Noradrenaline release from the locus coeruleus shapes stress-induced hippocampal gene expression.

Exposure to an acute stressor triggers a complex cascade of neurochemical events in the brain. However, deciphering their individual impact on stress-induced molecular changes remains a major challenge. Here, we combine RNA sequencing with selective pharmacological, chemogenetic, and optogenetic manipulations to isolate the contribution of the locus coeruleus-noradrenaline (LC-NA) system to the acute stress response in mice. We reveal that NA release during stress exposure regulates a large and reproducible set of genes in the dorsal and ventral hippocampus via ß-adrenergic receptors. For a smaller subset of these genes, we show that NA release triggered by LC stimulation is sufficient to mimic the stress-induced transcriptional response. We observe these effects in both sexes, and independent of the pattern and frequency of LC activation. Using a retrograde optogenetic approach, we demonstrate that hippocampus-projecting LC neurons directly regulate hippocampal gene expression. Overall, a highly selective set of astrocyte-enriched genes emerges as key targets of LC-NA activation, most prominently several subunits of protein phosphatase 1 (Ppp1r3c, Ppp1r3d, Ppp1r3g) and type II iodothyronine deiodinase (Dio2). These results highlight the importance of astrocytic energy metabolism and thyroid hormone signaling in LC-mediated hippocampal function and offer new molecular targets for understanding how NA impacts brain function in health and disease.

The vascular gene Apold1 is dispensable for normal development but controls angiogenesis under pathological conditions.

The molecular mechanisms of angiogenesis have been intensely studied, but many genes that control endothelial behavior and fate still need to be described. Here, we characterize the role of Apold1 (Apolipoprotein L domain containing 1) in angiogenesis in vivo and in vitro. Single-cell analyses reveal that - across tissues - the expression of Apold1 is restricted to the vasculature and that Apold1 expression in endothelial cells (ECs) is highly sensitive to environmental factors. Using Apold1-/- mice, we find that Apold1 is dispensable for development and does not affect postnatal retinal angiogenesis nor alters the vascular network in adult brain and muscle. However, when exposed to ischemic conditions following photothrombotic stroke as well as femoral artery ligation, Apold1-/- mice display dramatic impairments in recovery and revascularization. We also find that human tumor endothelial cells express strikingly higher levels of Apold1 and that Apold1 deletion in mice stunts the growth of subcutaneous B16 melanoma tumors, which have smaller and poorly perfused vessels. Mechanistically, Apold1 is activated in ECs upon growth factor stimulation as well as in hypoxia, and Apold1 intrinsically controls EC proliferation but not migration. Our data demonstrate that Apold1 is a key regulator of angiogenesis in pathological settings, whereas it does not affect developmental angiogenesis, thus making it a promising candidate for clinical investigation.

Resolving equivocal gain modulation of corticospinal excitability.

The ratio between the input and output of neuronal populations, usually referred to as gain modulation, is rhythmically modulated along the oscillatory cycle. Previous research on spinal neurons, however, revealed contradictory findings: both uni- and bimodal patterns of increased responsiveness for synaptic input have been proposed for the oscillatory beta rhythm. In this study, we compared previous approaches of phase estimation directly on simulated data and empirically tested the corresponding predictions in healthy males and females. We applied single-pulse transcranial magnetic stimulation over the primary motor cortex at rest, and assessed the spinal output generated by this input. Specifically, the peak-to-peak amplitude of the motor evoked potential in the contralateral forearm was estimated as a function of the EMG phase at which the stimulus was applied. The findings indicated that human spinal neurons adhere to a unimodal pattern of increased responsiveness, and suggest that the rising phase of the upper beta band maximizes gain modulation. Importantly, a bimodal pattern of increased responsiveness was shown to result in an artifact during data analysis and filtering. This observation of invalid preprocessing could be generalized to other frequency bands (i.e., delta, theta, alpha, and gamma), different task conditions (i.e., voluntary muscle contraction), and EEG-based phase estimations. Appropriate analysis algorithms, such as broad-band filtering, enable us to accurately determine gain modulation of neuronal populations and to avoid erroneous phase estimations. This may facilitate novel phase-specific interventions for targeted neuromodulation.

Evaluation of signal analysis algorithms for ipsilateral motor-evoked potentials induced by transcranial magnetic stimulation.

