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In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes.
In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes.
One Sentence Summary Bats avoid acoustic interference by rapidly adjusting the timing of vocalizations to the temporal pattern of varying noise.
In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes.
One Sentence Summary: Bats avoid acoustic interference by rapidly adjusting the timing of vocalizations to the temporal pattern of varying noise.
How the brain evolved remains a mystery. The goal of this thesis is to understand the fundamental processes that are behind the evolutionary history of the brain. Amniotes appeared 320 million years ago with the transition from water to land. This early group bifurcated into sauropsids (reptiles and birds) and synapsids (mammals). Amniote brains evolved separately and display obvious structural and functional differences. Although those differences reflect brain diversification, all amniote brains share a common ancestor and their brains show multiple derived similarities: equivalent structures, networks, circuits and cell types have been preserved during millions of years. Finding these differences and similarities will help us understand brain historical evolution and function. Studying brain evolution can be approached from various levels, including brain structure, circuits, cell types, and genes. We propose a focus on cell types for a more comprehensive understanding of brain evolution. Neurons are the basic building blocks and the most diverse cell types in the brain. Their evolution reflects changes in the developmental processes that produce them, which in turn may shape the neural circuits they belong to. However, there is currently a lack of a unified criteria for studying the homology of connectivity and development between neurons. A neuron’s transcriptome is a molecular representation of its identity, connectivity, and developmental/evolutionary history. Hence the comparison of neuronal transcriptomes within and across species is a new and transformative development in the study of brain evolution. As an alternative, comparing neuronal transcriptomes across different species can provide insights into the evolution of the brain. We propose that comparing transcriptomes can be a way to fill this gap and unify these criteria. In previous studies, published in Science (Tosches et al., 2018) and Nature (Norimoto et al., 2020), we leveraged scRNAseq in reptiles to re-evaluate the origins and evolution of the mammalian cerebral cortex and claustrum. Motivated by the success of this approach, in this thesis we have now expanded single-cell profiling to the entire brain of a lizard species, the Australian dragon Pogona vitticeps, with a special focus in thalamus and prethalamus of. This approach allowed us to study the evolution of neuron types in amniotes. Therefore, we aimed to build a multilevel atlas of the lizard brain based on histology and transcriptomic and compare it to an equal mouse dataset (Zeisel et al., 2018).
Our atlas reveals a general structure that is consistent with that for other amniote brains, allowing us to make a direct comparison between lizard and mouse, despite their evolutionary divergence 320 million years ago. Through our analysis of the transcriptomes present in various neuron types, we have uncovered a core of conserved classes and discovered a fascinating dichotomy of new and conserved neuron types throughout the brain. This research challenges the traditional notion that certain brain regions are more conserved than others.
Our research also has uncovered the evolutionary history of the lizard thalamus and prethalamus by comparing them to homologous brain regions of the mouse. This pioneering research sheds new light on our understanding of the evolutionary history of the lizard brain. We propose a new classification of the lizard thalamic nuclei based on
transcriptomics. Our research revealed that the thalamic neuron types in lizards can be grouped into two large, conserved categories from the medial to lateral thalamus. These categories are encoded by a common set of effector genes, linking theories based on connectivity and molecular studies of these areas. In our data we have seen that there is a conservation of the medial-lateral transcriptomic axis in mouse and lizard, this conservation was most likely already present in the common ancestor. Although there is a shared medial-lateral axis, a deeper study of the thalamic cell types has allowed us to see the existence of a partial diversification of the thalamic population, specifically in the sensory-related lateral thalamus; in opposition, the medial thalamic nuclei neuron-types have been preserved.
On the other hand, the comparison with the mammalian prethalamus allowed us to confirm that the lizard ventromedial thalamic neuron types are homologous to mouse reticular thalamic neuron types (Díaz et al., 1994), even if they do not express the classical Reticular thalamic nucleus (RTn) marker PV/pvalb. We also discovered that there has been a simplification in the mammalian prethalamic neuron types in favor of an increase in the number of Interneurons (IN) types within their thalamus. We suggest that the loss of GABAergic neuronal types in the mammalian prethalamus is linked to the need for a more efficient control of the thalamo-pallial communication in mammals, while in lizards, where thalamo-pallial communication is probably simpler, the diversity prethalamus presents a higher diversity.
