β-cell intrinsic dynamics rather than gap junction structure dictates subpopulations in the islet functional network

Abstract

Diabetes is caused by the inability of electrically coupled, functionally heterogeneous -cells within the pancreatic islet to provide adequate insulin secretion. Functional networks have been used to represent synchronized oscillatory [Ca2+] dynamics and to study -cell subpopulations, which play an important role in driving islet function. The mechanism by which highly synchronized -cell subpopulations drive islet function is unclear. We used experimental and computational techniques to investigate the relationship between functional networks, structural (gap-junction) networks, and intrinsic -cell dynamics in slow and fast oscillating islets. Highly synchronized subpopulations in the functional network were differentiated by intrinsic dynamics, including metabolic activity and KATP channel conductance, more than structural coupling. Consistent with this, intrinsic dynamics were more predictive of high synchronization in the islet functional network as compared to high levels of structural coupling. Finally, dysfunction of gap junctions, which can occur in diabetes, caused decreases in the efficiency and clustering of the functional network. These results indicate that intrinsic dynamics rather than structure drive connections in the functional network and highly synchronized subpopulations, but gap junctions are still essential for overall network efficiency. These findings deepen our interpretation of functional networks and the formation of functional sub-populations in dynamic tissues such as the islet.

Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis

“…Upon visual inspection of the networks and their corresponding parameters we can see a high degree of similarity between all displayed networks. Consistent with previous findings, all the networks exhibit high levels of clustering, modularity, and small-worldness [ 16 , 27 , 56 , 68 – 70 ]. In Fig 1C and 1D the degree and edge length distributions of the same networks as in Fig 1B are presented, and Fig 1E shows the calculated internetwork similarities (see Methods section for details).…”

“…The fast oscillations are representative of the electrical activity of cells, which is mediated by gap-junction-driven intercellular waves and thus contributes to the shorter, more clustered network structure which is quite similar to the underlying physical network. On the other hand, the slow component signal is associated with cellular metabolism which is to a greater extent affected by the similarity of intrinsic metabolic characteristics of cells and less by cell-to-cell coupling [ 56 , 70 , 78 , 79 ]. Interestingly, the raw-signal-derived functional network appears to be poised in between, which is somehow expected, as it encompasses both types of oscillatory activity.…”

“…Importantly, for the raw signal, it seems that except for the node degree, most of the network measures are more strongly determined by the slow component [ 56 ]. A logical consequence of the abovementioned differences in functional network structure is the finding that there is a relatively weak correlation between the fast and slow network layer [ 96 ], implying that different synchronization principles are at work [ 70 , 78 ], and one should not directly compare results of studies relying on fast oscillations with the ones relying on slow oscillations. Importantly, even with the same experimental model, e.g., isolated mouse islets, and set of analytical tools applied to extracting and analyzing [Ca 2+ ] i oscillations, islets with preponderance of fast, mixed or slow oscillations might coexist [ 99 – 101 ], and in this case, data should not be simply pooled, since this may obscure relevant biological differences, but analyzed for the two temporal components and for oscillatory phenotypes separately.…”

“…To facilitate interspecies comparison, future studies shall clearly specify the type of oscillations they are addressing. Finally, at present, it is difficult to experimentally compare the relationship between the structural networks of beta cells and their functional counterparts, but modelling studies suggest that the intricate structure of functional beta cell networks based on fast and slow oscillations may be at least partly explained by heterogeneity in beta cell activity and heterogenous intercellular coupling [ 68 , 70 , 78 ].…”

Synchronizing beta cells in the pancreas

“…So how do these two mechanisms work together to control blood glucose levels? Now, in eLife, Richard Benninger and co-workers – including Jennifer Briggs as first author – report new findings that shine some light on the relationship between beta cell subpopulations and gap junctions ( Briggs et al, 2023 ).…”