Objective. Evaluating ipsilateral motor-evoked potentials (iMEP) induced by transcranial magnetic stimulation is challenging. In healthy adults, isometric contraction is necessary to facilitate iMEP induction; therefore, the signal may be masked by the concurrent muscle activity. Signal analysis algorithms for iMEP evaluation need to be benchmarked and evaluated.Approach. An open analysis toolbox for iMEP evaluation was implemented on the basis of 11 previously reported algorithms, which were all threshold based, and a new template-based method based on data-driven signal decomposition. The reliability and validity of these algorithms were evaluated with a dataset of 4244 iMEP from 55 healthy adults.Main results.iMEP estimation varies drastically between algorithms. Several algorithms exhibit high reliability, but some appear to be influenced by background activity of muscle preactivation. Especially in healthy subjects, template-based approaches might be more valid than threshold-based ones. Measurement of iMEP persistence requires algorithms that reject some trials as MEP negative. The stricter the algorithms reject trials, the less reliable they generally are. Our evaluation identifies an optimally strict and reliable algorithm.Significance.We show different benchmarks and propose application for different use cases.

Deep-learning based identification, tracking, pose estimation, and behavior classification of interacting primates and mice in complex environments.

The quantification of behaviors of interest from video data is commonly used to study brain function, the effects of pharmacological interventions, and genetic alterations. Existing approaches lack the capability to analyze the behavior of groups of animals in complex environments. We present a novel deep learning architecture for classifying individual and social animal behavior, even in complex environments directly from raw video frames, while requiring no intervention after initial human supervision. Our behavioral classifier is embedded in a pipeline (SIPEC) that performs segmentation, identification, pose-estimation, and classification of complex behavior, outperforming the state of the art. SIPEC successfully recognizes multiple behaviors of freely moving individual mice as well as socially interacting non-human primates in 3D, using data only from simple mono-vision cameras in home-cage setups.

Multiomic profiling of the acute stress response in the mouse hippocampus.

The acute stress response mobilizes energy to meet situational demands and re-establish homeostasis. However, the underlying molecular cascades are unclear. Here, we use a brief swim exposure to trigger an acute stress response in mice, which transiently increases anxiety, without leading to lasting maladaptive changes. Using multiomic profiling, such as proteomics, phospho-proteomics, bulk mRNA-, single-nuclei mRNA-, small RNA-, and TRAP-sequencing, we characterize the acute stress-induced molecular events in the mouse hippocampus over time. Our results show the complexity and specificity of the response to acute stress, highlighting both the widespread changes in protein phosphorylation and gene transcription, and tightly regulated protein translation. The observed molecular events resolve efficiently within four hours after initiation of stress. We include an interactive app to explore the data, providing a molecular resource that can help us understand how acute stress impacts brain function in response to stress.

Optogenetic activation of striatal D1R and D2R cells differentially engages downstream connected areas beyond the basal ganglia.

The basal ganglia (BG) are a group of subcortical nuclei responsible for motor and executive function. Central to BG function are striatal cells expressing D1 (D1R) and D2 (D2R) dopamine receptors. D1R and D2R cells are considered functional antagonists that facilitate voluntary movements and inhibit competing motor patterns, respectively. However, whether they maintain a uniform function across the striatum and what influence they exert outside the BG is unclear. Here, we address these questions by combining optogenetic activation of D1R and D2R cells in the mouse ventrolateral caudoputamen with fMRI. Striatal D1R/D2R stimulation evokes distinct activity within the BG-thalamocortical network and differentially engages cerebellar and prefrontal regions. Computational modeling of effective connectivity confirms that changes in D1R/D2R output drive functional relationships between these regions. Our results suggest a complex functional organization of striatal D1R/D2R cells and hint toward an interconnected fronto-BG-cerebellar network modulated by striatal D1R and D2R cells.

Chronic adolescent stress increases exploratory behavior but does not appear to change the acute stress response in adult male C57BL/6 mice.

