Biology subjects

Sturman, O.

Publications and source records attributed to Sturman, O..

12 recordsLinked to original sources

bioRxiv2025

GrimACE: Automated, multimodal cage-side assessment of pain and well-being in mice

Pain and welfare monitoring is essential for ethical animal testing, but current cage-side assessments are qualitative and subjective. Here we present the GrimACE, the first fully standardised and automated cage-side monitoring tool for mice, the most widely used animals in research. The GrimACE uses computer vision to provide automated mouse grimace scale (MGS) assessment together with pose estimation in a dark, safe environment. We validated the system by analysing pain after brain surgeries (craniotomies) with head implants under two analgesia regimes. Human-expert and automated MGS scores showed very high correlation (Pearson's r=0.87). Both expert and automated scores revealed that a moderate increase in pain can be detected for up to 48 hours after surgeries, but that both a single dose of meloxicam (5mg/kg s.c.) or 3 doses of buprenorphine (0.1mg/kg) + meloxicam (5mg/kg s.c.) provide adequate and comparable pain management. Simultaneous pose estimation demonstrated that mice receiving buprenorphine + meloxicam showed increased movement 4h after surgery, indicative of hyperactivity, a well-known side-effect of opioid treatment. Significant weight loss was also detected in the buprenorphine + meloxicam treatment group compared to the meloxicam-only group. Additionally, detailed BehaviorFlow analysis and automated MGS scoring of control animals suggests that habituation to the GrimACE system is unnecessary, and that measurements can be repeated multiple times, ensuring standardised post-operative recovery monitoring.

neuroscience↗

bioRxiv2025

Distinct molecular mechanisms of stress habituation in the mouse hippocampus

Chronic stress is a risk factor for neuropsychiatric disorders, making the ability to adapt to repeated stress a crucial determinant of mental health. On a molecular level, it remains unclear whether repeated exposure to stress is characterized by habituation - a decreased responsiveness to the same stimulus - or by the emergence of new, adaptive responses. Here, we explore how the tightly regulated molecular response triggered by acute restraint stress becomes altered after repeated restraint exposure. Transcriptomic sampling of the mouse hippocampus at multiple time points revealed that repeated stress leads to widespread habituation, damping stress-induced gene expression of all stress-responsive genes. However, we find no evidence for the emergence of new response profiles or alterations in baseline gene expression. Using single-cell multi-omics, we show that these findings hold true across cell types, and we reveal cell type specific patterns of habituation. Transcriptomic and chromatin accessibility profiles identify two distinct mechanisms that contribute to the observed habituation patterns: an early cAMP-associated mechanism that is related to blunted transcription after chronic stress, and a late corticosterone-dependent mechanism that is linked to a shortened transcriptional response. These extensive data are integrated, along with our previous work, into an interactive app, providing a uniquely detailed molecular resource that characterizes the acute stress response and the process of habituation across the genome.

neuroscience↗

bioRxiv2023

Analysis of behavioral flow resolves latent phenotypes

The nuanced detection of rodent behavior in preclinical biomedical research is essential for understanding disease conditions, genetic phenotypes, and internal states. Recent advances in machine vision and artificial intelligence have popularized data-driven methods that segment complex animal behavior into clusters of behavioral motifs. However, despite the rapid progress, several challenges remain: Statistical power typically decreases due to multiple testing correction, poor transferability of clustering approaches across experiments limits practical applications, and individual differences in behavior are not considered. Here, we introduce "behavioral flow analysis" (BFA), which creates a single metric for all observed transitions between behavioral motifs. Then, we establish a "classifier-in-the-middle" approach to stabilize clusters and enable transferability of our analyses across datasets. Finally, we combine these approaches with dimensionality reduction techniques, enabling "behavioral flow fingerprinting" (BFF) for individual animal assessment. We validate our approaches across large behavioral datasets with a total of 443 open field recordings that we make publicly available, comparing various stress protocols with pharmacologic and brain-circuit interventions. Our analysis pipeline is compatible with a range of established clustering approaches, it increases statistical power compared to conventional techniques, and has strong reproducibility across experiments within and across laboratories. The efficient individual phenotyping allows us to classify stress-responsiveness and predict future behavior. This approach aligns with animal welfare regulations by reducing animal numbers, and enhancing information extracted from experimental animals

neuroscience↗

bioRxiv2023

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. We reveal that NA-release during stress exposure regulates a large and reproducible set of genes in the dorsal and ventral hippocampus via {beta}-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.

neuroscience↗

bioRxiv2022

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.

cell biology↗

bioRxiv2022

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

Understanding how the brains 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, are shaped by chemogenetically exciting or inhibiting D1 medium spiny neurons (MSNs) of the right dorsomedial striatum (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, the strongest changes in local dynamics were observed in unimodal regions, i.e., regions that process information from a single sensory modality, while changes in the local dynamics weakened along a putative cortical hierarchical gradient towards transmodal regions. In contrast, a decrease in functional connectivity was observed only for cortico-striatal connections after D1 excitation. Our results provide a comprehensive understanding of how targeted cellular-level manipulations affect local BOLD dynamics at the macroscale, including the role of a circuits structural characteristics and hierarchical cortical level in shaping those dynamics. These findings contribute to ongoing attempts to understand the influence of structure-function relationships in shaping inter-regional communication at subcortical and cortical levels.

