Cargando…

Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations

Beta cells within the pancreatic islets of Langerhans respond to stimulation with coherent oscillations of membrane potential and intracellular calcium concentration that presumably drive the pulsatile exocytosis of insulin. Their rhythmic activity is multimodal, resulting from networked feedback in...

Descripción completa

Detalles Bibliográficos
Autores principales: Zmazek, Jan, Klemen, Maša Skelin, Markovič, Rene, Dolenšek, Jurij, Marhl, Marko, Stožer, Andraž, Gosak, Marko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021717/
https://www.ncbi.nlm.nih.gov/pubmed/33833686
http://dx.doi.org/10.3389/fphys.2021.612233
_version_ 1783674791510671360
author Zmazek, Jan
Klemen, Maša Skelin
Markovič, Rene
Dolenšek, Jurij
Marhl, Marko
Stožer, Andraž
Gosak, Marko
author_facet Zmazek, Jan
Klemen, Maša Skelin
Markovič, Rene
Dolenšek, Jurij
Marhl, Marko
Stožer, Andraž
Gosak, Marko
author_sort Zmazek, Jan
collection PubMed
description Beta cells within the pancreatic islets of Langerhans respond to stimulation with coherent oscillations of membrane potential and intracellular calcium concentration that presumably drive the pulsatile exocytosis of insulin. Their rhythmic activity is multimodal, resulting from networked feedback interactions of various oscillatory subsystems, such as the glycolytic, mitochondrial, and electrical/calcium components. How these oscillatory modules interact and affect the collective cellular activity, which is a prerequisite for proper hormone release, is incompletely understood. In the present work, we combined advanced confocal Ca(2+) imaging in fresh mouse pancreas tissue slices with time series analysis and network science approaches to unveil the glucose-dependent characteristics of different oscillatory components on both the intra- and inter-cellular level. Our results reveal an interrelationship between the metabolically driven low-frequency component and the electrically driven high-frequency component, with the latter exhibiting the highest bursting rates around the peaks of the slow component and the lowest around the nadirs. Moreover, the activity, as well as the average synchronicity of the fast component, considerably increased with increasing stimulatory glucose concentration, whereas the stimulation level did not affect any of these parameters in the slow component domain. Remarkably, in both dynamical components, the average correlation decreased similarly with intercellular distance, which implies that intercellular communication affects the synchronicity of both types of oscillations. To explore the intra-islet synchronization patterns in more detail, we constructed functional connectivity maps. The subsequent comparison of network characteristics of different oscillatory components showed more locally clustered and segregated networks of fast oscillatory activity, while the slow oscillations were more global, resulting in several long-range connections and a more cohesive structure. Besides the structural differences, we found a relatively weak relationship between the fast and slow network layer, which suggests that different synchronization mechanisms shape the collective cellular activity in islets, a finding which has to be kept in mind in future studies employing different oscillations for constructing networks.
format Online
Article
Text
id pubmed-8021717
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-80217172021-04-07 Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations Zmazek, Jan Klemen, Maša Skelin Markovič, Rene Dolenšek, Jurij Marhl, Marko Stožer, Andraž Gosak, Marko Front Physiol Physiology Beta cells within the pancreatic islets of Langerhans respond to stimulation with coherent oscillations of membrane potential and intracellular calcium concentration that presumably drive the pulsatile exocytosis of insulin. Their rhythmic activity is multimodal, resulting from networked feedback interactions of various oscillatory subsystems, such as the glycolytic, mitochondrial, and electrical/calcium components. How these oscillatory modules interact and affect the collective cellular activity, which is a prerequisite for proper hormone release, is incompletely understood. In the present work, we combined advanced confocal Ca(2+) imaging in fresh mouse pancreas tissue slices with time series analysis and network science approaches to unveil the glucose-dependent characteristics of different oscillatory components on both the intra- and inter-cellular level. Our results reveal an interrelationship between the metabolically driven low-frequency component and the electrically driven high-frequency component, with the latter exhibiting the highest bursting rates around the peaks of the slow component and the lowest around the nadirs. Moreover, the activity, as well as the average synchronicity of the fast component, considerably increased with increasing stimulatory glucose concentration, whereas the stimulation level did not affect any of these parameters in the slow component domain. Remarkably, in both dynamical components, the average correlation decreased similarly with intercellular distance, which implies that intercellular communication affects the synchronicity of both types of oscillations. To explore the intra-islet synchronization patterns in more detail, we constructed functional connectivity maps. The subsequent comparison of network characteristics of different oscillatory components showed more locally clustered and segregated networks of fast oscillatory activity, while the slow oscillations were more global, resulting in several long-range connections and a more cohesive structure. Besides the structural differences, we found a relatively weak relationship between the fast and slow network layer, which suggests that different synchronization mechanisms shape the collective cellular activity in islets, a finding which has to be kept in mind in future studies employing different oscillations for constructing networks. Frontiers Media S.A. 2021-03-23 /pmc/articles/PMC8021717/ /pubmed/33833686 http://dx.doi.org/10.3389/fphys.2021.612233 Text en Copyright © 2021 Zmazek, Klemen, Markovič, Dolenšek, Marhl, Stožer and Gosak. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Zmazek, Jan
Klemen, Maša Skelin
Markovič, Rene
Dolenšek, Jurij
Marhl, Marko
Stožer, Andraž
Gosak, Marko
Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations
title Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations
title_full Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations
title_fullStr Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations
title_full_unstemmed Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations
title_short Assessing Different Temporal Scales of Calcium Dynamics in Networks of Beta Cell Populations
title_sort assessing different temporal scales of calcium dynamics in networks of beta cell populations
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021717/
https://www.ncbi.nlm.nih.gov/pubmed/33833686
http://dx.doi.org/10.3389/fphys.2021.612233
work_keys_str_mv AT zmazekjan assessingdifferenttemporalscalesofcalciumdynamicsinnetworksofbetacellpopulations
AT klemenmasaskelin assessingdifferenttemporalscalesofcalciumdynamicsinnetworksofbetacellpopulations
AT markovicrene assessingdifferenttemporalscalesofcalciumdynamicsinnetworksofbetacellpopulations
AT dolensekjurij assessingdifferenttemporalscalesofcalciumdynamicsinnetworksofbetacellpopulations
AT marhlmarko assessingdifferenttemporalscalesofcalciumdynamicsinnetworksofbetacellpopulations
AT stozerandraz assessingdifferenttemporalscalesofcalciumdynamicsinnetworksofbetacellpopulations
AT gosakmarko assessingdifferenttemporalscalesofcalciumdynamicsinnetworksofbetacellpopulations