Chronic stress exposure in adolescence can lead to a lasting change in stress responsiveness later in life and is associated with increased mental health issues in adulthood. Here we investigate whether the Chronic Social Instability (CSI) paradigm influences the behavioral and molecular responses to novel acute stressors in mice, and whether it alters physiological responses influenced by the noradrenergic system. Using large cohorts of mice, we show that CSI mice display a persistent increase in exploratory behaviors in the open field test alongside small but widespread transcriptional changes in the ventral hippocampus. However, both the transcriptomic and behavioral responses to novel acute stressors are indistinguishable between groups. In addition, the pupillometric response to a tail shock, known to be mediated by the noradrenergic system, remains unaltered in CSI mice. Ultra-high performance liquid chromatography analysis of monoaminergic neurotransmitter levels in the ventral hippocampus also shows no differences between control or CSI mice at baseline or in response to acute stress. We conclude that CSI exposure during adolescence leads to persistent changes in exploratory behavior and gene expression in the hippocampus, but it does not alter the response to acute stress in adulthood and is unlikely to alter the function of the noradrenergic system.

Pervasive compartment-specific regulation of gene expression during homeostatic synaptic scaling.

Synaptic scaling is a form of homeostatic plasticity which allows neurons to adjust their action potential firing rate in response to chronic alterations in neural activity. Synaptic scaling requires profound changes in gene expression, but the relative contribution of local and cell-wide mechanisms is controversial. Here we perform a comprehensive multi-omics characterization of the somatic and process compartments of primary rat hippocampal neurons during synaptic scaling. We uncover both highly compartment-specific and correlating changes in the neuronal transcriptome and proteome. Whereas downregulation of crucial regulators of neuronal excitability occurs primarily in the somatic compartment, structural components of excitatory postsynapses are mostly downregulated in processes. Local inhibition of protein synthesis in processes during scaling is confirmed for candidate synaptic proteins. Motif analysis further suggests an important role for trans-acting post-transcriptional regulators, including RNA-binding proteins and microRNAs, in the local regulation of the corresponding mRNAs. Altogether, our study indicates that, during synaptic scaling, compartmentalized gene expression changes might co-exist with neuron-wide mechanisms to allow synaptic computation and homeostasis.

FGFR3 overexpression is a useful detection tool for FGFR3 fusions and sequence variations in glioma.

BACKGROUND: Fibroblast growth factor receptor (FGFR) inhibitors are currently used in clinical development. A subset of glioblastomas carries gene fusion of FGFR3 and transforming acidic coiled-coil protein 3. The prevalence of other FGFR3 alterations in glioma is currently unclear. METHODS: We performed RT-PCR in 101 glioblastoma samples to detect FGFR3-TACC3 fusions ("RT-PCR cohort") and correlated results with FGFR3 immunohistochemistry (IHC). Further, we applied FGFR3 IHC in 552 tissue microarray glioma samples ("TMA cohort") and validated these results in two external cohorts with 319 patients. Gene panel sequencing was carried out in 88 samples ("NGS cohort") to identify other possible FGFR3 alterations. Molecular modeling was performed on newly detected mutations. RESULTS: In the "RT-PCR cohort," we identified FGFR3-TACC3 fusions in 2/101 glioblastomas. Positive IHC staining was observed in 73/1024 tumor samples of which 10 were strongly positive. In the "NGS cohort," we identified FGFR3 fusions in 9/88 cases, FGFR3 amplification in 2/88 cases, and FGFR3 gene mutations in 7/88 cases in targeted sequencing. All FGFR3 fusions and amplifications and a novel FGFR3 K649R missense mutation were associated with FGFR3 overexpression (sensitivity and specificity of 93% and 95%, respectively, at cutoff IHC score > 7). Modeling of these data indicated that Tyr647, a residue phosphorylated as a part of FGFR3 activation, is affected by the K649R mutation. CONCLUSIONS: FGFR3 IHC is a useful screening tool for the detection of FGFR3 alterations and could be included in the workflow for isocitrate dehydrogenase (IDH) wild-type glioma diagnostics. Samples with positive FGFR3 staining could then be selected for NGS-based diagnostic tools.

The Acute Stress Response in the Multiomic Era.

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.

Big behavior: challenges and opportunities in a new era of deep behavior profiling.

