Cardiac mitochondria exhibit dynamic functional clustering.

Area of Science:

• Mitochondrial physiology
• Systems biology
• Cardiac myocyte function

Background:

• Mitochondrial inner membrane potential (ΔΨm) exhibits multi-oscillatory behavior in cardiac networks under stress.
• Cardiac mitochondria form synchronously oscillating clusters with inversely correlated frequency and size.
• Local inter-mitochondrial coupling may modulate cluster frequency.

Purpose of the Study:

• To develop a method for quantifying cardiac mitochondrial network topology.
• To analyze dynamic local clustering coefficients of mitochondrial networks.
• To compare the topology of cardiac mitochondrial networks to random networks.

Main Methods:

• Identification of individual mitochondrial ΔΨm oscillation signals in cardiac myocytes.
• Cross-correlation analysis to determine time-varying inter-mitochondrial connectivity (≥90% signal correlation).
• Quantification of functional local clustering coefficients and comparison with Erdös-Rényi random networks.

Main Results:

• Cardiac mitochondrial networks exhibit dynamically changing clustering.
• The clustering coefficient for cardiac myocytes (0.500 ± 0.051) is significantly higher than for random networks (0.061 ± 0.020).
• Cardiac mitochondria form a non-random, clustered network structure.

Conclusions:

• Cardiac mitochondria form a network with dynamically connected components.
• The topological organization of cardiac mitochondria is prone to clustering.
• Observed clustering aligns with models of scale-free and chaotic systems in coupled oscillators.