An important goal is to identify the direct activation domain (AD)-interacting components of the transcriptional machinery within the context of native complexes. Toward this end, we first demonstrate that the multisubunit TFIID, SAGA, mediator, and Swi/Snf coactivator complexes from transcriptionally competent whole-cell yeast extracts were all capable of specifically interacting with the prototypic acidic ADs of Gal4 and VP16. We then used hexahistidine tags as genetically introduced activation domain-localized cross-linking receptors. In combination with immunological reagents against all subunits of TFIID and SAGA, we systematically identified the direct AD-interacting subunits within the AD-TFIID and AD-SAGA coactivator complexes enriched from whole-cell extracts and confirmed these results using purified TFIID and partially purified SAGA. Both ADs directly cross-linked to TBP and to a subset of TFIID and SAGA subunits that carry histone-fold motifs.
Owing to their morphological complexity and dense network connections, neurons modify their proteomes locally, using mRNAs and ribosomes present in the neuropil (tissue enriched for dendrites and axons). Although ribosome biogenesis largely takes place in the nucleus and perinuclear region, neuronal ribosomal protein (RP) mRNAs have been frequently detected remotely, in dendrites and axons. Here, using imaging and ribosome profiling, we directly detected the RP mRNAs and their translation in the neuropil. Combining brief metabolic labeling with mass spectrometry, we found that a group of RPs rapidly associated with translating ribosomes in the cytoplasm and that this incorporation was independent of canonical ribosome biogenesis. Moreover, the incorporation probability of some RPs was regulated by location (neurites vs. cell bodies) and changes in the cellular environment (following oxidative stress). Our results suggest new mechanisms for the local activation, repair and/or specialization of the translational machinery within neuronal processes, potentially allowing neuronal synapses a rapid means to regulate local protein synthesis.
Owing to their morphological complexity and dense network connections, neurons modify their proteomes locally, using mRNAs and ribosomes present in the neuropil (tissue enriched for dendrites and axons). Although ribosome biogenesis largely takes place in the nucleus and perinuclear region, neuronal ribosomal protein (RP) mRNAs have been frequently detected remotely, in dendrites and axons. Here, using imaging and ribosome profiling, we directly detected the RP mRNAs and their translation in the neuropil. Combining brief metabolic labeling with mass spectrometry, we found that a group of RPs quickly associated with translating ribosomes in the cytoplasm and that this incorporation is independent of canonical ribosome biogenesis. Moreover, the incorporation probability of some RPs was regulated by location (neurites vs. cell bodies) and changes in the cellular environment (in response to oxidative stress). Our results suggest new mechanisms for the local activation, repair and/or specialization of the translational machinery within neuronal processes, potentially allowing remote neuronal synapses a rapid solution to the relatively slow and energy-demanding requirement of nuclear ribosome biogenesis.
Viruses that carry a positive-sense, single-stranded (+ssRNA) RNA translate their genomes soon after entering the host cell to produce viral proteins, with the exception of retroviruses. A distinguishing feature of retroviruses is reverse transcription, where the +ssRNA genome serves as a template to synthesize a double-stranded DNA copy that subsequently integrates into the host genome. As retroviral RNAs are produced by the host cell transcriptional machinery and are largely indistinguishable from cellular mRNAs, we investigated the potential of incoming retroviral genomes to directly express proteins. Here we show through multiple, complementary methods that retroviral genomes are translated after entry. Our findings challenge the notion that retroviruses require reverse transcription to produce viral proteins. Synthesis of retroviral proteins in the absence of productive infection has significant implications for basic retrovirology, immune responses and gene therapy applications.
We examined the feedback between the major protein degradation pathway, the ubiquitin-proteasome system (UPS), and protein synthesis in rat and mouse neurons. When protein degradation was inhibited, we observed a coordinate dramatic reduction in nascent protein synthesis in neuronal cell bodies and dendrites. The mechanism for translation inhibition involved the phosphorylation of eIF2α, surprisingly mediated by eIF2α kinase 1, or heme-regulated kinase inhibitor (HRI). Under basal conditions, neuronal expression of HRI is barely detectable. Following proteasome inhibition, HRI protein levels increase owing to stabilization of HRI and enhanced translation, likely via the increased availability of tRNAs for its rare codons. Once expressed, HRI is constitutively active in neurons because endogenous heme levels are so low; HRI activity results in eIF2α phosphorylation and the resulting inhibition of translation. These data demonstrate a novel role for neuronal HRI that senses and responds to compromised function of the proteasome to restore proteostasis.