The assessment of rodent behavior forms a cornerstone of preclinical assessment in neuroscience research. Nonetheless, the true and almost limitless potential of behavioral analysis has been inaccessible to scientists until very recently. Now, in the age of machine vision and deep learning, it is possible to extract and quantify almost infinite numbers of behavioral variables, to break behaviors down into subcategories and even into small behavioral units, syllables or motifs. However, the rapidly growing field of behavioral neuroethology is experiencing birthing pains. The community has not yet consolidated its methods, and new algorithms transfer poorly between labs. Benchmarking experiments as well as the large, well-annotated behavior datasets required are missing. Meanwhile, big data problems have started arising and we currently lack platforms for sharing large datasets-akin to sequencing repositories in genomics. Additionally, the average behavioral research lab does not have access to the latest tools to extract and analyze behavior, as their implementation requires advanced computational skills. Even so, the field is brimming with excitement and boundless opportunity. This review aims to highlight the potential of recent developments in the field of behavioral analysis, whilst trying to guide a consensus on practical issues concerning data collection and data sharing.

Deep learning-based behavioral analysis reaches human accuracy and is capable of outperforming commercial solutions.

To study brain function, preclinical research heavily relies on animal monitoring and the subsequent analyses of behavior. Commercial platforms have enabled semi high-throughput behavioral analyses by automating animal tracking, yet they poorly recognize ethologically relevant behaviors and lack the flexibility to be employed in variable testing environments. Critical advances based on deep-learning and machine vision over the last couple of years now enable markerless tracking of individual body parts of freely moving rodents with high precision. Here, we compare the performance of commercially available platforms (EthoVision XT14, Noldus; TSE Multi-Conditioning System, TSE Systems) to cross-verified human annotation. We provide a set of videos-carefully annotated by several human raters-of three widely used behavioral tests (open field test, elevated plus maze, forced swim test). Using these data, we then deployed the pose estimation software DeepLabCut to extract skeletal mouse representations. Using simple post-analyses, we were able to track animals based on their skeletal representation in a range of classic behavioral tests at similar or greater accuracy than commercial behavioral tracking systems. We then developed supervised machine learning classifiers that integrate the skeletal representation with the manual annotations. This new combined approach allows us to score ethologically relevant behaviors with similar accuracy to humans, the current gold standard, while outperforming commercial solutions. Finally, we show that the resulting machine learning approach eliminates variation both within and between human annotators. In summary, our approach helps to improve the quality and accuracy of behavioral data, while outperforming commercial systems at a fraction of the cost.

A complete pupillometry toolbox for real-time monitoring of locus coeruleus activity in rodents.

The locus coeruleus (LC) is a region in the brainstem that produces noradrenaline and is involved in both normal and pathological brain function. Pupillometry, the measurement of pupil diameter, provides a powerful readout of LC activity in rodents, primates and humans. The protocol detailed here describes a miniaturized setup that can screen LC activity in rodents in real-time and can be established within 1-2 d. Using low-cost Raspberry Pi computers and cameras, the complete custom-built system costs only ~300 euros, is compatible with stereotaxic surgery frames and seamlessly integrates into complex experimental setups. Tools for pupil tracking and a user-friendly Pupillometry App allow quantification, analysis and visualization of pupil size. Pupillometry can discriminate between different, physiologically relevant firing patterns of the LC and can accurately report LC activation as measured by noradrenaline turnover. Pupillometry provides a rapid, non-invasive readout that can be used to verify accurate placement of electrodes/fibers in vivo, thus allowing decisions about the inclusion/exclusion of individual animals before experiments begin.

Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation.

The locus coeruleus (LC) supplies norepinephrine (NE) to the entire forebrain and regulates many fundamental brain functions. Studies in humans have suggested that strong LC activation might shift network connectivity to favor salience processing. To causally test this hypothesis, we use a mouse model to study the effect of LC stimulation on large-scale functional connectivity by combining chemogenetic activation of the LC with resting-state fMRI, an approach we term "chemo-connectomics." We show that LC activation rapidly interrupts ongoing behavior and strongly increases brain-wide connectivity, with the most profound effects in the salience and amygdala networks. Functional connectivity changes strongly correlate with transcript levels of alpha-1 and beta-1 adrenergic receptors across the brain, and functional network connectivity correlates with NE turnover within select brain regions. We propose that these changes in large-scale network connectivity are critical for optimizing neural processing in the context of increased vigilance and threat detection.

Combined endogenous and exogenous disinhibition of intracortical circuits augments plasticity induction in the human motor cortex.

