Ultrastructural characterization of microtubules at high resolution in the mammalian peripheral nervous system

Mechanotransduction is the ability of living organisms to sense and respond to mechanical forces by converting them into a biological response. In mammals, mechanotransduction is mediated by specialized sensory neurons which are capable of detecting a wide range of mechanical stimuli, relying on the presence of mechanotransducer channels on sensory nerve endings. Surprisingly, little is known about the properties of mechanotransducers in mammals and thus the mechanisms that convert mechanical forces into electrical signals at the peripheral endings of sensory neurons and, especially how the cytoskeleton influences it. In previous work, we have found that mice lacking the -tubulin acetyltransferase Atat1 display a significant decrease in mechanosensitivity across all major fiber types innervating the skin, strongly affecting light touch and pain, with no impact on other sensory modalities1. We also assessed that such a phenotype does not arise from wide-ranging effects on the development, morphology and structure of peripheral sensory neurons but may be caused by the lack of a sub-membrane ring of acetylated -tubulin that somehow sets the mechanical rigidity of the cells, rendering them more resistant to mechanical deformation1. How -tubulin acetylation is capable of setting cellular rigidity remains poorly understood. Here, an ultrastructural analysis on sensory nerve endings was performed to examine whether the lack of -tubulin acetylation affect microtubules (MTs) organization and structure along the sensory neuron axis, from the soma of DRG neurons to their peripheral endings. Superresolution microscopy analysis on DRG neurons shows that the lack of -tubulin acetylation does not affect the overall MTs organization. Moreover, combining high-resolution transmission electron microscopy with image analysis, I investigated MT morphology and distribution in the saphenous nerve from Atat1control and Atat1cKO mice. Our results demonstrated that no major differences were observed between MTs from the Atat1cKO compared to the Atat1control when minor axis, eccentricity, solidity and perimeter length were compared. These results were also confirmed by Cryo-EM observations, suggesting that lack of acetylation does not affect MTs ultrastructure in mammals in the absence of mechanical stress. Finally, the von Frey assay shows that mice lacking Atat1 not only display a profound loss of light touch and pain sensitivity but, in addition, they develop allodynia only beginning at day 21 post SNI (spared nerve injury), suggesting that microtubule acetylation play an important role in hypersensitivity to mechanical stimuli associated with chronic pain

Acetylated microtubules are essential for touch sensation in mice

The sense of touch depends upon the transformation of mechanical energy into electrical signals by peripheral sensory neurons and associated cells in the skin. This conversion is thought to be mediated by a complex of proteins in which ion channels such as Piezo2 function as mechanotransducers. However, how mechanical energy is transmitted into mechanosensitive ion channel opening, and how cellular components such as the cytoskeleton influence this process, is largely unknown. Here we show that mice lacking the tubulin acetyltransferase, Atat1, in sensory neurons display profound deficits in their ability to detect mechanical touch and pain. In the absence of Atat1, behavioural responses to innocuous and noxious mechanical stimuli are strongly reduced in multiple assays while sensitivity of mice to thermal stimuli is unaltered. In ex vivo skin-nerve preparations, the mechanosensitivity of all low- and high- threshold mechanoreceptor subtypes innervating the skin is substantially decreased in Atat1 conditional knockout mice. In cultured dorsal root ganglion neurons, both slowly- and rapidly- adapting mechanically- activated currents are absent or reduced upon Atat1 deletion with no effect on other neuronal functions. We establish that this broad loss of mechanosensitivity is dependent upon the acetyltransferase activity of Atat1, and that by mimicking α-tubulin acetylation genetically by substituting the lysine amino acid for a structurally similar glutamine, mechanosensitivity can be restored in Atat1- deficient sensory neurons. Finally, we demonstrate that acetylated microtubules localize to a prominent band under the membrane of sensory neuron cell bodies and axons, and in the absence of Atat1 and acetylated α-tubulin, cultured sensory neurons display significant reductions in their membrane elasticity. Our results indicate that the microtubule cytoskeleton is an essential component of the mammalian mechanotransduction complex and that by influencing cellular stiffness, α-tubulin acetylation can tune mechanical sensitivity across the full range of mechanoreceptor subtypes

Nature and source of animal spontaneous behaviors: Insights from psychobehavioral development and neuronal population dynamics in mice

