Obesity is an increasing problem where the central nervous system (CNS) plays a major role by regulating food intake. This regulation is based on feedback systems from peripheral organs, including adipose tissue. Brown adipose tissue (BAT) is a subtype of adipose tissue that produces heat in response to cold by switching from an idle state to a highly energy-consuming state. BAT also secretes signalling molecules called batokines, but the biological effects of batokines on distal tissues are unclear. My overall hypothesis is that the energetic state of BAT will be communicated to the CNS, via batokines, to mediate appetite control, in a BAT-brain axis. To test this, we will establish a peptide library of human plasma peptidomes of samples collected during different states of BAT activity, combined with peptidome datasets generated from human brown fat cells using two complementary approaches: peptidomics and smORF mapping. Joining these datasets will allow us to select batokine candidates that are consistently regulated by alterations in BAT activity in plasma and brown fat cells. Using in silico approaches for peptide ranking and bioactivity prediction, we will select peptides, and create a neural bioactivity screening platform, assessing neural activity and/or plasticity. For this, we will establish 3D-cultures of appetite-regulating neurons, including human iPSC-derived AgRP and POMC neurons as well as of murine primary hypothalamic neurons. These models will be incorporated with high-content screening and imaging approaches. Successful peptides will be tested for metabolic effects in mice models, and targeted neurons and signalling pathways will be tracked down to a single cell level. All experimental data will be integrated with the in-silico data to generate a searchable online atlas of appetite regulating peptides, promoting my overall goal of discovering novel appetite-regulating circuits to identify new strategies to target obesity and its related diseases.
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