Johannes Bohacek

Last Name

Bohacek

First Name

Johannes

ORCID

0000-0002-8442-653X

Organisational unit

09499 - Bohacek, Johannes / Bohacek, Johannes

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Publications 1 - 10 of 56

A guide to designing germline-dependent epigenetic inheritance experiments in mammals
Bohacek, Johannes; Mansuy, Isabelle (2017)
Nature Methods
Recent work has demonstrated that environmental factors experienced by parents can affect their offspring across multiple generations, and that such transgenerational transmission can depend on the germline. Causal evidence for the involvement of germ cells is rare, however, and the underlying molecular mechanisms remain poorly understood. Further, studies often employ varying methods in experimental design and data interpretation. We provide a critical analysis of these issues and suggest possible solutions and guidelines for improving study design and generating reproducible and high-quality data.
Single-Nucleus RNA-Sequencing in Brain Tissue
Waag, Rebecca; Bohacek, Johannes (2023)
Current Protocols
Neuroscience research greatly benefits from single-cell sequencing technologies, which can reveal transcriptional alterations on a cellular level. However, preparing single-cell suspensions is technically challenging, requires experience, and has several limitations that can influence the transcriptional readout. Performing sequencing of single nuclei instead of single cells alleviates several of the challenges of sample preparation and highlights acute nuclear transcription. Here, we provide a protocol to prepare a nuclei suspension for single-nucleus RNA-sequencing for cell type-specific transcriptional profiling of brain tissue using the 10x Genomics single-cell gene expression assay. Furthermore, we highlight important aspects to consider during experimental design and data analysis.
Paternal experience impacts cognitive function in offspring: a pre-existing concept
Bohacek, Johannes; Weber-Stadlbauer, Ulrike; Mansuy, Isabelle (2017)
Molecular Psychiatry
Molecular insights into transgenerational non-genetic inheritance of acquired behaviours
Bohacek, Johannes; Mansuy, Isabelle (2015)
Nature Reviews Genetics
Distinct Proteomic, Transcriptomic, and Epigenetic Stress Responses in Dorsal and Ventral Hippocampus
Floriou-Servou, Amalia; von Ziegler, Lukas; Stalder, Luzia; et al. (2018)
Biological Psychiatry
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.
Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation
Zerbi, Valerio; Floriou-Servou, Amalia; Markicevic, Marija; et al. (2019)
Neuron
Noradrenaline release from the locus coeruleus shapes stress-induced hippocampal gene expression
Privitera, Mattia; von Ziegler, Lukas M.; Floriou Servou, Amalia; et al. (2024)
eLife
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 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.
Tonic and burst-like locus coeruleus stimulation distinctly shift network activity across the cortical hierarchy
Grimm, Christina; Duss, Sian N.; Privitera, Mattia; et al. (2024)
Nature Neuroscience
Noradrenaline (NA) release from the locus coeruleus (LC) changes activity and connectivity in neuronal networks across the brain, modulating multiple behavioral states. NA release is mediated by both tonic and burst-like LC activity. However, it is unknown whether the functional changes in target areas depend on these firing patterns. Using optogenetics, photometry, electrophysiology and functional magnetic resonance imaging in mice, we show that tonic and burst-like LC firing patterns elicit brain responses that hinge on their distinct NA release dynamics. During moderate tonic LC activation, NA release engages regions associated with associative processing, while burst-like stimulation biases the brain toward sensory processing. These activation patterns locally couple with increased astrocytic and inhibitory activity and change the brain's topological configuration in line with the hierarchical organization of the cerebral cortex. Together, these findings reveal how the LC-NA system achieves a nuanced regulation of global circuit operations.
Big behavior: challenges and opportunities in a new era of deep behavior profiling
von Ziegler, Lukas; Sturman, Oliver; Bohacek, Johannes (2021)
Neuropsychopharmacology
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.
Analysis of behavioral flow resolves latent phenotypes
von Ziegler, Lukas M.; Roessler, Fabienne K.; Sturman, Oliver; et al. (2023)
bioRxiv
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

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Johannes Bohacek

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