Awake animals switch between different behavioral states irregularly even in a homogenous and steady environment, especially obvious outside from any behavioral task when they are free to voluntarily behave. These irregular but structured patterns have been taken as a representation of internal states such as emotion, and are believed to represent underlying background brain activity and its dynamics. To date, the nature and source of animal spontaneous behaviors remain as a major conceptual challenge to academia, due to the lack of approaches to systematically and quantitatively examine this fundamental process. To achieve insights about the neural substrate of animal spontaneous behaviors, the research was conducted in two directions: (i) To interpret previously challenging and inconclusive behavioral development by re-evaluating spontaneous behaviors that represent emotionality, centered on the study of PTSD (post-traumatic stress disorder)-like internal psychological development in laboratory mice; (ii) To demonstrate a driving and control principle explaining fine-scale and global observations of neuronal and behavioral dynamics in spontaneously behaving mice, by two-photon calcium imaging of neuronal populations across cerebral cortical layers and areas. The results from these investigations provide the first system-level view of experimentally disentangled components, processes, and determinants explaining the nature and source of animal spontaneous behaviors.Okinawa Institute of Science and Technology Graduate Universit

Stochastic dynamics of migrating cells

Cell migration is critical in many physiological phenomena, including embryogenesis, immune response, and cancer. In all these processes, cells face a common physical challenge: they navigate confining extra-cellular environments, in which they squeeze through thin constrictions. The motion of cells is powered by a complex machinery whose molecular basis is increasingly well understood. However, a quantitative understanding of the functional cell behaviours that emerge at the cellular scale remains elusive. This raises a central question, which acts as a common thread throughout the projects in this thesis: do migrating cells exhibit emergent dynamical 'laws' that describe their behavioural dynamics in confining environments? To address this question, we develop data-driven approaches to infer the dynamics of migrating cells directly from experimental data. We study the migration of cells in artificial confinements featuring a thin constriction across which cells repeatedly squeeze. From the experimental cell trajectories, we infer an equation of cell motion, which decomposes the dynamics into deterministic and stochastic contributions. This approach reveals that cells deterministically drive themselves into the thin constriction, which is in contrast to the intuition that constrictions act as effective barriers. This active driving leads to intricate non-linear dynamics that are poised close to a bifurcation between a bistable system and a limit cycle oscillator. We further generalize this data-driven framework to detect and characterize the variance of migration behaviour within a cell population and to investigate how cells respond to varying confinement size, shape, and orientation. We next investigate the mechanistic basis of these dynamics. Cell migration relies on the concerted dynamics of several cellular components, including cell protrusions and adhesive connections to the environment. Based on the experimental data, we systematically constrain a mechanistic model for confined cell migration. This model indicates that the observed deterministic driving is a consequence of the combined effects of the variable adhesiveness of the environment and a self-reinforcement of cell polarity in response to thin constrictions. These results suggest polarity feedback adaptation as a key mechanism in confined cell migration. Finally, we investigate the dynamics of interacting cells. To enable inference of cell-cell interactions, we develop Underdamped Langevin Inference, an inference method for stochastic high-dimensional and interacting systems. We apply this method to experiments of confined pairs of cells, which repeatedly collide with one another. This reveals that non-cancerous (MCF10A) and cancerous (MDA-MB-231) cells exhibit distinct interactions: while the non-cancerous cells exhibit repulsion and effective friction, the cancerous cells exhibit attraction and a surprising 'anti-friction' interaction. These interactions lead to non-cancerous cells predominantly reversing upon collision, while the cancer cells are able to efficiently move past one another by relative sliding. Furthermore, we investigate the effects of cadherin-mediated molecular contacts on cell-cell interactions in collective migration. Taken together, the data-driven approaches presented in this thesis may help to provide a new avenue to uncover the emergent laws governing the stochastic dynamics of migrating cells. We demonstrate how these approaches can provide key insights both into underlying mechanisms as well as emergent cell behaviours at larger scales.Zellmigration ist ein Kernelement vieler physiologischer Phänomene wie der Embryogenese, dem Immunsystem und der Krebsmetastase. In all diesen Prozessen stehen Zellen vor einer physikalischen Herausforderung: Sie bewegen sich in beengten Umgebungen, in denen sie Engstellen passieren müssen. Die Zellbewegung wird von einer komplexen Maschinerie an- getrieben, deren molekulare Komponenten immer besser verstanden werden. Demgegenüber fehlt ein quantitatives Verständnis des funktionalen Migrationsverhaltens der Zelle als Ganzes. Die verbindende Fragestellung der Projekte in dieser Arbeit lautet daher: gibt es emergente dynamische 'Gesetze', die die Verhaltensdynamik migrierender Zellen in beengten Umgebungen beschreiben? Um dieser Frage nachzugehen, entwickeln wir datengetriebene Ansätze, die es uns erlauben, die Dynamik migrierender Zellen direkt aus experimentellen Daten zu inferieren. Wir untersuchen Zellmigration in künstlichen Systemen, in denen Zellen Engstellen wiederholt passieren müssen. Aus den experimentellen Zelltrajektorien inferieren wir eine Bewegungsgleichung, die die Dynamik in deterministische und stochastische Komponenten trennt. Diese Methode zeigt, dass sich Zellen deterministisch 'aktiv' in die Engstellen hineinbewegen, ganz entgegen der intuitiven Erwartung, dass Engstellen als Hindernis fungieren könnten. Dieser aktive Antrieb führt zu einer komplexen nichtlinearen Dynamik im Übergangsbereich zwischen einem bistabilen System und einem Grenzzyklus-Oszillator. Wir verallgemeinern diesen datenbasierten Ansatz, um die Varianz des Migrationsverhaltens innerhalb einer Zellpopulation zu quantifizieren, und analysieren, wie Zellen auf die Größe, Form und Orientierung ihrer Umgebung reagieren. Darauf aufbauend untersuchen wir die zugrundeliegenden Mechanismen dieser Dynamik. Zellmigration basiert auf verschiedenen zellulären Komponenten, wie unter Anderem den Zellprotrusionen und der Adhäsion mit der Umgebung. Auf Basis der experimentellen Daten entwickeln wir ein mechanistisches Modell für Zellmigration in beengten Systemen, welches zeigt, dass der beobachtete aktive Antrieb eine Konsequenz zweier Effekte ist: Einer variierenden Adhäsion mit der Umgebung und einer Zellpolarität, die sich in Engstellen selbst verstärkt. Diese Ergebnisse deuten darauf hin, dass die Anpassung der Zellpolarität an die lokale Geometrie ein Schlüsselmechanismus in beengter Zellmigration ist. Schließlich analysieren wir die Dynamik interagierender Zellen. Um Zell-Zell Interaktionen zu inferieren, entwickeln wir die Underdamped Langevin Inference, eine Inferenzmethode für stochastische hochdimensionale und interagierende Systeme. Wir wenden diese Methode auf Daten von eingeschlossenen Zellpaaren an, welche wiederholt miteinander kollidieren. Dies zeigt, dass gesunde (MCF10A) und krebsartige (MDA-MB-231) Zellen unterschiedliche Interaktionen aufweisen: Während gesunde Zellen mit Abstoßung und effektiver Reibung interagieren, zeigen Krebszellen Anziehung und eine überraschende 'Anti-Reibung'. Diese Interaktionen führen dazu, dass gesunde Zellen nach Kollisionen primär umkehren, während Krebszellen effizient aneinander vorbeigleiten. Darüberhinaus analysieren wir die Effekte von Cadherin-basierten Molekularkontakten auf Zell-Zell Interaktionen in kollektiver Migration. Zusammenfassend könnten die in dieser Arbeit präsentierten datengetriebenen Ans ̈atze dabei helfen, ein besseres Verständnis der emergenten stochastischen Dynamik migrierender Zellen zu erlangen. Wir zeigen, wie diese Methoden wichtige Erkenntnisse sowohl über die zugrundeliegenden Mechanismen als auch über das emergente Zellverhalten liefern können

