismal energy resources to meet situational demands. However, successful stress coping also requires the efficient termination of the stress response. Maladaptive coping—particularly in response to severe or repeated stressors—can lead to allostatic (over)load, causing wear and tear on tissues, exhaustion, and disease. We propose that deep molecular profiling of the changes triggered by acute stressors could provide molecular correlates for allostatic load and predict healthy or maladaptive stress responses. We present a theoretical framework to interpret multiomic data in light of energy homeostasis and activity-dependent gene regulation, and we review the signaling cascades and molecular changes rapidly induced by acute stress in different cell types in the brain. In addition, we review and reanalyze recent data from multiomic screens conducted mainly in the rodent hippocampus and amygdala after acute psychophysical stressors. We identify challenges surrounding experimental design and data analysis, and we highlight promising new research directions to better understand the stress response on a multiomic level.

      Keywords

      In every person there are “reservoirs of power” which are not ordinarily called upon, but which are nevertheless ready to pour forth streams of energy if only the occasion presents itself.—Walter B. Cannon, 1927

      Molecular Correlates of Allostasis

      The genome-wide molecular changes in response to chronic stress have been extensively characterized (
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      ), as chronic stress is a major risk factor for neuropsychiatric disorders (
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      Unraveling the epigenetic landscape of depression: Focus on early life stress.
      ). Much less is known about the genome-wide response to acute stress, although the border between acute and chronic stress is diffuse. First, it is unclear how many repeated exposures to acute stressors are necessary to qualify as chronic stress. Second, recent work suggests that acute stressors can trigger long-lasting molecular and structural changes in the brain that resemble changes observed after chronic stress [for a review, see (
      • Musazzi L.
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      Acute or chronic? A stressful question.
      )]. More important, whether the stress response is adaptive or maladaptive depends on the modality, intensity, and duration of the stressor as well as on individual (epi)genetic and environmental factors that determine stress resilience or vulnerability. This is addressed by the concept of allostatic load, the paradox that stress-induced signals, which are healthy and favor survival, can also cause pathology when overused or dysregulated (
      • McEwen B.S.
      • Akil H.
      Revisiting the stress concept: Implications for affective disorders.
      ,
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      Protective and damaging effects of stress mediators.
      ). However, the biological correlates that determine whether allostasis successfully manages to maintain homeostasis, or whether allostatic overload damages tissue and leads to disease, remain largely unknown. We propose that detailed multiomic profiling of the acute stress response can provide such a biological correlate of allostatic load. If the molecular response triggered by acute stress can be catalogued, it might be possible to identify processes that go awry in the subset of individuals that respond to acute stressors with psychological disease, as seen with posttraumatic stress disorder (
      • Fenster R.J.
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      Brain circuit dysfunction in post-traumatic stress disorder: From mouse to man.
      ). Furthermore, molecular profiling might reveal when and how the adaptive stress response changes after repeated activation in the context of chronic stress.

      An Overview of the Stress Response System

      The brain continuously integrates sensory information, identifies potential threats, and coordinates appropriate bodily responses. Although most brain areas and circuits are involved in these processes, and various brain circuits can trigger a stress response depending on the nature of the stressor, there are key regions that integrate stress signals in situations of (real or perceived) threat: the paraventricular nucleus of the hypothalamus, the amygdala, and several brainstem nuclei including the locus coeruleus (LC) noradrenergic system (
      • Ulrich-Lai Y.M.
      • Herman J.P.
      Neural regulation of endocrine and autonomic stress responses.
      ,
      • Joëls M.
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      The neuro-symphony of stress.
      ). This leads to the coordinated release of neuromodulators, neuropeptides, and hormones throughout the brain, and it initiates the systemic stress response by activating both the sympatho-adreno-medullary system and the hypothalamic-pituitary-adrenal axis (Figure 1). The sympatho-adreno-medullary system releases noradrenaline from sympathetic nerve endings and triggers adrenaline and noradrenaline release from the adrenal medulla into the blood circulation. This causes the characteristic peripheral effects of the fight-or-flight response (e.g., pupil dilation, increase in heart rate). The hypothalamic-pituitary-adrenal axis, which involves several hormone-mediated signaling steps, culminates in the release of glucocorticoids (mainly corticosterone in rodents and cortisol in humans) from the adrenal cortex a few minutes after stress initiation (
      • Droste S.K.
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      Corticosterone levels in the brain show a distinct ultradian rhythm but a delayed response to forced swim stress.
      ). Glucocorticoids reach all organs through the blood circulation, yet brain entry of glucocorticoids is delayed, starting around 10 minutes and peaking at 30 to 60 minutes after stress initiation (
      • Droste S.K.
      • De Groote L.
      • Atkinson H.C.
      • Lightman S.L.
      • Reul J.M.H.M.
      • Linthorst A.C.E.
      Corticosterone levels in the brain show a distinct ultradian rhythm but a delayed response to forced swim stress.
      ,
      • Kitchener P.
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      • Borrelli E.
      • Piazza P.V.
      Differences between brain structures in nuclear translocation and DNA binding of the glucocorticoid receptor during stress and the circadian cycle.
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      • Collins A.
      • Kersanté F.
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      A rapid release of corticosteroid-binding globulin from the liver restrains the glucocorticoid hormone response to acute stress.
      ,
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      • Sillaber I.
      • Roedel A.
      • Erhardt A.
      • Mueller M.B.
      • Ohl F.
      • et al.
      The temporal dynamics of intrahippocampal corticosterone in response to stress-related stimuli with different emotional and physical load: An in vivo microdialysis study in C57BL/6 and DBA/2 inbred mice.
      ). This exemplifies how all stress signals act across different time scales given that their synthesis, release, breakdown/removal, and downstream cellular effects vary greatly. Their actions are also specific for different parts of the body—different brain regions, cell types, and even cellular compartments—because of differences in axonal projection patterns, receptor expression/localization, or chromatin accessibility (
      • Joëls M.
      • Baram T.Z.
      The neuro-symphony of stress.
      ,
      • Joëls M.
      • Pasricha N.
      • Karst H.
      The interplay between rapid and slow corticosteroid actions in brain.
      ,
      • Hermans E.J.
      • Henckens M.J.A.G.
      • Joëls M.
      • Fernández G.
      Dynamic adaptation of large-scale brain networks in response to acute stressors.
      ). This complexity allows for a rich combinatorial code that enables a fine-tuned behavioral and molecular response to different stressors.
      Figure thumbnail gr1
      Figure 1The three parallel and interconnected stress systems. On exposure to stress, neurons that are mainly located in the hypothalamus, amygdala, and brainstem integrate incoming information and orchestrate the stress response (
      • Ulrich-Lai Y.M.
      • Herman J.P.
      Neural regulation of endocrine and autonomic stress responses.
      ). CRH neurons in the PVN and amygdala release CRH. The LC releases NA throughout the brain, which serves as a broadcast signal sufficient to change brain connectivity and promote vigilance (
      • Hermans E.J.
      • van Marle H.J.F.
      • Ossewaarde L.
      • Henckens M.J.A.G.
      • Qin S.
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      • et al.
      Stress-related noradrenergic activity prompts large-scale neural network reconfiguration.
      ,
      • Zerbi V.
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      • et al.
      Rapid reconfiguration of the functional connectome after chemogenetic locus coeruleus activation.
      ). These stress-induced signals also trigger the activation of the SAM system and the HPA axis. The SAM system first activates the IML, a group of preganglionic neurons in the gray matter of the spinal cord. The IML projects to chromaffin cells in the adrenal medulla, triggering the release of adrenaline and NA into the bloodstream, and to postganglionic noradrenergic neurons that directly innervate internal organs. CRH released by hypophysiotropic neurons of the PVN acts on the anterior pituitary gland and enables the release of ACTH, which in turn triggers the de novo synthesis and release of GCs from the adrenal cortex into the circulation. The SAM system and HPA axis act in parallel to mobilize and reallocate the body’s energy resources. While catecholamines cannot cross the blood–brain barrier, GCs enter the brain and exert multiple effects on cellular structure and function, in part via GR- and MR-mediated membrane effects and GRE-mediated effects on transcription. Created with BioRender.com. ACTH, adrenocorticotropic hormone; CRH, corticotropin-releasing hormone; GC, glucocorticoid; GR, glucocorticoid receptor; GRE, glucocorticoid response element; HPA, hypothalamic-pituitary-adrenal; IEG, immediate early gene; IML, intermediolateral cell column; LC, locus coeruleus; MR, mineralocorticoid receptor; NA, noradrenaline; PVN, paraventricular nucleus of the hypothalamus; SAM, sympatho-adreno-medullary; SNS, sympathetic nervous system.

