Biology subjects

Puetz, B.

Publications and source records attributed to Puetz, B..

4 recordsLinked to original sources

bioRxiv2023

Extracellular vesicle-mediated trafficking of developmental cues is altered during human brain disease

Cellular crosstalk is an essential process influenced by numerous factors including secreted vesicles that transfer nucleic acids, lipids, and proteins between cells. Extracellular vesicles (EVs) have been the center of many studies focusing on neuron-to-neuron communication, but the role of EVs in progenitor-to-neuron and -astrocyte communication and whether EVs display cell-type-specific features for cellular crosstalk during neurogenesis is unknown. Here, using human-derived cerebral organoids, neural progenitors, neurons, and astrocytes, we found that many proteins coded by genes associated with neurodevelopmental disorders are transported via EVs. Thus, we characterized the protein content of EVs and showed their cell type-specific dynamics and function during brain development. Changes in the physiological crosstalk between cells can lead to neurodevelopmental disorders. EVs from patients with epilepsy were found altered in composition and function. Alterations in the intracellular and extracellular compartments highlighted a clear dysregulation of protein trafficking. This study sheds new light on the biology of EVs during brain development and neurodevelopmental disorders. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=185 SRC="FIGDIR/small/546646v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1dad15aorg.highwire.dtl.DTLVardef@e699ccorg.highwire.dtl.DTLVardef@17b371borg.highwire.dtl.DTLVardef@5efa7b_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical abstract(left) EV uptake mechanism varies depending on the receiving cell type; NPCs transport neuron EVs (nEVs) and astrocyte EVs (aEVs) to the nucleus, astrocytes localize progenitor EVs (pEVs) to the cytoplasm, and neurons retain pEVs and aEVs along the plasma membrane. (right) Cerebral organoids (COs) from progressive Myoclonus Epilepsy Type I (EPM1) patients release EVs lacking key proteins in neurodevelopment and proteins necessary for EV biogenesis and release. Illustration created using BioRender.

developmental biology↗

bioRxiv2022

Automatically annotated motion tracking identifies a distinct social behavioral profile following chronic social defeat stress

Severe stress exposure is a global problem with long-lasting negative behavioral and physiological consequences, increasing the risk of stress-related disorders such as major depressive disorder (MDD). An essential characteristic of MDD is the impairment of social functioning and lack of social motivation. Chronic social defeat stress is an established animal model for MDD research, which induces a cascade of physiological and social behavioral changes. The current developments of markerless pose estimation tools allow for more complex and socially relevant behavioral tests, but the application of these tools to social behavior remains to be explored. Here, we introduce the open-source tool "DeepOF" to investigate the individual and social behavioral profile in mice by providing supervised and unsupervised pipelines using DeepLabCut annotated pose estimation data. The supervised pipeline relies on pre-trained classifiers to detect defined traits for both single and dyadic animal behavior. Subsequently, the unsupervised pipeline explores the behavioral repertoire of the animals without label priming, which has the potential of pointing towards previously unrecognized motion motifs that are systematically different across conditions. We here provide evidence that the DeepOF supervised and unsupervised pipelines detect a distinct stress-induced social behavioral pattern, which was particularly observed at the beginning of a novel social encounter. The stress-induced social behavior shows a state of arousal that fades with time due to habituation. In addition, while the classical social avoidance task does identify the stress-induced social behavioral differences, both DeepOF behavioral pipelines provide a clearer and more detailed profile. DeepOF aims to facilitate reproducibility and unification of behavioral classification of social behavior by providing an open-source tool, which can significantly advance the study of rodent individual and social behavior, thereby enabling novel biological insights as well as drug development for psychiatric disorders.

neuroscience↗

bioRxiv2022

DiffBrainNet: differential analyses add new insights into the response to glucocorticoids at the level of genes, networks and brain regions

Genome-wide gene expression analyses are invaluable tools for increasing our knowledge of biological and disease processes, allowing a hypothesis-free comparison of gene expression profiles across experimental groups, tissues and cell types. Traditionally, transcriptomic data analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders and their risk factors, including stress. In this manuscript, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress hormone receptor agonist dexamethasone in C57Bl/6 mice, in 8 brain regions important for stress processing: the prefrontal cortex, the amygdala, the paraventricular nucleus of the hypothalamus, the cerebellar cortex, and sub regions of the hippocampus: the dorsal and ventral Cornu Ammonis 1, the dorsal and ventral dentate gyrus. By applying a combination of differential network- and differential expression-analyses, we find that these explain distinct but complementary aspects and biological mechanisms of the responses to the stimulus. In addition, network analysis identifies new differentially connected partners of important genes and can be used to generate hypotheses on specific molecular pathways affected. With this work, we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain: DiffBrainNet (http://diffbrainnet.psych.mpg.de), which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner.

genomics↗

bioRxiv2017

Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations

The immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. We isolated monocytes from 134 genotyped individuals, stimulated the cells with three defined microbe-associated molecular patterns (LPS, MDP, and ppp-dsRNA), and profiled the transcriptome at three time points. After mapping expression quantitative trait loci (eQTL), we identified 417 response eQTLs (reQTLs) with differing effect between the conditions. We characterized the dynamics of genetic regulation on early and late immune response, and observed an enrichment of reQTLs in distal cis-regulatory elements. Response eQTLs are also enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover novel reQTL effects in multiple GWAS loci, and show a stronger enrichment of response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli modifying genetic predisposition to disease.

genetics↗