neuroscience↗

bioRxiv2021

Chronic adolescent stress increases exploratory behavior but does not 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 in mice influences the behavioural and molecular responses to novel acute stressors, 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 behavioural 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 challenges in adulthood and is unlikely to alter the function of the noradrenergic system.

neuroscience↗

bioRxiv2021

Molecular roadmap of the healthy stress response in the mouse hippocampus

The acute stress response mobilizes energy to meet situational demands and re-establish homeostasis. However, little is known about the nature and dynamics of the underlying molecular cascades. We used a brief forced swim exposure to trigger a strong stress response in mice, which transiently increases anxiety, but does not lead to lasting maladaptive behavioral changes. Using multiomic profiling we characterize the stress-induced molecular events in the hippocampus over time, across molecular scales, and down to the level of cell types and single cells. Our results unveil the complexity and specificity of the healthy stress response, with widespread changes in protein phosphorylation and gene transcription, but tightly regulated protein translation. All observed molecular events resolve efficiently within 4 hours after initiation of stress. The data are accessible through an interactive web portal, creating an extensive molecular resource that will help understand how stress impacts brain function in health and disease.

neuroscience↗

bioRxiv2021

Optogenetic Activation of Striatal D1/D2 Medium Spiny Neurons Differentially Engages Downstream Connected Areas Beyond the Basal Ganglia

The basal ganglia (BG) are a group of subcortical nuclei responsible for motor control, motor learning and executive function. Central to BG function are striatal medium spiny neurons (MSNs) expressing D1 and D2 dopamine receptors. D1 and D2 MSNs are typically considered functional antagonists that facilitate voluntary movements and inhibit competing motor patterns, respectively. While their opposite role is well documented for certain sensorimotor loops of the BG-thalamocortical network, it is unclear whether MSNs maintain a uniform functional role across the striatum and which influence they exert on brain areas outside the BG. Here, we addressed these questions by combining optogenetic activation of D1 and D2 MSNs in the mouse ventrolateral caudoputamen (vl CPu) with whole-brain functional MRI (fMRI) recordings. Neuronal excitation of either cell population in the vl CPu evoked distinct activity patterns in key regions of the BG-thalamocortical network including the pallidum, thalamus and motor cortex. Importantly, we report that striatal D1 and D2 MSN stimulation differentially engaged cerebellar and prefrontal regions. We characterised these long-range interactions by computational modelling of effective connectivity and confirmed that changes in D1 / D2 output drive functional relationships between regions within and beyond the BG. These results suggest a more complex functional organization of MSNs across the striatum than previously anticipated and provide evidence for the existence of an interconnected fronto - BG - cerebellar network modulated by striatal D1 and D2 MSNs. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=129 HEIGHT=200 SRC="FIGDIR/small/436576v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@a18349org.highwire.dtl.DTLVardef@1b256faorg.highwire.dtl.DTLVardef@16c454aorg.highwire.dtl.DTLVardef@1392b23_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

SIPEC: the deep-learning Swiss knife for behavioral data analysis

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.

neuroscience↗

bioRxiv2020

Deep learning based behavioral analysis enables high precision rodent tracking and is capable of outperforming commercial solutions

To study brain function, preclinical research relies heavily on animal monitoring and the subsequent analyses of behavior. Commercial platforms have enabled semi high-throughput behavioral analyses by providing accurate tracking of animals, yet they often struggle with the analysis of ethologically relevant behaviors and lack the flexibility to adapt to variable testing environments. In the last couple of years, substantial advances in deep learning and machine vision have given researchers the ability to take behavioral analysis entirely into their own hands. Here, we directly compare the performance of commercially available platforms (Ethovision XT14, Noldus; TSE Multi Conditioning System, TSE Systems) to cross-verified human annotation. To this end, we provide a set of videos - carefully annotated by several human raters - of three widely used behavioral tests (open field, elevated plus maze, forced swim test). Using these data, we show that by combining deep learning-based motion tracking (DeepLabCut) with simple post-analysis, we can track animals in a range of classic behavioral tests at similar or even greater accuracy than commercial behavioral solutions. In addition, we integrate the tracking data from DeepLabCut with post analysis supervised machine learning approaches. This combination allows us to score ethologically relevant behaviors with similar accuracy to humans, the current gold standard, thus outperforming commercial solutions. Moreover, 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, outperforming commercial systems at a fraction of the cost.

animal behavior and cognition↗

bioRxiv2019

Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation

The locus coeruleus (LC) supplies norepinephrine (NE) to the entire forebrain, regulates many fundamental brain functions, and is implicated in several neuropsychiatric diseases. Although selective manipulation of the LC is not possible in humans, studies have suggested that strong LC activation might shift network connectivity to favor salience processing. To test this hypothesis, we use a mouse model to study the impact 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". LC activation rapidly interrupts ongoing behavior and strongly increases brain-wide connectivity, with the most profound effects in the salience and amygdala networks. We reveal a direct correlation between functional connectivity changes and transcript levels of alpha-1, alpha-2, and beta-1 adrenoceptors across the brain, and a positive correlation between NE turnover and functional connectivity within select brain regions. These results represent the first brain-wide functional connectivity mapping in response to LC activation, and demonstrate a causal link between receptor expression, brain states and functionally connected large-scale networks at rest. 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.

neuroscience↗