      Stress and Energy Metabolism

      On the organismal level, the stress response serves to generate and reallocate energy substrates (
      • Cannon W.B.
      Bodily Changes in Pain, Hunger, Fear and Rage: An Account of Recent Researches Into the Function of Emotional Excitement.
      ,
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      The Story of the Adaptation Syndrome: Told in the Form of Informal, Illustrated Lectures.
      ). The high energy demand of the brain results largely from the presynaptic vesicle cycle and from postsynaptic ionic pumps that constantly reestablish ion gradients in response to action potential firing (
      • Boumezbeur F.
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      Competition between glucose and lactate as oxidative energy substrates in both neurons and astrocytes: A comparative NMR study.
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      Neurophysiological investigation of the basis of the fMRI signal.
      ). Stress triggers the release, synthesis, and turnover of glutamate, neuromodulators, and neuropeptides, metabolically highly expensive processes. To fuel these energy demands, the release of adrenaline from the adrenals stimulates the breakdown of glycogen stores (glycogenolysis) in the liver while inhibiting insulin secretion, thereby rapidly raising blood glucose levels (
      • Nonogaki K.
      New insights into sympathetic regulation of glucose and fat metabolism.
      ,
      • Sutherland E.W.
      • Rall T.W.
      The relation of adenosine-3',5'-phosphate and phosphorylase to the actions of catecholamines and other hormones.
      ). However, the brain needs to respond within (milli)seconds to the increased metabolic demand, much faster than bloodborne glucose can arrive at synapses, where mitochondria at pre- and postsynaptic sites ramp up adenosine triphosphate production in response to rising calcium levels (
      • Harris J.J.
      • Jolivet R.
      • Attwell D.
      Synaptic energy use and supply.
      ). These sites are far away from the metabolic machinery of the neuronal cell body but are close to astrocytes, which tightly wrap synapses and provide lactate as fuel for neurons. Importantly, lactate is the preferred energy substrate of neurons in Drosophila, mice, rats, and humans (
      • Boumezbeur F.
      • Petersen K.F.
      • Cline G.W.
      • Mason G.F.
      • Behar K.L.
      • Shulman G.I.
      • Rothman D.L.
      The contribution of blood lactate to brain energy metabolism in humans measured by dynamic 13C nuclear magnetic resonance spectroscopy.
      ,
      • Bouzier-Sore A.-K.
      • Voisin P.
      • Bouchaud V.
      • Bezancon E.
      • Franconi J.-M.
      • Pellerin L.
      Competition between glucose and lactate as oxidative energy substrates in both neurons and astrocytes: A comparative NMR study.
      ,
      • Larrabee M.G.
      Partitioning of CO2 production between glucose and lactate in excised sympathetic ganglia, with implications for brain.
      ,
      • Volkenhoff A.
      • Weiler A.
      • Letzel M.
      • Stehling M.
      • Klämbt C.
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      Glial glycolysis is essential for neuronal survival in Drosophila.
      ), and lactate delivery can sustain neuronal activity in the absence of glucose (
      • Wyss M.T.
      • Jolivet R.
      • Buck A.
      • Magistretti P.J.
      • Weber B.
      In vivo evidence for lactate as a neuronal energy source.
      ). The astrocyte–neuron lactate shuttle hypothesis explains how neuronal activity increases astrocytic glycolysis (glucose use) to produce lactate, which is then shuttled as an energy substrate to neurons (
      • Coggan J.S.
      • Keller D.
      • Calì C.
      • Lehväslaiho H.
      • Markram H.
      • Schürmann F.
      • Magistretti P.J.
      Norepinephrine stimulates glycogenolysis in astrocytes to fuel neurons with lactate.
      ,
      • Mächler P.
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      • Elsayed M.
      • Stobart J.
      • Gutierrez R.
      • von Faber-Castell A.
      • et al.
      In vivo evidence for a lactate gradient from astrocytes to neurons.
      ,
      • Pellerin L.
      • Magistretti P.J.
      Glutamate uptake into astrocytes stimulates aerobic glycolysis: A mechanism coupling neuronal activity to glucose utilization.
      ,
      • Magistretti P.J.
      • Allaman I.
      Lactate in the brain: From metabolic end-product to signalling molecule.
      ,
      • Barros L.F.
      • Weber B.
      CrossTalk proposal: An important astrocyte-to-neuron lactate shuttle couples neuronal activity to glucose utilisation in the brain.
      ). The immediate astrocytic lactate release in response to neuronal activity is mediated by rising extracellular potassium levels (
      • Sotelo-Hitschfeld T.
      • Niemeyer M.I.
      • Mächler P.
      • Ruminot I.
      • Lerchundi R.
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      Channel-mediated lactate release by K+-stimulated astrocytes.
      ). Although less well characterized, oligodendrocytes similarly provide lactate as energy substrate to axons as oligodendrocytes sense glutamate leakage during action potential propagation, which allows them to adjust glucose uptake and lactate production in an activity-dependent manner (
      • Fünfschilling U.
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      Glycolytic oligodendrocytes maintain myelin and long-term axonal integrity.
      ,
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      • Lengacher S.
      • Farah M.H.
      • Hoffman P.N.
      • et al.
      Oligodendroglia metabolically support axons and contribute to neurodegeneration.
      ,
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      • Baltan S.
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      Oligodendroglial NMDA receptors regulate glucose import and axonal energy metabolism.
      ). To sustain lactate supply, the lactate pool needs to be quickly replenished, which occurs through glycogen breakdown (glycogenolysis) in astrocytes. After the immediate release of lactate, glycogenolysis leads to a lactate surge in astrocytes that is dependent in part on β-adrenergic signaling (
      • Zuend M.
      • Saab A.S.
      • Wyss M.T.
      • Ferrari K.D.
      • Hösli L.
      • Looser Z.J.
      • et al.
      Arousal-induced cortical activity triggers lactate release from astrocytes.
      ). Thus, the stress-induced enhancement of the neuron–glia lactate shuttle is mediated by noradrenergic stimulation provided by LC axons, which triggers almost instantaneous calcium influx in astrocytes (
      • Oe Y.
      • Wang X.
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      • Konno A.
      • Ozawa K.
      • Yahagi K.
      • et al.
      Distinct temporal integration of noradrenaline signaling by astrocytic second messengers during vigilance.
      ). In addition, LC activation optimizes neurovascular coupling by controlling vasoconstriction and rerouting blood flow to the regions with sustained oxygen demand and subsequently higher activity (
      • Bekar L.K.
      • Wei H.S.
      • Nedergaard M.
      The locus coeruleus-norepinephrine network optimizes coupling of cerebral blood volume with oxygen demand.
      ). Thus, far-ranging noradrenergic projections likely trigger brainwide switches in the energetic state by tapping into brain energy stores in response to stress-induced activity (
      • Sorg O.
      • Magistretti P.J.
      Characterization of the glycogenolysis elicited by vasoactive intestinal peptide, noradrenaline and adenosine in primary cultures of mouse cerebral cortical astrocytes.
      ). These very rapid effects are followed by rising blood glucose, which reaches the brain and is used by neurons and astrocytes in very different ways. Astrocytes use glucose predominantly through oxidative glycolysis to produce lactate and pyruvate (and to store glycogen). Neurons predominantly process glucose through the pentose phosphate pathway, which is vital for generating reducing equivalents to scavenge reactive oxygen species that result from neurons' exceptionally high mitochondrial oxidative activity [for a detailed review, see (
      • Barros L.F.
      Metabolic signaling by lactate in the brain.
      ,
      • Magistretti P.J.
      • Allaman I.
      A cellular perspective on brain energy metabolism and functional imaging.
      )]. Interestingly, glucocorticoid signaling via glucocorticoid receptors (GRs) appears to counteract this rapid increase in metabolic substrates. Two hours after a short restraint stress exposure, lactate transport within astrocytes is suppressed, an effect that is mediated by glucocorticoid–GR signaling, which reduces lactate delivery from astrocytes to neurons (
      • Murphy-Royal C.
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      • Institoris A.
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      • et al.
      Stress gates an astrocytic energy reservoir to impair synaptic plasticity.
      ). The vital role of mitochondria in adapting to stress-induced changes in metabolic demands—with a focus on chronic stress and psychopathology—has been reviewed in depth elsewhere (
      • Filiou M.D.
      • Sandi C.
      Anxiety and brain mitochondria: A bidirectional crosstalk.
      ,
      • Picard M.
      • McEwen B.S.
      • Epel E.S.
      • Sandi C.
      An energetic view of stress: Focus on mitochondria.
      ). Surprisingly little is known about changes in mitochondria in response to acute stress. In the medial prefrontal cortex (mPFC), acute stress leads to a surge in neuronal activity, triggering an increase in glucose metabolism and synaptic uptake of glucose and increasing the number and size of mitochondria (
      • Musazzi L.
      • Sala N.
      • Tornese P.
      • Gallivanone F.
      • Belloli S.
      • Conte A.
      • et al.
      Acute inescapable stress rapidly increases synaptic energy metabolism in prefrontal cortex and alters working memory performance.
      ). In contrast, metabolic analysis after chronic stress showed reduced mitochondrial respiration and glucose availability in the mPFC (
      • Weger M.
      • Alpern D.
      • Cherix A.
      • Ghosal S.
      • Grosse J.
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      Mitochondrial gene signature in the prefrontal cortex for differential susceptibility to chronic stress.
      ). Thus, the ability to adapt to changing metabolic demands might become dysregulated after chronic stress exposure.

