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RESEARCH PAPER / 2026-01-30

Quantitative muscle color as a proxy for structural and functional characteristics during muscle remodeling in Gryllus lineaticeps

Laturney, M., Martins, L., Diaz, T., Lo, E., Uen, N., Williams, C. M.

University of California, Berkeley · biorxiv

Abstract

Understanding the cellular and physiological mechanisms underlying muscle remodeling requires model systems that allow rapid, reliable, and quantitative assessment of muscle state. The cricket Gryllus lineaticeps naturally undergoes non-pathological striated muscle breakdown (histolysis), making it a promising system for studying this process. However, current assessments of muscle state are largely qualitative, subjective, and poorly standardized across experiments. Here, we developed and validated a continuous, quantitative muscle color metric to objectively capture histolysis progression and functional changes in muscle. We show that this metric robustly tracks variation in muscle color across remodeling stages, including the challenging fully transparent stage, and strongly predicts protein content, mitochondrial abundance, and iron content in a muscle- and trait-specific manner. The reproducibility of these relationships across independent datasets demonstrates the generality and robustness of this approach. By providing a rapid, objective, and biologically informative proxy of muscle state, this framework not only advances the utility of G. lineaticeps as a model for muscle remodeling but also offers a strategy for exploring the cellular dynamics underlying age-related muscle diseases and disorders, addressing an increasing public health concern in aging populations.

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Research summary

The paper claims that a quantitative muscle color metric can objectively capture histolysis progression and functional changes in muscle. This research is relevant as it explores the cellular dynamics underlying muscle remodeling, which could inform strategies for addressing age-related muscle diseases and disorders, a significant concern in aging populations.

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