Multiomic profiling of the acute stress response in the mouse hippocampus

Ziegler, Lukas von; Floriou-Servou, Amalia; Waag, Rebecca; Gupta, Rebecca R Das; Sturman, Oliver; Gapp, Katharina; Maat, Christina A.; Kockmann, Tobias; Lin, Han-Yu; Duss, Sian N.; Privitera, Mattia; Hinte, Laura; Meyenn, Ferdinand von; Zeilhofer, Hanns Ulrich; Germain, Pierre-Luc; Bohacek, Johannes

doi:10.1038/s41467-022-29367-5

Cited by 51 publications

(80 citation statements)

References 121 publications

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“…Unpredictable chronic stress reduced the spontaneous running wheel activity of mice and maintained this reduction for up to 8 weeks [ 31 ]. Acute stress significantly reduced the movement distance and the central residence time of mice [ 32 ]. Our results also showed that the movement distance of mice decreased significantly with the extension of cold exposure at various temperatures.…”

Section: Discussionmentioning

confidence: 99%

Effect of Acute Cold Stress on Neuroethology in Mice and Establishment of Its Model

Liu

2022

Animals

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Cold environment is an inevitable stress source for humans and livestock in cold areas, which easily induce a cold stress response and then cause a series of abnormal changes in energy metabolism, neuroendocrine system, behavior and emotion. Homeostasis is maintained by the unified regulation of the autonomic nervous system, endocrine system, metabolism and behavior under cold exposure. Behavior is an indispensable part of the functional regulation of the body to respond to environmental changes. At present, the behavioral changes caused by cold exposure are unclear or even chaotic due to the difficulty of defining cold stress. Therefore, this study aims to systematically observe the changes in spontaneous movement, exploratory behavior and anxiety of mice under different intensity cold exposure and summarize the characteristics and behavior traits combined with relevant blood physiological indexes under corresponding conditions. Mice models of cold stress with different intensities were established (cold exposure gradients were 22 ℃, 16 ℃, 10 ℃ and 4 ℃, and time gradients of each temperature were 2 h, 4 h, 6 h, 8 h, 10 h and 12 h). After the corresponding cold exposure treatment, mice immediately carried out the open field test（OFT) and elevated plus maze test (PMT) to evaluate their spontaneous movement, exploratory behavior and anxiety. Subsequently, blood samples were collected and used for the determination of corticosterone (Cort), corticotropin-releasing hormone (CRH), epinephrine (E), norepinephrine (NE), dopamine (DA) and 5-hydroxytryptamine (5-HT) by enzyme-linked immunosorbent assay (ELISA). Spontaneous movement of mice increased under 22 ℃ cold exposure, but their exploration behavior did not significantly change, and their anxiety improved at the initial stage. The spontaneous movement and anxiety of mice increased in the initial stage and decreased in the later stage under cold exposure at 16, 10 and 4 ℃ and the exploratory behavior was inhibited. The hypothalamic–pituitary–adrenal (HPA) axis and locus coeruleus-noradrenergic (LC/NE) system were activated by cold stress and fluctuated with different intensities of cold exposure. Meanwhile, serum DA increased, and 5-HT was the opposite under different intensities of cold exposure. In conclusion, mild acute cold exposure promoted the spontaneous movement, increased exploratory behavior and improved anxiety. As the intensity of cold exposure increases, cold exposure had a negative effect on spontaneous movement, exploratory behavior and emotion. The physiological basis of these behavioral and emotional changes in mice under different intensity cold stimulation is the fluctuation of Cort, CRH, E, NE, DA and 5-HT.

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Section: Discussionmentioning

confidence: 99%

Effect of Acute Cold Stress on Neuroethology in Mice and Establishment of Its Model

Liu

2022

Animals

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“…Atherosclerosis (AS) is the main cause of coronary heart disease, cerebral infarction, and peripheral vascular disease ( 11 ). Chronic stress is prevalent in modern society and causes many kinds of mental diseases ( 12 , 13 ). The main results of this study were that renal SGLT1 expression was increased in the case of chronic stress alone, but not statistically significant ( P > 0.05).…”

Section: Discussionmentioning

confidence: 99%

SGLT1/2 as the potential biomarkers of renal damage under Apoe−/− and chronic stress via the BP neural network model and support vector machine

Wang

Meng

et al. 2022

Front. Cardiovasc. Med.