      Molecular Changes Induced by Acute Stress

      Stress-induced changes in neuronal activity and metabolic demand should be reflected on the molecular level as changes in gene expression patterns. Indeed, stress rapidly upregulates messenger RNA and protein levels of many immediate early genes (IEGs) (most prominently c-Fos) in several brain regions (
      • Bland S.T.
      • Schmid M.J.
      • Der-Avakian A.
      • Watkins L.R.
      • Spencer R.L.
      • Maier S.F.
      Expression of c-fos and BDNF mRNA in subregions of the prefrontal cortex of male and female rats after acute uncontrollable stress.
      ,
      • Bohacek J.
      • Manuella F.
      • Roszkowski M.
      • Mansuy I.M.
      Hippocampal gene expression induced by cold swim stress depends on sex and handling.
      ,
      • Roszkowski M.
      • Manuella F.
      • Von Ziegler L.
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      • Moreau J.L.
      • Mansuy I.M.
      • Bohacek J.
      Rapid stress-induced transcriptomic changes in the brain depend on beta-adrenergic signaling.
      ,
      • Carter S.D.
      • Mifsud K.R.
      • Reul J.M.H.M.
      Acute stress enhances epigenetic modifications but does not affect the constitutive binding of pCREB to immediate-early gene promoters in the rat hippocampus.
      ). Induction of IEGs involves several classes of signaling molecules, which seem to act in combination and at different time scales (
      • Revest J.M.
      • Di Blasi F.
      • Kitchener P.
      • Rougé-Pont F.
      • Desmedt A.
      • Turiault M.
      • et al.
      The MAPK pathway and Egr-1 mediate stress-related behavioral effects of glucocorticoids.
      ). Here we exemplify this by focusing on four major stress-induced signals in the rodent hippocampus: 1) glutamate-dependent calcium signaling, 2) glucocorticoids and their interaction with glutamate signaling, 3) glucocorticoids and their transcriptional effects via nuclear GR and mineralocorticoid receptor (MR) signaling, and 4) neuromodulatory signaling through metabotropic receptors.

      Glutamate

      The fastest mediator of stress-induced transcription of IEGs is glutamate. By activating calcium signaling pathways in both neurons (
      • Xia Z.
      • Dudek H.
      • Miranti C.K.
      • Greenberg M.E.
      Calcium influx via the NMDA receptor induces immediate early gene transcription by a MAP kinase/ERK-dependent mechanism.
      ) and astrocytes (
      • Rose C.R.
      • Felix L.
      • Zeug A.
      • Dietrich D.
      • Reiner A.
      • Henneberger C.
      Astroglial glutamate signaling and uptake in the hippocampus.
      ), glutamate triggers the expression of stress-induced IEGs. A prime example in neurons is c-Fos, regulated through the ERK (extracellular signal-regulated kinase) and MAPK (mitogen-activated protein kinase) signaling pathway (
      • Xia Z.
      • Dudek H.
      • Miranti C.K.
      • Greenberg M.E.
      Calcium influx via the NMDA receptor induces immediate early gene transcription by a MAP kinase/ERK-dependent mechanism.
      ). Indeed, several MAPKs are phosphorylated immediately (but transiently) after restraint (
      • Meller E.
      • Shen C.
      • Nikolao T.A.
      • Jensen C.
      • Tsimberg Y.
      • Chen J.
      • Gruen R.J.
      Region-specific effects of acute and repeated restraint stress on the phosphorylation of mitogen-activated protein kinases.
      ) and acute swim (
      • Shen C.P.
      • Tsimberg Y.
      • Salvadore C.
      • Meller E.
      Activation of Erk and JNK MAPK pathways by acute swim stress in rat brain regions.
      ) stress in multiple brain regions.

      Glutamate and GR Interactions

      In addition to immediate synaptic glutamate signaling, acute stress leads to a prolonged accumulation of extracellular glutamate levels in the hippocampus and PFC, an increase that lasts for roughly an hour after an acute stress exposure and depends on glucocorticoid signaling (
      • Lowy M.T.
      • Wittenberg L.
      • Yamamoto B.K.
      Effect of acute stress on hippocampal glutamate levels and spectrin proteolysis in young and aged rats.
      ,
      • Lowy M.T.
      • Gault L.
      • Yamamoto B.K.
      Adrenalectomy attenuates stress-induced elevations in extracellular glutamate concentrations in the hippocampus.
      ,
      • Moghaddam B.
      • Bolinao M.L.
      • Stein-Behrens B.
      • Sapolsky R.
      Glucocortcoids mediate the stress-induced extracellular accumulation of glutamate.
      ,
      • Musazzi L.
      • Tornese P.
      • Sala N.
      • Popoli M.
      Acute stress is not acute: Sustained enhancement of glutamate release after acute stress involves readily releasable pool size and synapsin I activation.
      ,
      • Musazzi L.
      • Milanese M.
      • Farisello P.
      • Zappettini S.
      • Tardito D.
      • Barbiero V.S.
      • et al.
      Acute stress increases depolarization-evoked glutamate release in the rat prefrontal/frontal cortex: The dampening action of antidepressants.
      ). Glucocorticoid-dependent alterations of glutamate receptors—glutamate release, clearance, and metabolism—have been widely studied (
      • Popoli M.
      • Yan Z.
      • McEwen B.S.
      • Sanacora G.
      The stressed synapse: The impact of stress and glucocorticoids on glutamate transmission.
      ). Briefly, acute stress increases surface expression of NMDA receptors and AMPA receptors at the postsynaptic plasma membrane in the mPFC through nongenomic glucocorticoid–GR signaling (
      • Yuen E.Y.
      • Liu W.
      • Karatsoreos I.N.
      • Ren Y.
      • Feng J.
      • McEwen B.S.
      • Yan Z.
      Mechanisms for acute stress-induced enhancement of glutamatergic transmission and working memory.
      ). The key molecules linking glucocorticoids to these effects are the genes Sgk1 and Rab4 (
      • Yuen E.Y.
      • Liu W.
      • Karatsoreos I.N.
      • Ren Y.
      • Feng J.
      • McEwen B.S.
      • Yan Z.
      Mechanisms for acute stress-induced enhancement of glutamatergic transmission and working memory.
      ). This increases both NMDA receptor–mediated and AMPA receptor–mediated synaptic currents between 1 and 24 hours after stress (
      • Yuen E.Y.
      • Liu W.
      • Karatsoreos I.N.
      • Feng J.
      • McEwen B.S.
      • Yan Z.
      Acute stress enhances glutamatergic transmission in prefrontal cortex and facilitates working memory.
      ). In parallel, glucocorticoids nongenomically induce phosphorylation of Ser9 of synapsin 1, which increases the readily releasable pool of glutamate vesicles in the mPFC (
      • Treccani G.
      • Musazzi L.
      • Perego C.
      • Milanese M.
      • Nava N.
      • Bonifacino T.
      • et al.
      Stress and corticosterone increase the readily releasable pool of glutamate vesicles in synaptic terminals of prefrontal and frontal cortex.
      ). Stress-induced GR can also directly interact with the ERK–MAPK signaling pathway (
      • Gutièrrez-Mecinas M.
      • Trollope A.F.
      • Collins A.
      • Morfett H.
      • Hesketh S.A.
      • Kersanté F.
      • Reul J.M.H.M.
      Long-lasting behavioral responses to stress involve a direct interaction of glucocorticoid receptors with ERK1/2-MSK1-Elk-1 signaling.
      ) given that pERK1/2-mediated activation of MSK1 and ELK-1 requires a rapid protein–protein interaction between pERK1/2 and activated GRs. This effect appears within 15 minutes after stress in dentate gyrus granule neurons, but not in other hippocampal subregions. This leads to both phosphorylation of histone H3 at Ser10 and acetylation of Lys14, which then induces transcription of the IEGs c-Fos and Egr-1. For an in-depth discussion of this epigenetic process, see (
      • Reul J.M.H.M.
      • Collins A.
      • Saliba R.S.
      • Mifsud K.R.
      • Carter S.D.
      • Gutierrez-Mecinas M.
      • et al.
      Glucocorticoids, epigenetic control and stress resilience.
      ).

