Expanding the limits of Multiomics : From Bulk to Single Cells

Solid Lipid-Based Nanoparticles in Drug Delivery: From Foundational Insights to Brain-Targeting Strategies

Anne Desmazieres

Neuronal activity and immune cues modulate neuron-microglia communication and shape its role in repair

Multiple Sclerosis (MS) is an inflammatory, demyelinating and neurodegenerative disease of the central nervous system (CNS). While an endogenous repair process exists following demyelination in MS, it is incomplete and varies between individuals. Understanding the mechanisms of remyelination and neuroprotection is therefore crucial to promote repair in patients.

In MS, the nodes of Ranvier, which support the fast axonal conduction, are disrupted but can reorganize early during repair, even before remyelination proceeds. Furthermore, microglia, the central nervous system resident immune cells, are key players in the disease, as they can engage in pro-inflammatory as well as pro-regenerative processes.

Our recent work identified nodal structures as a preferential site for microglia-neuron interaction in both mouse and human. We now demonstrate that neuronal activity promotes microglia-node interaction and the switch towards pro-regenerative microglia. Conversely, adaptive immune cues impair microglia-node interaction in an inflammatory MS model and the extent of these interactions at the onset of remission correlates with recovery. Taken together, our findings identify factors that influence microglia-neuron crosstalk in disease and suggest that neuronal activity supports remyelination not only by directly regulating oligodendroglia, but also by modulating microglial behavior during repair.

Multimodal biomarkers based on brain dynamics, omics and clinical data for neuropathologies: Examples of stroke, ALS and bipolar disorder

Abstract:
Recent progress in neuroimaging techniques give access to the brain activity in vivo at the whole-brain level, which holds many promises for the study of cognition and neuropathologies. As an example, an active direction in clinical research is the extraction of markers for the prognosis of patient evolution using fMRI. To go beyond a phenomenological analysis, models have also been developed to go beyond a pure (black-box) machine-learning approach applied on the recorded signals, aiming to develop interpretable markers or signatures of the brain dynamics. In this presentation I will focus on analyzing the propagation dynamics within brain subnetworks, which is also used to uncover information processing during cognitive tasks. Then, I will discuss data-fusion strategies to incorporate transcriptomics and clinical data to whole-brain dynamics data, in order to go towards multimodal biomarkers and uncover pathological mechanisms.

Diving into neurons: cellular and molecular mechanisms to unlock axon regeneration

In adult mammals, neurons of the central nervous system (CNS) fail to regenerate their axon after injury and to reconnect their target, hindering functional reconnection. To address this unmet need, my recent studies have explored several aspects. First, I showed that axon guidance is active not only during development but also in the mature brain after injury and is responsible for reconnection failure. Second, I showed that the intrinsic regrowth capacity of adult neurons relies on the translational regulation of specific mRNAs, highlighting translation as a dynamic layer of gene regulation involved in axon injury response and regeneration.

Interestingly, it is now established that translation is compartmentalized within neurons and occurs locally in the axon in a soma-autonomous manner. This local translation ensures a rapid and efficient renewal of proteins essential for neuronal circuit development and function. However, very little is known about the role and parameters of local translation in CNS repair, notably in the regrowth capacity of injured axons.

In the light of our recent findings, I will discuss our understanding of the mechanisms underlying the inability of adult CNS neurons to regenerate, as well as current strategies to promote axon regrowth and their limitations. I will also present the rationale for exploring local translation in injured axons as a potential key of their regrowth and of reconnection in the adult CNS.

With symptoms such as spontaneous pain, allodynia and or hyperalgesia, chronic pain affects more than 1.5
billion people worldwide and accounts for about 20% of physician visits. Yet, up to two-thirds of patients are
unsatisfied with current treatments. Despite relentless pharmacological efforts and major scientific advances in
our understanding of how the brain orchestrates coping behavioral mechanisms in response to pathological
pain, this past decade has been marked by an increasing number of failing clinical trials. Interestingly, current
pain behavioral and neuroimaging studies present tremendous potential in terms of translational diagnostic,
prognostic and or treatment-response tools. However, many technical obstacles. First, while humans can
verbally describe their pain, studies on rodents have long relied on behavioral assays providing non-exhaustive
characterization or altering animals’ original sensitivity through repetitive stimulations. Second, the variability
across chronic pain patients and conditions makes it challenging to understand functional brain dynamic
alterations supporting pain chronification or resolution. While pain duration varies according to the initial cause
of tissue injury, there is no rigorously controlled study establishing both semiology- and etiology-specific
dynamic brain signatures for the transition from acute to chronic pain. In line with this, most preclinical pain
neuroimaging studies are performed on anesthetized laboratory animals, which is a confound considering the
analgesic effect of anesthetics. Such caveats render correlations between chronic pain as a disease and inherent
behavioral and real-time brain activity alterations, challenging. Here I present emerging videography and
computational-based behavioral approaches that have the potential to significantly improve preclinical pain
research. Lastly, through a preliminary study, I show how the unprecedented longitudinal coupling of behavior
and awake resting-state fMRI in head-fixed mice, can unravel novel anatomical targets for the treatment of long-
lasting pain.