EPFL: Breakdown and repair of the aging brain metabolic system

The study presented explores the complex relationship between the aging brain, energy metabolism, blood flow and neuronal activity by introducing a comprehensive, data-driven molecular model of the neuro-glial vascular system, including all key enzymes, transporters, metabolites, and blood flow vital for neuronal electrical activity with 16’800 interaction pathways. We find significant alterations in metabolite concentrations and differential effects on ATP supply in neurons and astrocytes and within subcellular compartments within aged brains, and identify reduced Na⁺/K⁺-ATPase as the leading cause of impaired neuronal action potentials. The model predicts that the metabolic pathways cluster more closely in the aged brain, suggesting a loss of robustness and adaptability. Additionally, the aged metabolic system displays reduced flexibility, undermining its capacity to efficiently respond to stimuli and recover from damage. Through transcription factor analysis, the estrogen-related receptor alpha (ESRRA) emerged as a central target connected to these aging-related changes. An unguided optimization search pinpointed potential interventions capable of restoring the brain’s metabolic flexibility and restoring action potential generation. These strategies include increasing the NADH cytosol-mitochondria shuttle, NAD+ pool, ketone β-hydroxybutyrate, lactate and Na⁺/K⁺-ATPase and reducing blood glucose levels. The model is open-sourced to help guide further research in brain metabolism.

Publication: https://www.biorxiv.org/content/10.1101/2023.08.30.555341v2 

Scientific Collaborator: Polina Shichkova, Ph. D

Data visualization tool: Blue Brain BioExplorer

EPFL: Neuromodulation of neocortical microcircuitry: a multi-scale framework to model the effects of cholinergic release

Neuromodulation of neocortical microcircuits is one of the most fascinating
and mysterious aspects of brain physiology. Despite over a century of research,
the neuroscientific community has yet to uncover the fundamental biological organizing principles underlying neuromodulatory release.

Phylogenetically, Acetylcholine (ACh) is perhaps the oldest neuromodulator, and one of the most well-studied. ACh regulates the physiology of neurons and synapses, and modulates neural microcircuits to bring about a reconfiguration of global network states. ACh is known to support cognitive processes such as learning and memory, and is involved in the regulation of arousal, attention and sensory processing. While the effects of ACh in the neocortex have been characterized extensively, integrated knowledge of its mechanisms of action is lacking.

Furthermore, the ways in which ACh is released from en-passant axons originating in subcortical nuclei are still debatable. Simulation-based paradigms play an important role in testing scientific hypotheses, and provide a useful framework to integrate what is already known and systematically explore previously uncharted territory.

Importantly, data-driven computational approaches highlight gaps in current knowledge and guide experimental research. To this end, I developed a multi-scale model of cholinergic innervation of rodent somatosensory cortex comprising two distinct sets of ascending projections implementing either synaptic (ST) or volumetric transmission (VT). The model enables the projection types to be combined in arbitrary proportions, thus permitting investigations of the relative contributions of these two transmission modalities.

Using our ACh model, we find that the two modes of cholinergic release act in concert and have powerful desynchronizing effects on microcircuit activity. Furthermore we show that this modeling framework can be extended to other neuromodulators, such as dopamine and serotonin, with minimal constraining data. In summary, our results suggest a more nuanced view of neuromodulation in which multiple modes of transmitter release - ST vs VT - are required to produce synergistic functional effects.

Publication: https://infoscience.epfl.ch/entities/publication/0a69c342-ac83-4fa3-bc08-44b886969d60

Scientific Collaborator: Cristina Colangelo, Ph.D

Data visualization tool: Blue Brain BioExplorer