Content-aware approach for improving biomedical image analysis: an interdisciplinary study series

Biomedicine is a highly interdisciplinary research area at the interface of sciences, anatomy, physiology, and medicine. In the last decade, biomedical studies have been greatly enhanced by the introduction of new technologies and techniques for automated quantitative imaging, thus considerably advancing the possibility to investigate biological phenomena through image analysis. However, the effectiveness of this interdisciplinary approach is bounded by the limited knowledge that a biologist and a computer scientist, by professional training, have of each other’s fields. The possible solution to make up for both these lacks lies in training biologists to make them interdisciplinary researchers able to develop dedicated image processing and analysis tools by exploiting a content-aware approach. The aim of this Thesis is to show the effectiveness of a content-aware approach to automated quantitative imaging, by its application to different biomedical studies, with the secondary desirable purpose of motivating researchers to invest in interdisciplinarity. Such content-aware approach has been applied firstly to the phenomization of tumour cell response to stress by confocal fluorescent imaging, and secondly, to the texture analysis of trabecular bone microarchitecture in micro-CT scans. Third, this approach served the characterization of new 3-D multicellular spheroids of human stem cells, and the investigation of the role of the Nogo-A protein in tooth innervation. Finally, the content-aware approach also prompted to the development of two novel methods for local image analysis and colocalization quantification. In conclusion, the content-aware approach has proved its benefit through building new approaches that have improved the quality of image analysis, strengthening the statistical significance to allow unveiling biological phenomena. Hopefully, this Thesis will contribute to inspire researchers to striving hard for pursuing interdisciplinarity

29th Annual Computational Neuroscience Meeting: CNS*2020

Meeting abstracts This publication was funded by OCNS. The Supplement Editors declare that they have no competing interests. Virtual | 18-22 July 202

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)