      Glucocorticoids and Hormone Receptor Transcription Factors

      Independent of glutamate, glucocorticoids also act as classic hormone receptor transcription factors. They interact with the high-affinity MR and the low-affinity GR (
      • Reul J.M.H.M.
      • Van Den Bosch F.R.
      • De Kloet E.R.
      Relative occupation of type-I and type-II corticosteroid receptors in rat brain following stress and dexamethasone treatment: Functional implications.
      ,
      • Reul J.M.H.M.
      • De Kloet E.R.
      Two receptor systems for corticosterone in rat brain: Microdistribution and differential occupation.
      ), although the true complexity of their effects (including transrepression and protein–protein interactions with other hormone receptors) is beyond the scope of this review (
      • Ratman D.
      • Vanden Berghe W.
      • Dejager L.
      • Libert C.
      • Tavernier J.
      • Beck I.M.
      • De Bosscher K.
      How glucocorticoid receptors modulate the activity of other transcription factors: A scope beyond tethering.
      ). In the classic mode of action, GR and MR directly bind to glucocorticoid response elements to induce transcription or suppression of target genes (
      • Mifsud K.R.
      • Reul J.M.H.M.
      Acute stress enhances heterodimerization and binding of corticosteroid receptors at glucocorticoid target genes in the hippocampus.
      ,
      • Becker P.B.
      • Gloss B.
      • Schmid W.
      • Strähle U.
      • Schütz G.
      In vivo protein-DNA interactions in a glucocorticoid response element require the presence of the hormone.
      ). In the hippocampus, activated GR accumulates in the nucleus and binds glucocorticoid response elements within 30 minutes of stress exposure or corticosterone administration (
      • Kitchener P.
      • Di Blasi F.
      • Borrelli E.
      • Piazza P.V.
      Differences between brain structures in nuclear translocation and DNA binding of the glucocorticoid receptor during stress and the circadian cycle.
      ,
      • Revest J.M.
      • Di Blasi F.
      • Kitchener P.
      • Rougé-Pont F.
      • Desmedt A.
      • Turiault M.
      • et al.
      The MAPK pathway and Egr-1 mediate stress-related behavioral effects of glucocorticoids.
      ,
      • Nishi M.
      • Ogawa H.
      • Ito T.
      • Matsuda K.-I.
      • Kawata M.
      Dynamic changes in subcellular localization of mineralocorticoid receptor in living cells: In comparison with glucocorticoid receptor using dual-color labeling with green fluorescent protein spectral variants.
      ), and transcriptional waves of gene expression are observed from 30 minutes to 5 hours (
      • Revest J.M.
      • Di Blasi F.
      • Kitchener P.
      • Rougé-Pont F.
      • Desmedt A.
      • Turiault M.
      • et al.
      The MAPK pathway and Egr-1 mediate stress-related behavioral effects of glucocorticoids.
      ,
      • Morsink M.C.
      • Steenbergen P.J.
      • Vos J.B.
      • Karst H.
      • Joels M.
      • Kloet E.R.
      • Datson N.A.
      Acute activation of hippocampal glucocorticoid receptors results in different waves of gene expression throughout time.
      ). While the full extent of GR-mediated transcription in vivo is still not known, there are a number of IEGs (Egr1, Sgk1, and Per1) that are regulated by glucocorticoid response elements and are also readily activated by acute stress in the hippocampus (
      • Revest J.M.
      • Di Blasi F.
      • Kitchener P.
      • Rougé-Pont F.
      • Desmedt A.
      • Turiault M.
      • et al.
      The MAPK pathway and Egr-1 mediate stress-related behavioral effects of glucocorticoids.
      ,
      • Anacker C.
      • Cattaneo A.
      • Musaelyan K.
      • Zunszain P.A.
      • Horowitz M.
      • Molteni R.
      • et al.
      Role for the kinase SGK1 in stress, depression, and glucocorticoid effects on hippocampal neurogenesis.
      ,
      • Reddy T.E.
      • Gertz J.
      • Crawford G.E.
      • Garabedian M.J.
      • Myers R.M.
      The hypersensitive glucocorticoid response specifically regulates period 1 and expression of circadian genes.
      ,
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ). However, there is also evidence that injection of glucocorticoids alone is not sufficient to reproduce most of the transcriptional changes observed after stress (
      • Gray J.D.
      • Rubin T.G.
      • Hunter R.G.
      • McEwen B.S.
      Hippocampal gene expression changes underlying stress sensitization and recovery.
      ), which is in line with the interactions between glutamate and GRs discussed above (
      • Gutièrrez-Mecinas M.
      • Trollope A.F.
      • Collins A.
      • Morfett H.
      • Hesketh S.A.
      • Kersanté F.
      • Reul J.M.H.M.
      Long-lasting behavioral responses to stress involve a direct interaction of glucocorticoid receptors with ERK1/2-MSK1-Elk-1 signaling.
      ) and reminds us that many signals contribute to the transcriptional changes induced by stress. For a detailed description of glucocorticoid-mediated gene expression in the brain, see (
      • Mifsud K.R.
      • Reul J.M.H.M.
      Mineralocorticoid and glucocorticoid receptor-mediated control of genomic responses to stress in the brain.
      ).

      Neuromodulatory Signaling

      Most neuromodulatory signals, such as noradrenaline, dopamine, serotonin, and corticotropin-releasing factor, are relayed through G protein–coupled receptors. Thus, they act slower than glutamate (
      • Oe Y.
      • Wang X.
      • Patriarchi T.
      • Konno A.
      • Ozawa K.
      • Yahagi K.
      • et al.
      Distinct temporal integration of noradrenaline signaling by astrocytic second messengers during vigilance.
      ,
      • Maguire M.E.
      • Ross E.M.
      • Gilman A.G.
      β-Adrenergic receptor: ligand binding properties and the interaction with adenylyl cyclase.
      ) but modulate intracellular signaling cascades and coregulate gene expression (
      • Schutsky K.
      • Ouyang M.
      • Castelino C.B.
      • Zhang L.
      • Thomas S.A.
      Stress and glucocorticoids impair memory retrieval via β2-adrenergic, Gi/o-coupled suppression of cAMP signaling.
      ). Noradrenaline, for example, can potentiate c-Fos expression but likely also regulates unique sets of genes (
      • Roszkowski M.
      • Manuella F.
      • Von Ziegler L.
      • Durán-Pacheco G.
      • Moreau J.L.
      • Mansuy I.M.
      • Bohacek J.
      Rapid stress-induced transcriptomic changes in the brain depend on beta-adrenergic signaling.
      ,
      • Bing G.
      • Stone E.A.
      • Zhang Y.
      • Filer D.
      Immunohistochemical studies of noradrenergic-induced expression of c-fos in the rat CNS.
      ). Stratifying the subcomponents of the stress response is a daunting task. We propose that studying the effects of natural stressors in their entirety—and inhibiting the contribution of specific signaling pathways using pharmacology—is likely the best way forward. Deep multiomic assessment of such changes is now possible across all molecular levels, as summarized in Figure 2 and reviewed in the next section.
      Figure thumbnail gr2
      Figure 2Four levels of measurement to assess the molecular effects of acute stress using multiomic techniques. In level 1, activation of membrane receptors, stress leads to the release of a large variety of neurochemicals (e.g., glutamate, neuromodulators, neuropeptides), which bind to receptors on the cell membrane and induce the opening of ion channels or conformational changes and/or dimerization of G protein–coupled receptors. These events can be visualized in real time with an ever-increasing arsenal of genetically encoded sensors (
      • Ravotto L.
      • Duffet L.
      • Zhou X.
      • Weber B.
      • Patriarchi T.
      A bright and colorful future for G-protein coupled receptor sensors.
      ) using in vivo two-photon imaging (
      • Oe Y.
      • Wang X.
      • Patriarchi T.
      • Konno A.
      • Ozawa K.
      • Yahagi K.
      • et al.
      Distinct temporal integration of noradrenaline signaling by astrocytic second messengers during vigilance.
      ,
      • Patriarchi T.
      • Cho J.R.
      • Merten K.
      • Howe M.W.
      • Marley A.
      • Xiong W.H.
      • et al.
      Ultrafast neuronal imaging of dopamine dynamics with designed genetically encoded sensors.
      ) or miniscopes (
      • Gründemann J.
      • Bitterman Y.
      • Lu T.
      • Krabbe S.
      • Grewe B.F.
      • Schnitzer M.J.
      • Lüthi A.
      Amygdala ensembles encode behavioral states.
      ). In level 2, intracellular signal transduction, receptor binding activates kinases that phosphorylate proteins, which can be sampled using phosphoproteomic techniques based on LC-MS/MS (
      • Arrington J.V.
      • Hsu C.C.
      • Elder S.G.
      • Andy Tao W.
      Recent advances in phosphoproteomics and application to neurological diseases.
      ). In level 3, regulation of transcription, intracellular signaling cascades activate transcription factors, which act in protein complexes to alter the epigenetic profile and regulate gene transcription, changes that can be assessed using epigenomic and transcriptomic techniques (
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ). In level 4, regulation of translation and energy metabolism, some of the transcriptional changes will lead to changes in protein translation, which can be measured using translatomics or proteomics (
      • Murphy-Royal C.
      • Johnston A.D.
      • Boyce A.K.J.
      • Diaz-Castro B.
      • Institoris A.
      • Peringod G.
      • et al.
      Stress gates an astrocytic energy reservoir to impair synaptic plasticity.
      ,
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ,
      • Heiman M.
      • Kulicke R.
      • Fenster R.J.
      • Greengard P.
      • Heintz N.
      Cell type–specific mRNA purification by translating ribosome affinity purification (TRAP).
      ). Owing to the high energy demand, mitochondrial function and metabolism also change, and these changes can be measured with metabolomics (e.g., 1H-MRS, LC-MS). Novel techniques to profile additional layers of molecular regulation rapidly emerge such as interrogating complex codes of covalent protein and mRNA modifications and sequencing tools for various classes of noncoding RNAs. A major challenge is the bioinformatic and conceptual integration of stress-induced changes across these different levels of measurement. Created with BioRender.com. ATP, adenosine triphosphate; ER, endoplasmic reticulum; GFP, green fluorescent protein; 1H-MRS, proton magnetic resonance spectroscopy; LC-MS, liquid chromatography–mass spectrometry; LC-MS/MS, liquid chromatography–tandem mass spectrometry; mRNA, messenger RNA; NT, neurotransmitter; TRAP, translating ribosome affinity purification.

