Communications BiologyMolecular BiologyPeer-reviewed journal article
Multi-omics Insight into Cardiac Myofibril Remodeling in Post-Prandial Burmese Pythons
Thomas G. MartiniD, Lorena Suarez-ArtilesiD, Kathleen C. WoulfeiD, Elise Gerlach MelhedegaardiD, Yuxiao TaniD, Dakota R. HuntiD, Bruce E. KirkpatrickiD, Lia Nguyen, Joseph Lee, Isabella Laskey, Kristi S. AnsethiD, Julien OchalaiD, Michael GotthardtiD, Philipp MertinsiD, Leslie Anne LeinwandiD
Abstract
Burmese pythons exhibit rapid cardiac remodeling in response to a dramatic increase in metabolic rate during digestion. Here, we performed single-myofibril mechanics measurements and myosin heavy chain metabolic assays to evaluate the impact of feeding on the cardiomyocyte sarcomere - the fundamental molecular unit of muscle contraction - using two experimental paradigms: normal feeding (one meal per month) and frequent feeding (eight meals per month). Myofibril tension and rate of relaxation increased during digestion in both paradigms, while frequent feeding was further associated with slower myofibril activation kinetics and faster myosin heavy chain ATP turnover. To identify molecular changes at the sarcomere and gain potential mechanistic insight, we performed multi-omics analyses. RNA sequencing identified increased expression of some sarcomere genes during digestion; however, proteomics analysis suggested a delay in sarcomere protein synthesis at the peak of remodeling, as expression of many sarcomere proteins decreased. Analysis of post-translational modifications (ubiquitinomics, phospho-proteomics, acetylomics) identified hundreds of significantly regulated sites on sarcomere proteins during digestion, including many on the tension-regulating titin and myosin heavy chain proteins. Our results detail the molecular underpinnings of cardiac remodeling in digesting Burmese pythons and suggest that natures solution for rapidly increasing cardiac contractility is a post-translational sarcomere tuning program.
- organism: non-human primate
- assay: bulk RNA-seq
- assay: proteomics
- research focus: gene regulatory network inference
- approach: statistical model
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