Pauls, S. D. | Search bioRxiv

bioRxiv2024

Omega-3 polyunsaturated fatty acids modify glucose metabolism in THP-1 monocytes

Chronic inflammation is a driving factor in diseases like obesity and type 2 diabetes. Enhanced glucose metabolism, including via oxidative phosphorylation, may contribute to heightened immune activation. A recent clinical trial showed that supplementation with the n-3 fatty acid -linolenic acid (ALA) reduced oxidative phosphorylation rates in human monocytes. However, the mechanism remains unknown. Therefore, our objective was to explore the direct effects of ALA and docosahexaenoic acid (DHA) on glucose metabolism in a cell culture model and to explore the molecular mechanism. THP-1 monocytes were treated for 48h with 10-40 M of ALA or DHA and compared with vehicle and oleic acid controls. The Seahorse XFe24 system was used to approximate catabolic rates in the presence of glucose, including glycolysis and oxidative phosphorylation. The latter was validated by respirometry using an Oroboros O2k Oxygraph. Both ALA and DHA treatments reduced oxidative phosphorylation and increased glycolytic rates relative to control conditions. We identified pyruvate dehydrogenase kinase 4 (PDK4), an enzyme that inhibits the conversion of pyruvate to acetyl-CoA, as a possible mechanistic candidate. This gene was significantly upregulated by ALA and, to a greater extent, by DHA. Using fluorescent indicators, we also found that DHA increased reactive oxygen species while ALA had no effect. Our data suggest that ALA and DHA trigger a re-wiring of bioenergetic pathways in monocytes, possibly via the upregulation of PKD4. Given the close relationship between cell metabolism and immune cell activation, this may represent a novel mechanism by which n-3 fatty acids modulate immune function and inflammation.

cell biology↗

bioRxiv2021

Phase Gradients and Anisotropy of the Suprachiasmatic Network

Biological neural networks operate at several levels of granularity, from the individual neuron to local neural circuits to networks of thousands of cells. The daily oscillation of the brains master clock in the suprachiasmatic nucleus (SCN) rests on a yet to be identified network of connectivity among its ~20,000 neurons. The SCN provides an accessible model to explore neural organization at several levels of organization. To relate cellular to local and global network behaviors, we explore network topology by examining SCN slices in three orientations using immunochemistry, light and confocal microscopy, real-time imaging, and mathematical modeling. Importantly, the results reveal small local groupings of neurons that form intermediate structures, here termed "phaseomes" which can be identified through stable local phase differences of varying magnitude among neighboring cells. These local differences in phase are distinct from the global phase relationship - that between individual cells and the mean oscillation of the overall SCN. The magnitude of the phaseomes local phase differences are associated with a global phase gradient observed in the SCNs rostral-caudal extent. Modeling results show that a gradient in connectivity strength can explain the observed gradient of phaseome strength, an extremely parsimonious explanation for the heterogeneous oscillatory structure of the SCN. Significance statementOscillation is a fundamental property of information sensing and encoding in the brain. Using real time imaging and modeling, we explore encoding of time by examining circadian oscillation in single neurons, small groups of neurons, and the entire nucleus, in the brains master: the suprachiasmatic nucleus (SCN). New insights into the network organization underlying circadian rhythmicity include the discovery of intermediate structures, termed phaseomes, characterized by neurons which are stably out of phase with their neighbors. Modeling indicates that the pattern of phaseomes across the tissue encompasses a gradient in connectivity strength from the rostral to caudal aspects of the nucleus. Anisotropy in network organization emerges from comparisons of phaseomes and connectivity gradients in sagittal, horizontal and coronal slices.

neuroscience↗