      The Multiomic Landscape of the Acute Stress Response

      Phosphoproteomics

      The fast phosphorylation changes involving ERK–MAPK signaling or synaptic proteins have so far been studied using antibodies for single protein posttranslational modifications (
      • Meller E.
      • Shen C.
      • Nikolao T.A.
      • Jensen C.
      • Tsimberg Y.
      • Chen J.
      • Gruen R.J.
      Region-specific effects of acute and repeated restraint stress on the phosphorylation of mitogen-activated protein kinases.
      ,
      • Shen C.P.
      • Tsimberg Y.
      • Salvadore C.
      • Meller E.
      Activation of Erk and JNK MAPK pathways by acute swim stress in rat brain regions.
      ,
      • Treccani G.
      • Musazzi L.
      • Perego C.
      • Milanese M.
      • Nava N.
      • Bonifacino T.
      • et al.
      Stress and corticosterone increase the readily releasable pool of glutamate vesicles in synaptic terminals of prefrontal and frontal cortex.
      ,
      • Revest J.-M.
      • Kaouane N.
      • Mondin M.
      • Le Roux A.
      • Rougé-Pont F.
      • Vallée M.
      • et al.
      The enhancement of stress-related memory by glucocorticoids depends on synapsin-Ia/Ib.
      ). Owing to technical advances in liquid chromatography coupled to tandem mass spectrometry (
      • Aebersold R.
      • Mann M.
      Mass spectrometry-based proteomics.
      ,
      • Gillet L.C.
      • Leitner A.
      • Aebersold R.
      Mass spectrometry applied to bottom-up proteomics: Entering the high-throughput era for hypothesis testing.
      ,
      • Jünger M.A.
      • Aebersold R.
      Mass spectrometry-driven phosphoproteomics: Patterning the systems biology mosaic: Mass spectrometry-driven phosphoproteomics.
      ), phosphoproteomics now allows simultaneous unbiased detection and quantification of a large number of known or novel protein phosphorylation sites (
      • Arrington J.V.
      • Hsu C.C.
      • Elder S.G.
      • Andy Tao W.
      Recent advances in phosphoproteomics and application to neurological diseases.
      ). Such methods have already been used in vitro, revealing the temporal dynamics of the phosphoproteome following chemical activation of cultured hippocampal neurons across nearly 2000 dynamically altered phosphosites (
      • Engholm-Keller K.
      • Waardenberg A.J.
      • Müller J.A.
      • Wark J.R.
      • Fernando R.N.
      • Arthur J.W.
      • et al.
      The temporal profile of activity-dependent presynaptic phospho-signalling reveals longlasting patterns of poststimulus regulation.
      ). Assessing the phosphoproteome using these techniques after acute stress will be necessary in future work.