The prefrontal cortex (PFC) is considered the cognitive center of the mammalian brain. It is involved in a variety of cognitive functions such as decision making, working memory, goal-directed behavior, processing of emotions, flexible action selection, attention, and others (Fuster, 2015). In rodents, these functions are associated with the medial prefrontal cortex (mPFC). Experiments in mice and rats have shown that neurons in the mPFC are necessary for successful performance of many cognitive tasks. Moreover, measurements of neural activity in the mPFC show excitation or inhibition in different cells in relation to specific aspects of the tasks to be solved. To date, however, it is largely unknown whether prefrontal neurons are stably activated during the same behaviors within a task and whether similar aspects are represented by the same neurons in different tasks. In addition, it is unclear how specifically neurons are activated, for example, whether cells that are activated in response to reward are activated in a different task without reward in a different situation or remain inactive. To address these questions, we recorded the same neurons in the mPFC of mice over the course of several weeks while the animals performed various behaviors.
To do this, we expressed GCaMP6 in pyramidal neurons in the mPFC of mice. A small lens was implanted in the same location and a miniature microscope ("miniscope") was used to record neural activity. Later the extracted neurons got aligned based on their shape and position across multiple days and sessions. The mice performed five different behavioral tests while neural activity was measured: A spatial working memory test in a T-maze, exploration of the elevated plus maze (EPM), a novel object recognition (NO) test including free open field (OF) exploration, a social interaction (SI) test and discriminatory auditory fear conditioning (FC). Each task was repeated at least twice to check for stable task encoding across sessions. Behavioral performance and neural correlates to specific task events were similar to earlier studies across all tasks. We utilized generalized linear models (GLM) to determine which behavioral variables most strongly influence neural activity in the mPFC. The position of the mouse in the environment was found to explain most of the variance in neural activity, together with movement speed they were the strongest predictors of neural activity across all tasks. Reward time points in the working memory test, the conditioned stimulus after fear conditioning, or head direction in general were also strongly encoded in the mPFC.
Many of the recorded neurons showed a stable spatial activity profile across multiple sessions of the same task. Similarly, cells that coded for position in one task tended to code for position in other tasks. Not only did the same cells code for position across multiple tasks, but cells also coded for movement speed and head direction. This indicates that at least these general behavioral variables are each represented by the same neurons in the mPFC. Interestingly, the stability of position or speed coding did not depend on the time between two sessions, but only on whether it was within the same or across different tasks. Within the same task, stability was slightly higher than across different tasks.
To find out whether task-specific behavioral aspects were also stably encoded in the mPFC, difference scores as the difference in neural activity between two task aspects like left- and right-choice trials or exposed and enclosed locations were calculated. Many cells encoded these aspects stably across different sessions of each task. Both the left-right differences in the different phases of the working memory test, the open-closed-arm differences in the elevated plus maze, the different activity between center and corners in the open field, the social target-object differences in the social interaction test, and the differences between the two tones during fear conditioning were all stably encoded across the population of mPFC cells. Only the distinction between the novel and the familiar object during object recognition was not stably encoded, but also the preference for the novel object was not present in the second session of novel object exploration.
There was also an overlap in coding for different aspects within a task across multiple sessions. For example, cells stably encoded left-right differences in the T-maze between different sessions as a function of walking direction across different phases of working memory, an aspect that we could already show within one session (Vogel, Hahn et al., 2022). During fear conditioning, the same cells showed a discrimination between CS+ and CS- that also responded to the start of CS+.
Consistency in the neurons activity across different tasks was also found, but only between tasks with similar demands, the elevated plus-maze and free exploration of the open field. Cells that were more active in the open arms also showed more activity in the center of the open field and vice versa. This could be an indicator that the cells were coding for anxiety or exposure across those tasks, indicating that neurons in the mPFC also stably encode general task aspects independent of the specific environment. However, it remains unclear what exactly these neurons encode; in the case of a general fear signal, one would also expect activation during fear conditioning which could not be found.
Overall, we found that neurons in the mPFC of mice encoded multiple general behavioral variables across multiple tasks and task-specific variables were encoded stably within each of the tested tasks. However, we found little task-specific variables that were systematically encoded by the same neurons with the exception being the elevated plus-maze and open field exploration, two tasks with similar features.