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.

Neuromodulation of striatal D1 cells shapes BOLD fluctuations in anatomically connected thalamic and cortical regions.

Understanding how the brain's macroscale dynamics are shaped by underlying microscale mechanisms is a key problem in neuroscience. In animal models, we can now investigate this relationship in unprecedented detail by directly manipulating cellular-level properties while measuring the whole-brain response using resting-state fMRI. Here, we focused on understanding how blood-oxygen-level-dependent (BOLD) dynamics, measured within a structurally well-defined striato-thalamo-cortical circuit in mice, are shaped by chemogenetically exciting or inhibiting D1 medium spiny neurons (MSNs) of the right dorsomedial caudate putamen (CPdm). We characterize changes in both the BOLD dynamics of individual cortical and subcortical brain areas, and patterns of inter-regional coupling (functional connectivity) between pairs of areas. Using a classification approach based on a large and diverse set of time-series properties, we found that CPdm neuromodulation alters BOLD dynamics within thalamic subregions that project back to dorsomedial striatum. In the cortex, changes in local dynamics were strongest in unimodal regions (which process information from a single sensory modality) and weakened along a hierarchical gradient towards transmodal regions. In contrast, a decrease in functional connectivity was observed only for cortico-striatal connections after D1 excitation. Our results show that targeted cellular-level manipulations affect local BOLD dynamics at the macroscale, such as by making BOLD dynamics more predictable over time by increasing its self-correlation structure. This contributes to ongoing attempts to understand the influence of structure-function relationships in shaping inter-regional communication at subcortical and cortical levels.

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.

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.

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.

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.

Exploratory rearing: a context- and stress-sensitive behavior recorded in the open-field test.

Stressful experiences are linked to anxiety disorders in humans. Similar effects are observed in rodent models, where anxiety is often measured in classic conflict tests such as the open-field test. Spontaneous rearing behavior, in which rodents stand on their hind legs to explore, can also be observed in this test yet is often ignored. We define two forms of rearing, supported rearing (in which the animal rears against the walls of the arena) and unsupported rearing (in which the animal rears without contacting the walls of the arena). Using an automated open-field test, we show that both rearing behaviors appear to be strongly context dependent and show clear sex differences, with females rearing less than males. We show that unsupported rearing is sensitive to acute stress, and is reduced under more averse testing conditions. Repeated testing and handling procedures lead to changes in several parameters over varying test sessions, yet unsupported rearing appears to be rather stable within a given animal. Rearing behaviors could therefore provide an additional measure of anxiety in rodents relevant for behavioral studies, as they appear to be highly sensitive to context and may be used in repeated testing designs.