      Transcriptomics

      Transcriptomics has been a mainstay technique in neuroscience labs for many years, and several studies have shown that acute stress leads to robust changes in gene expression in the hippocampus (
      • Gray J.D.
      • Rubin T.G.
      • Hunter R.G.
      • McEwen B.S.
      Hippocampal gene expression changes underlying stress sensitization and recovery.
      ,
      • Roszkowski M.
      • Manuella F.
      • Von Ziegler L.
      • Durán-Pacheco G.
      • Moreau J.L.
      • Mansuy I.M.
      • Bohacek J.
      Rapid stress-induced transcriptomic changes in the brain depend on beta-adrenergic signaling.
      ,
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ,
      • Terenina E.E.
      • Cavigelli S.
      • Mormede P.
      • Zhao W.
      • Parks C.
      • Lu L.
      • et al.
      Genetic factors mediate the impact of chronic stress and subsequent response to novel acute stress.
      ,
      • Tsolakidou A.
      • Trümbach D.
      • Panhuysen M.
      • Pütz B.
      • Deussing J.
      • Wurst W.
      • et al.
      Acute stress regulation of neuroplasticity genes in mouse hippocampus CA3 area—Possible novel signalling pathways.
      ,
      • Stankiewicz A.M.
      • Goscik J.
      • Majewska A.
      • Swiergiel A.H.
      • Juszczak G.R.
      The effect of acute and chronic social stress on the hippocampal transcriptome in mice.
      ) and amygdala (
      • Sillivan S.E.
      • Jones M.E.
      • Jamieson S.
      • Rumbaugh G.
      • Miller C.A.
      Bioinformatic analysis of long-lasting transcriptional and translational changes in the basolateral amygdala following acute stress.
      ,
      • Hohoff C.
      • Gorji A.
      • Kaiser S.
      • Willscher E.
      • Korsching E.
      • Ambrée O.
      • et al.
      Effect of acute stressor and serotonin transporter genotype on amygdala first wave transcriptome in mice.
      ). Although hundreds of genes change after an acute stress exposure, the picture remains incomplete. The major challenge here is the dynamic nature of transcription. Given that stress-induced signals will alter the transcriptome in an interactive and temporally defined manner, costly time course experiments are required. In vivo, transcriptomic changes appeared 5 minutes after an acute footshock stressor (
      • Cho J.
      • Yu N.-K.
      • Choi J.-H.
      • Sim S.-E.
      • Kang S.J.
      • Kwak C.
      • et al.
      Multiple repressive mechanisms in the hippocampus during memory formation.
      ), and bath application of corticosterone to hippocampal slices resulted in complex waves of gene expression that terminated within 5 hours (
      • Morsink M.C.
      • Steenbergen P.J.
      • Vos J.B.
      • Karst H.
      • Joels M.
      • Kloet E.R.
      • Datson N.A.
      Acute activation of hippocampal glucocorticoid receptors results in different waves of gene expression throughout time.
      ). Unfortunately, many transcriptomic studies of acute stress need to be interpreted with caution because they are underpowered and resort to uncorrected p values (
      • Gray J.D.
      • Rubin T.G.
      • Hunter R.G.
      • McEwen B.S.
      Hippocampal gene expression changes underlying stress sensitization and recovery.
      ,
      • Peña C.J.
      • Smith M.
      • Ramakrishnan A.
      • Cates H.M.
      • Bagot R.C.
      • Kronman H.G.
      • et al.
      Early life stress alters transcriptomic patterning across reward circuitry in male and female mice.
      ,
      • Terenina E.E.
      • Cavigelli S.
      • Mormede P.
      • Zhao W.
      • Parks C.
      • Lu L.
      • et al.
      Genetic factors mediate the impact of chronic stress and subsequent response to novel acute stress.
      ,
      • Hohoff C.
      • Gorji A.
      • Kaiser S.
      • Willscher E.
      • Korsching E.
      • Ambrée O.
      • et al.
      Effect of acute stressor and serotonin transporter genotype on amygdala first wave transcriptome in mice.
      ) or have compared transcriptional responses using tools like Venn diagrams (
      • Gray J.D.
      • Rubin T.G.
      • Hunter R.G.
      • McEwen B.S.
      Hippocampal gene expression changes underlying stress sensitization and recovery.
      ,
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ,
      • Terenina E.E.
      • Cavigelli S.
      • Mormede P.
      • Zhao W.
      • Parks C.
      • Lu L.
      • et al.
      Genetic factors mediate the impact of chronic stress and subsequent response to novel acute stress.
      ,
      • Tsolakidou A.
      • Trümbach D.
      • Panhuysen M.
      • Pütz B.
      • Deussing J.
      • Wurst W.
      • et al.
      Acute stress regulation of neuroplasticity genes in mouse hippocampus CA3 area—Possible novel signalling pathways.
      ,
      • Gray J.D.
      • Rubin T.G.
      • Kogan J.F.
      • Marrocco J.
      • Weidmann J.
      • Lindkvist S.
      • et al.
      Translational profiling of stress-induced neuroplasticity in the CA3 pyramidal neurons of BDNF Val66Met mice.
      ,
      • Pulga A.
      • Porte Y.
      • Morel J.-L.
      Changes in C57BL6 mouse hippocampal transcriptome induced by hypergravity mimic acute corticosterone-induced stress.
      ), which in retrospect proved to be simplistic and potentially misleading (see Figures S1 and S2). Importantly, because most datasets are publicly available, they can be reevaluated as bioinformatic capabilities evolve. For example, in our previous profiling of the transcriptomic changes triggered by different acute stressors (novelty stress, swim stress, and restraint stress) in the ventral and dorsal hippocampus (
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ), Venn diagrams overestimated the differences in stress-induced gene expression between the two regions as well as the differences in gene expression between stressors. Reanalyzing these published data, we plotted the fold changes of all genes that are significantly altered in either the dorsal or ventral hippocampus, which revealed that stress-induced genes react in a strikingly similar fashion across regions and across stressors (Figure 3A, left two panels). Although an analysis tailored for the identification of region-specific alterations (dorsal vs. ventral hippocampus) in response to stress did uncover some differentially expressed genes (Figure S1B), not all such differences imply different regulatory mechanisms, and some could be due to the differential cell type composition of the two regions (see Supplemental Methods for more details). Analyzing the variance in the expression of each differentially expressed gene (Figure 3B) indicates that most of the variance (∼74% overall) attributable to the different experimental groups is equally well explained by two groups (stressed vs. control animals). Our reanalysis warrants an updated interpretation of the transcriptomic response after acute stress, emphasizing the high overall similarity of transcriptional changes after different psychophysical stressors, and across the dorsal and ventral hippocampus. It will be interesting to see how stress-induced changes differ in additional brain regions such as the amygdala and mPFC.
      Figure thumbnail gr3
      Figure 3Reanalysis of published data reveals region and cell type specificity of stress-induced transcriptomic changes and its relationship to activity-dependent transcription. (A) Comparison of the hippocampal transcriptome in response to psychophysical stressors in the ventral and dorsal hippocampus (two left panels) (
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ) with two models of neuronal activation (two right panels) (
      • Chen P.B.
      • Kawaguchi R.
      • Blum C.
      • Achiro J.M.
      • Coppola G.
      • O’Dell T.J.
      • Martin K.C.
      Mapping gene expression in excitatory neurons during hippocampal late-phase long-term potentiation.
      ,
      • Fernandez-Albert J.
      • Lipinski M.
      • Lopez-Cascales M.T.
      • Rowley M.J.
      • Martin-Gonzalez A.M.
      • del Blanco B.
      • et al.
      Immediate and deferred epigenomic signatures of in vivo neuronal activation in mouse hippocampus.
      ). Shown is the union of genes that respond to psychophysiological stressors or to forskolin-mediated LTP (see ). The stress-induced changes are similar between regions and stressors, and much of this response is also consistent with activity-dependent transcription. (B) Variance explained by experimental groups in the hippocampus dataset (
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ). Each bar represents a DEG (well-known gene names are included as examples); the gray parts represent the proportion of variance explained by the division between stressed animals (i.e., novelty, swim, or restraint) and control animals, while the blue part indicates the additional proportion of the variance that is further explained by the specific stress groups. (C) Comparison of the stress-induced changes in hippocampal bulk messenger RNA sequencing with that of in silico sorted cell types from amygdalar single-cell RNA sequencing data (
      • Wu Y.E.
      • Pan L.
      • Zuo Y.
      • Li X.
      • Hong W.
      Detecting activated cell populations using single-cell RNA-seq.
      ). Shown are the genes that are significantly altered by stress in the hippocampal data as well as in at least one of the cell types in the amygdala. The profiles suggest contributions of different cell types to the shared transcriptional response, in particular of glial and endothelial cells, with a much more marginal contribution of neurons. In both (A) and (C), each row represents the same gene across the entire dataset, and each column represents a biological replicate. Represented are the log-fold changes to the means of the controls (of the respective region) scaled by unit variance. DEG, differentially expressed gene; LTP, long-term potentiation.
      To our knowledge, our data constitute the only direct transcriptomic comparison between different acute stressors in vivo (
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ) (Figure 3A). It is striking that the response to swim and restraint stress is very similar to the arguably more subtle exposure to a novel environment (novelty stress), which prompts an interesting question: To what extent is the observed transcriptional stress response in the hippocampus merely the result of neuronal activation? To address this question, we reanalyzed published data to compare the hippocampal stress signature with two models of neuronal activation (Figure 3A, right panels): forskolin-triggered long-term potentiation in hippocampal slices (
      • Chen P.B.
      • Kawaguchi R.
      • Blum C.
      • Achiro J.M.
      • Coppola G.
      • O’Dell T.J.
      • Martin K.C.
      Mapping gene expression in excitatory neurons during hippocampal late-phase long-term potentiation.
      ) and in vivo kainic acid injection (
      • Fernandez-Albert J.
      • Lipinski M.
      • Lopez-Cascales M.T.
      • Rowley M.J.
      • Martin-Gonzalez A.M.
      • del Blanco B.
      • et al.
      Immediate and deferred epigenomic signatures of in vivo neuronal activation in mouse hippocampus.
      ). Despite the differences in experimental systems and time points profiled, we observe that the vast majority of stress-responsive genes are consistently upregulated or downregulated across datasets at the peak of the response. Clearly, heightened neuronal activity is a central component of the stress response given that one of the key functions of the stress response is to manage excessive glutamate release, via regulation of NMDA and AMPA receptor expression, glutamate clearance by glia, and the reduction of spine density and dendritic complexity (
      • Popoli M.
      • Yan Z.
      • McEwen B.S.
      • Sanacora G.
      The stressed synapse: The impact of stress and glucocorticoids on glutamate transmission.
      ,
      • Chen Y.
      • Dubé C.M.
      • Rice C.J.
      • Baram T.Z.
      Rapid loss of dendritic spines after stress involves derangement of spine dynamics by corticotropin-releasing hormone.
      ,
      • Gunn B.G.
      • Baram T.Z.
      Stress and seizures: Space, time and hippocampal circuits.
      ,
      • Nasca C.
      • Bigio B.
      • Zelli D.
      • de Angelis P.
      • Lau T.
      • Okamoto M.
      • et al.
      Role of the astroglial glutamate exchanger xCT in ventral hippocampus in resilience to stress.
      ,
      • Yuen E.Y.
      • Wei J.
      • Liu W.
      • Zhong P.
      • Li X.
      • Yan Z.
      Repeated stress causes cognitive impairment by suppressing glutamate receptor expression and function in prefrontal cortex.
      ,
      • Zink M.
      • Vollmayr B.
      • Gebicke-Haerter P.J.
      • Henn F.A.
      Reduced expression of glutamate transporters vGluT1, EAAT2 and EAAT4 in learned helpless rats, an animal model of depression.
      ). Exploring this concept with multiomic approaches could reveal important insights into the adaptive—and maladaptive—changes triggered by acute and chronic stress exposures and could help to differentiate homeostatic processes from those involving allostatic load. In addition, a more systematic and thorough integration of stress research with the well-established field of activity-dependent transcription could prove to be beneficial (
      • Fernandez-Albert J.
      • Lipinski M.
      • Lopez-Cascales M.T.
      • Rowley M.J.
      • Martin-Gonzalez A.M.
      • del Blanco B.
      • et al.
      Immediate and deferred epigenomic signatures of in vivo neuronal activation in mouse hippocampus.
      ,
      • Su Y.
      • Shin J.
      • Zhong C.
      • Wang S.
      • Roychowdhury P.
      • Lim J.
      • et al.
      Neuronal activity modifies the chromatin accessibility landscape in the adult brain.
      ).