BACKGROUND: Motor imagery (MI) engages cortical areas in the human brain similar to motor practice. Corticospinal excitability (CSE) is facilitated during but not after MI practice. We hypothesized that lasting CSE changes could be achieved by associatively pairing this endogenous modulation with exogenous stimulation of the same intracortical circuits. METHODS: We combined MI with a disinhibition protocol (DIS) targeting intracortical circuits by paired-pulse repetitive transcranial magnetic stimulation in one main and three subsequent experiments. The follow-up experiments were applied to increase effects, e.g., by individualizing inter-stimulus intervals, adding neuromuscular stimulation and expanding the intervention period. CSE was captured during (online) and after (offline) the interventions via input-output changes and cortical maps of motor evoked potentials. A total of 35 healthy subjects (mean age 26.1 ±â€¯2.6 years, 20 females) participated in this study. RESULTS: A short intervention (48 stimuli within ∼90s) increased CSE. This plasticity developed rapidly, was associative (with MIon, but not MIoff or REST) and persisted beyond the intervention period. Follow-up experiments revealed the relevance of individualizing inter-stimulus intervals and of consistent inter-burst periods for online and offline effects, respectively. Expanding this combined MI/DIS intervention to 480 stimuli amplified the sustainability of CSE changes. When concurrent neuromuscular electrical stimulation was applied, the plasticity induction was cancelled. CONCLUSIONS: This novel associative stimulation protocol augmented plasticity induction in the human motor cortex within a remarkably short period of time and in the absence of active movements. The combination of endogenous and exogenous disinhibition of intracortical circuits may provide a therapeutic backdoor when active movements are no longer possible, e.g., for hand paralysis after stroke.

Distinct Proteomic, Transcriptomic, and Epigenetic Stress Responses in Dorsal and Ventral Hippocampus.

BACKGROUND: Acutely stressful experiences can trigger neuropsychiatric disorders and impair cognitive processes by altering hippocampal function. Although the intrinsic organization of the hippocampus is highly conserved throughout its long dorsal-ventral axis, the dorsal (anterior) hippocampus mediates spatial navigation and memory formation, whereas the ventral (posterior) hippocampus is involved in emotion regulation. To understand the molecular consequences of stress, detailed genome-wide screens are necessary and need to distinguish between dorsal and ventral hippocampal regions. While transcriptomic screens have become a mainstay in basic and clinical research, proteomic methods are rapidly evolving and hold even greater promise to reveal biologically and clinically relevant biomarkers. METHODS: Here, we provide the first combined transcriptomic (RNA sequencing) and proteomic (sequential window acquisition of all theoretical mass spectra [SWATH-MS]) profiling of dorsal and ventral hippocampus in mice. We used three different acute stressors (novelty, swim, and restraint) to assess the impact of stress on both regions. RESULTS: We demonstrated that both hippocampal regions display radically distinct molecular responses and that the ventral hippocampus is particularly sensitive to the effects of stress. Separately analyzing these structures greatly increased the sensitivity to detect stress-induced changes. For example, protein interaction cluster analyses revealed a stress-responsive epigenetic network around histone demethylase Kdm6b restricted to the ventral hippocampus, and acute stress reduced methylation of its enzymatic target H3K27me3. Selective Kdm6b knockdown in the ventral hippocampus led to behavioral hyperactivity/hyperresponsiveness. CONCLUSIONS: These findings underscore the importance of considering dorsal and ventral hippocampus separately when conducting high-throughput molecular analyses, which has important implications for fundamental research as well as clinical studies.

Subregion-Specific Proteomic Signature in the Hippocampus for Recognition Processes in Adult Mice.

The hippocampal formation is a brain structure essential for higher-order cognitive functions. It has a complex anatomical organization and cellular composition, and hippocampal subregions have different properties and functional roles. In this study, we used SWATH-MS to determine whether the proteomes of hippocampus areas CA1 and CA3 can explain the commonalities or specificities of these subregions in basal conditions and after recognition memory. We show that the proteomes of areas CA1 and CA3 are largely different in basal conditions and that differential changes and dynamics in protein expression are induced in these areas after recognition of an object or object location. While changes are consistent across both recognition paradigms in area CA1, they are not in area CA3, suggesting distinct proteomic responses in areas CA1 and CA3 for memory formation.