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BackgroundChronic stress (CS) could produce negative emotions. The molecular mechanism of SGLT1 and SGLT2 in kidney injury caused by chronic stress combined with atherosclerosis remains unclear.MethodsIn total, 60 C57BL/6J mice were randomly divided into four groups, namely, control (CON, n = 15), control diet + chronic stress (CON+CS, n = 15), high-fat diet + Apoe−/− (HF + Apoe−/−, n = 15), and high-fat diet + Apoe−/− + chronic stress (HF+Apoe−/− + CS, n = 15) groups. The elevated plus maze and open field tests were performed to examine the effect of chronic stress. The expression of SGLT1 and SGLT2 in the kidney was detected. The support vector machine (SVM) and back propagation (BP) neural network model were constructed to explore the predictive value of the expression of SGLT1/2 on the renal pathological changes. The receiver operating characteristic (ROC) curve analysis was used.ResultsA chronic stress model and atherosclerosis model were constructed successfully. Edema, broken reticular fiber, and increased glycogen in the kidney would be obvious in the HF + Apoe−/− + CS group. Compared with the CON group, the expression of SGLT1/2 in the kidney was upregulated in the HF + Apoe−/− + CS group (P < 0.05). There existed positive correlations among edema, glycogen, reticular fiber, expression of SGLT1/2 in the kidney. There were higher sensitivity and specificity of diagnosis of SGLT1/2 for edema, reticular fiber, and glycogen in the kidney. The result of the SVM and BP neural network model showed better predictive values of SGLT1 and SGLT2 for edema and glycogen in the kidney.ConclusionIn conclusion, SGLT1/2 might be potential biomarkers of renal damage under Apoe−/− and chronic stress, which provided a potential research direction for future related explorations into this mechanism.

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“…SimBA (Nilsson et al, 2020 ) uses features extracted from DLC or SLEAP pose data as input to a random forest classifier to label mouse behaviors, such as sniffing (social behavior; Dawson et al, 2022 ), freezing (fear conditioning; Hon et al, 2022 ), and pup retrieval (Winters et al, 2022 ). DLCAnalyzer (Sturman et al, 2020 ) also includes capabilities for supervised behavior classification and has been used to track head dips in the EPM (Grimm et al, 2021 ) and head angle in the open-field test (von Ziegler et al, 2022 ). MARS combines pose estimation and behavior classification capabilities and is suitable for multi-animal social behavior analysis (e.g., attack, mounting; Segalin et al, 2021 ).…”

Section: Machine Learning Approaches For Emotional Behavioral Analysismentioning

confidence: 99%

Using deep learning to study emotional behavior in rodent models

Kuo

Denman

Beacher

et al. 2022

Front. Behav. Neurosci.

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Quantifying emotional aspects of animal behavior (e.g., anxiety, social interactions, reward, and stress responses) is a major focus of neuroscience research. Because manual scoring of emotion-related behaviors is time-consuming and subjective, classical methods rely on easily quantified measures such as lever pressing or time spent in different zones of an apparatus (e.g., open vs. closed arms of an elevated plus maze). Recent advancements have made it easier to extract pose information from videos, and multiple approaches for extracting nuanced information about behavioral states from pose estimation data have been proposed. These include supervised, unsupervised, and self-supervised approaches, employing a variety of different model types. Representations of behavioral states derived from these methods can be correlated with recordings of neural activity to increase the scope of connections that can be drawn between the brain and behavior. In this mini review, we will discuss how deep learning techniques can be used in behavioral experiments and how different model architectures and training paradigms influence the type of representation that can be obtained.

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Multiomic profiling of the acute stress response in the mouse hippocampus

Cited by 51 publications

References 121 publications

Effect of Acute Cold Stress on Neuroethology in Mice and Establishment of Its Model

Effect of Acute Cold Stress on Neuroethology in Mice and Establishment of Its Model

SGLT1/2 as the potential biomarkers of renal damage under Apoe−/− and chronic stress via the BP neural network model and support vector machine

Using deep learning to study emotional behavior in rodent models

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