      Single-Cell Transcriptomics

      A major gap between the observed changes in gene expression and a mechanistic understanding of the stress response is the lack of cell type specificity of most -omic data. Stress can selectively affect inhibitory neurons and alter the excitation–inhibition balance (
      • Jacobson-Pick S.
      • Richter-Levin G.
      Short- and long-term effects of juvenile stressor exposure on the expression of GABA.
      ,
      • Hadad-Ophir O.
      • Albrecht A.
      • Stork O.
      • Richter-Levin G.
      Amygdala activation and GABAergic gene expression in hippocampal sub-regions at the interplay of stress and spatial learning.
      ,
      • Ritov G.
      • Boltyansky B.
      • Richter-Levin G.
      A novel approach to PTSD modeling in rats reveals alternating patterns of limbic activity in different types of stress reaction.
      ,
      • Tzanoulinou S.
      • Riccio O.
      • De Boer M.W.
      • Sandi C.
      Peripubertal stress-induced behavioral changes are associated with altered expression of genes involved in excitation and inhibition in the amygdala.
      ). For example, the glutamate decarboxylases Gad65 and Gad67 were upregulated in inhibitory hippocampal neurons between 1 and 2 hours after restraint stress (
      • Bowers G.
      • Cullinan W.E.
      • Herman J.P.
      Region-specific regulation of glutamic acid decarboxylase (GAD) mRNA expression in central stress circuits.
      ), and the cystine/glutamate antiporter Scl7a11 was reduced specifically in astrocytes of the ventral hippocampus (
      • Nasca C.
      • Bigio B.
      • Zelli D.
      • de Angelis P.
      • Lau T.
      • Okamoto M.
      • et al.
      Role of the astroglial glutamate exchanger xCT in ventral hippocampus in resilience to stress.
      ). Importantly, the heterogeneity of cell types is far more complex than previously recognized, and even within–cell type heterogeneity in the hippocampus seems to be the norm rather than the exception (
      • Cembrowski M.S.
      • Bachman J.L.
      • Wang L.
      • Sugino K.
      • Shields B.C.
      • Spruston N.
      Spatial gene-expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons.
      ,
      • Cembrowski M.S.
      • Phillips M.G.
      • DiLisio S.F.
      • Shields B.C.
      • Winnubst J.
      • Chandrashekar J.
      • et al.
      Dissociable structural and functional hippocampal outputs via distinct subiculum cell classes.
      ,
      • Cembrowski M.S.
      • Spruston N.
      Heterogeneity within classical cell types is the rule: Lessons from hippocampal pyramidal neurons.
      ). Accordingly, stress will have different effects not only on different cell types but likely also on different subclasses of cells depending on their intrinsic genetic makeup, connectivity, or location (
      • Cembrowski M.S.
      • Wang L.
      • Sugino K.
      • Shields B.C.
      • Spruston N.
      Hipposeq: A comprehensive RNA-seq database of gene expression in hippocampal principal neurons.
      ,
      • Erwin S.R.
      • Sun W.
      • Copeland M.
      • Lindo S.
      • Spruston N.
      • Cembrowski M.S.
      A sparse, spatially biased subtype of mature granule cell dominates recruitment in hippocampal-associated behaviors.
      ). Owing to technical and bioinformatic advances, single-cell RNA sequencing (scRNA-seq) now allows quantitative comparisons of gene expression between experimental groups within cell types (
      • Crowell H.
      • Soneson C.
      • Germain P.-L.
      • Calini D.
      • Collin L.
      • Raposo C.
      • et al.
      On the discovery of subpopulation-specific state transitions from multi-sample multi-condition single-cell RNA sequencing data.
      ). However, scRNA-seq comes with two major challenges. First, the highly interconnected and tightly packed brain tissue is difficult to dissociate into intact and viable cells, which are required to gain high-quality scRNA-seq data. Second, commonly used tissue dissociation protocols can cause artificial upregulation of IEGs. Available plate-based manual dissociation protocols are laborious, require experience and carefully controlled experiments, and do not scale well (
      • Erwin S.R.
      • Sun W.
      • Copeland M.
      • Lindo S.
      • Spruston N.
      • Cembrowski M.S.
      A sparse, spatially biased subtype of mature granule cell dominates recruitment in hippocampal-associated behaviors.
      ,
      • Hempel C.M.
      • Sugino K.
      • Nelson S.B.
      A manual method for the purification of fluorescently labeled neurons from the mammalian brain.
      ). One option to circumvent dissociation-induced IEG expression is to perform tissue dissociation on ice using a cold-active protease (
      • Adam M.
      • Potter A.S.
      • Potter S.S.
      Psychrophilic proteases dramatically reduce single-cell RNA-seq artifacts: A molecular atlas of kidney development.
      ), but this has not yet been tested in brain tissue (
      • Denisenko E.
      • Guo B.B.
      • Jones M.
      • Hou R.
      • De Kock L.
      • Lassmann T.
      • et al.
      Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows.
      ,
      • O’Flanagan C.H.
      • Campbell K.R.
      • Zhang A.W.
      • Kabeer F.
      • Lim J.L.P.
      • Biele J.
      • et al.
      Dissociation of solid tumor tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses.
      ). Similarly, Wu et al. (
      • Wu Y.E.
      • Pan L.
      • Zuo Y.
      • Li X.
      • Hong W.
      Detecting activated cell populations using single-cell RNA-seq.
      ) developed an scRNA-seq technique that uses a milder dissociation protocol (at lower temperature and using a transcription inhibitor) to characterize the transcriptional response of amygdala cells to restraint stress, novelty (odor), and pentylenetetrazol-induced seizures. Although to our knowledge their results constitute the only available scRNA-seq dataset after acute stress, relatively little attention was given to the stress condition, most likely owing to its high variability and the small effects relative to seizures. A limitation of this dataset is that a considerable proportion of the cells show high expression of both glial and neuronal markers (see Supplemental Methods), which could be due, for instance, to an incomplete dissociation. Excluding those cells, we reanalyzed the data, aggregated by broad cell classes, and compared them with the hippocampal stress signature (Figure 3C). Plotting genes that are altered both in the hippocampus bulk RNA sequencing and in at least one cell type (in response to at least one treatment) reveals a relatively high concordance between single-cell and bulk signatures despite the differences in time point and brain region profiled. This suggests that bulk sequencing can be sufficiently sensitive to detect changes even from relatively rare cell populations such as endothelial cells. Curiously, neurons were by far the least correlated with the bulk signature, suggesting that the majority of gene expression changes might occur in glial and endothelial cells. This hypothesis warrants replication and validation using a technically refined approach.
      An alternative to scRNA-seq is single-nucleus RNA sequencing, which allows higher throughput sample processing because frozen tissue is used for fast mechanical disruption into single-nucleus suspension on ice (
      • Grindberg R.V.
      • Yee-Greenbaum J.L.
      • McConnell M.J.
      • Novotny M.
      • O’Shaughnessy A.L.
      • Lambert G.M.
      • et al.
      RNA-sequencing from single nuclei.
      ). Despite single-nucleus RNA sequencing results being dominated by nascent transcripts and missing non-nuclear RNAs, nuclear sequencing yields accurate expression of the majority of marker genes to confidently identify cellular subpopulations (
      • Lake B.B.
      • Codeluppi S.
      • Yung Y.C.
      • Gao D.
      • Chun J.
      • Kharchenko P.V.
      • et al.
      A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA.
      ,
      • Bakken T.E.
      • Hodge R.D.
      • Miller J.A.
      • Yao Z.
      • Nguyen T.N.
      • Aevermann B.
      • et al.
      Single-nucleus and single-cell transcriptomes compared in matched cortical cell types.
      ,
      • Ding J.
      • Adiconis X.
      • Simmons S.K.
      • Kowalczyk M.S.
      • Hession C.C.
      • Marjanovic N.D.
      • et al.
      Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.
      ). The goal of providing a detailed overview of the dynamic molecular response to various acute stressors at single-cell resolution in different brain regions is currently still prohibitively expensive, yet this is undoubtedly the direction in which the field will move by exploiting advances in scRNA-seq and spatial transcriptomics (
      • Ortiz C.
      • Navarro J.F.
      • Jurek A.
      • Märtin A.
      • Lundeberg J.
      • Meletis K.
      Molecular atlas of the adult mouse brain.
      ).

      Translatome and Proteome

      Not all transcriptional changes will affect the expression level of the corresponding proteins, and notably several stress-induced signals—such as the MAPK–ERK cascade—can regulate translation via the mTOR (mechanistic target of rapamycin) pathway (
      • Roux P.P.
      • Topisirovic I.
      Signaling pathways involved in the regulation of mRNA translation.
      ). A direct way to assess whether stress changes protein levels is by interrogating the proteome. There are few studies addressing the effects of acute stress on the proteome, detecting only very few protein changes in the hippocampus 24 hours after stress (
      • Floriou-Servou A.
      • von Ziegler L.
      • Stalder L.
      • Sturman O.
      • Privitera M.
      • Rassi A.
      • et al.
      Distinct proteomic, transcriptomic, and epigenetic stress responses in dorsal and ventral hippocampus.
      ) and in the basolateral amygdala 30 days after stress (
      • Sillivan S.E.
      • Jones M.E.
      • Jamieson S.
      • Rumbaugh G.
      • Miller C.A.
      Bioinformatic analysis of long-lasting transcriptional and translational changes in the basolateral amygdala following acute stress.
      ). It remains unclear whether the time points chosen for these analyses or the coverage and sensitivity provided by the proteomic technology are responsible for the low number of significantly altered proteins. Alternatively, translational inhibition is known to occur in response to cellular stress, likely to preserve cellular energy resources, which could explain these unexpected results (
      • Pakos-Zebrucka K.
      • Koryga I.
      • Mnich K.
      • Ljujic M.
      • Samali A.
      • Gorman A.M.
      The integrated stress response.
      ). In short, the temporal dynamics of the proteomic changes and their relation to transcriptional changes in response to acute stress remain largely unexplored.
      Given the greater sensitivity of sequencing-based techniques over mass spectrometry, there is increasing interest in the analysis of the messenger RNAs that are actively translated, namely the translatome (
      • King H.A.
      • Gerber A.P.
      Translatome profiling: Methods for genome-scale analysis of mRNA translation.
      ). Beyond sensitivity, ribosomal tags expressed in transgenic mice under specific promoters allow profiling of the actively translated (ribosome-associated) RNA in select subpopulations of cells. This has already been used to investigate the stress-induced effects on the translatome of hippocampal CA3 pyramidal neurons (
      • Gray J.D.
      • Rubin T.G.
      • Kogan J.F.
      • Marrocco J.
      • Weidmann J.
      • Lindkvist S.
      • et al.
      Translational profiling of stress-induced neuroplasticity in the CA3 pyramidal neurons of BDNF Val66Met mice.
      ,
      • Marrocco J.
      • Petty G.H.
      • Ríos M.B.
      • Gray J.D.
      • Kogan J.F.
      • Waters E.M.
      • et al.
      A sexually dimorphic pre-stressed translational signature in CA3 pyramidal neurons of BDNF Val66Met mice.
      ,
      • Marrocco J.
      • Gray J.D.
      • Kogan J.F.
      • Einhorn N.R.
      • O’Cinneide E.M.
      • Rubin T.G.
      • et al.
      Early life stress restricts translational reactivity in CA3 neurons associated with altered stress responses in adulthood.
      ). However, a recent reanalysis revealed that these studies were underpowered and yielded vastly overestimated effects and that increased gene translation after acute stress is mostly restricted to well-known IEGs (
      • von Ziegler L.
      • Bohacek J.
      • Germain P.-L.
      Translatomic profiling of the acute stress response: It’s a TRAP.
      ). Translatome profiling in astrocytes from the somatosensory cortex revealed robust translational changes 90 minutes after acute restraint stress (
      • Murphy-Royal C.
      • Johnston A.D.
      • Boyce A.K.J.
      • Diaz-Castro B.
      • Institoris A.
      • Peringod G.
      • et al.
      Stress gates an astrocytic energy reservoir to impair synaptic plasticity.
      ). Combined with the previous comparison of scRNA-seq data (Figure 3D), these data remind us to look beyond neurons as profound stress-induced changes occur in glial and endothelial cells.

      Outlook and Conclusions

      Much of the healthy molecular response to acute stressors reflects a tightly choreographed dance among neurons, endothelial cells, and glial cells, providing energy substrates for increased neuronal activity while keeping excessive excitability (seizures) in check. We are only beginning to understand how lifestyle factors can affect energy metabolism and thus influence health through mechanisms that involve glial cells and mitochondria (
      • Larrieu T.
      • Cherix A.
      • Duque A.
      • Rodrigues J.
      • Lei H.
      • Gruetter R.
      • Sandi C.
      Hierarchical status predicts behavioral vulnerability and nucleus accumbens metabolic profile following chronic social defeat stress.
      ,
      • Siracusa R.
      • Fusco R.
      • Cuzzocrea S.
      Astrocytes: Role and functions in brain pathologies.
      ). We argue here that detailed knowledge of the molecular response to acute stress will help to understand the effects of chronic stress and individual differences in stress resilience and vulnerability. To achieve this, we suggest three approaches: 1) a detailed characterization of the acute stress response across all molecular levels (see Figure 2) over time to catalogue the peak molecular stress response and its termination, 2) a multiomic comparison of different acute stressors to identify molecular breaking points where some stressors overwhelm the ability to cope and lead to allostatic load, and 3) a time-course experiment where repeated exposure to acute stressors is used to characterize the molecular transition from acute to chronic stress. For all these experiments, a major challenge is to integrate the resulting datasets across scales, stressors, and time points. This challenge only grows, as new multiomic methods rapidly emerge and reveal, for example, that stress can change the chromatin landscape (
      • Mifsud K.R.
      • Reul J.M.H.M.
      Mineralocorticoid and glucocorticoid receptor-mediated control of genomic responses to stress in the brain.
      ,
      • Papale L.A.
      • Li S.
      • Madrid A.
      • Zhang Q.
      • Chen L.
      • Chopra P.
      • et al.
      Sex-specific hippocampal 5-hydroxymethylcytosine is disrupted in response to acute stress.
      ,
      • Hunter R.G.
      • Murakami G.
      • Dewell S.
      • Seligsohn M.
      • Baker M.E.R.
      • Datson N.A.
      • et al.
      Acute stress and hippocampal histone H3 lysine 9 trimethylation, a retrotransposon silencing response.
      ) and induce changes in the epitranscriptome (
      • Engel M.
      • Eggert C.
      • Kaplick P.M.
      • Eder M.
      • Röh S.
      • Tietze L.
      • et al.
      The role of m6A/m-RNA methylation in stress response regulation.
      ), metabolome, lipidome (
      • Hamilton P.J.
      • Chen E.Y.
      • Tolstikov V.
      • Peña C.J.
      • Picone J.A.
      • Shah P.
      • et al.
      Chronic stress and antidepressant treatment alter purine metabolism and beta oxidation within mouse brain and serum.
      ,
      • Steenwyk G.
      • Gapp K.
      • Jawaid A.
      • Germain P.
      • Manuella F.
      • Tanwar D.K.
      • et al.
      Involvement of circulating factors in the transmission of paternal experiences through the germline.
      ), and microbiome (
      • Foster J.A.
      • Rinaman L.
      • Cryan J.F.
      Stress & the gut-brain axis: Regulation by the microbiome.
      ). Although bioinformatically demanding, useful examples of complex data integration have emerged in other neuroscience fields (
      • Fernandez-Albert J.
      • Lipinski M.
      • Lopez-Cascales M.T.
      • Rowley M.J.
      • Martin-Gonzalez A.M.
      • del Blanco B.
      • et al.
      Immediate and deferred epigenomic signatures of in vivo neuronal activation in mouse hippocampus.
      ,
      • Su Y.
      • Shin J.
      • Zhong C.
      • Wang S.
      • Roychowdhury P.
      • Lim J.
      • et al.
      Neuronal activity modifies the chromatin accessibility landscape in the adult brain.
      ). In addition, we caution that novel techniques be used rigorously because underpowered -omic datasets can easily produce misleading information. Despite these hurdles, the -omic revolution offers the tools to study the acute stress response with the breadth and resolution necessary for understanding such a complex and dynamic system.

      Acknowledgments and Disclosures

      The lab of JB is funded by ETH Zürich , ETH Project Grant No. ETH-20 19-1 , the Swiss National Science Foundation (Grant No. 310030_172889/1 ), the Botnar Foundation , and the Swiss 3R Competence Center . The position of P-LG is co-funded by Isabelle Mansuy (Brain Research Institute, University of Zürich, and Institute of Neuroscience, ETH Zürich), Gerhard Schratt and Johannes Bohacek (Institute of Neuroscience, ETH Zürich), and Mark Robinson (Institute of Molecular Life Sciences, University of Zürich).
      We thank Katharina Gapp for thoughtful comments on the manuscript and Yuan-Chen Tsai for valuable input and help in creating Figure 2. We thank the anonymous reviewers for their constructive feedback. We apologize to all the authors whose work we were not able to discuss in this review owing to space restrictions.
      The authors report no biomedical financial interests or potential conflicts of interest.

      Supplementary Material

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