Muscle mechanics from the molecule to organism

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Research Interests:

Structural and mechanical properties of muscle
that coordinate myosin function

Probing myosin kinetics in cells via systems analysis

Applied computational physiology and biophysics


Image adapted from D. Maughan and B. Palmer


Overview

My research efforts combine computational analyses and experimental measurements to identify, characterize, and describe molecular mechanism modulating muscle contraction.  My interdisciplinary training has benefited from many exciting collaborations that motivate an ever evolving set of studies.


Structural and mechanical properties of muscle that coordinate myosin cross-bridge behavior

Vert vs. Invert X-section
 
 Actin (blue) and myosin (red) are the contractile proteins that generate force in muscle cells, comprising one of the most ubiquitous molecular motor systems found in nature. Actin and myosin form thin and thick filaments, respectively.  These filaments are organized in lattice-like configuration within the sarcomere. Multiple proteins must work together to maintain proper architecture and underlying mechanical properties of the muscle filament lattice
(shown here in cross-section) to facilitate normal contraction. My PhD research at University of Washington focused on creating a half-sarcomere representation of the muscle filament lattice in silico.

   I have used this spatially-explicit computational modeling to probe how ensemble behavior of actin-myosin cross-bridges is effected by structural and mechanical characteristics of the muscle filament network.  Simulations have shown:

-- the ratio and arrangement of thick and thin filaments influences cooperative cross-bridge binding

-- energy consumption varies strongly with timing between neural activation and force production

-- apparent rates of cooperative force production slow with diminished stiffness of the myofilament lattice

-- spatial characteristics of thin filament activation in skeletal muscle play the dominant role in cooperative cross-bridge binding

   I envision future applications of this modeling paradigm will illustrate spatial and mechanical mechanisms by which additional sarcomeric proteins modulate normal and dysfunctional muscle contraction.  Applications include specific protein targets that undergo dynamic phosphorylation such as troponin, tropomyosin, myosin regulatory light chain, titin, or myosin binding protein-C or reductions in myosin cycling kinetics due to aging or disease. Back to Top



Mechanical system analysis to measure myosin cross-bridge kinetics in muscle cells

   Many of the mechanisms coordinating cooperative cross-bridge binding that I predicted with computational modeling during 
my PhD arose from a motor system with strain-dependent or load-dependent kinetics.  This behavior implies that fundamental characteristics of muscle, such as force production, power output, and shortening and lengthening, rely upon the way cross-
bridges sense strain and respond to load.  However, strain-dependent myosin kinetics are difficult to measure on the single 
molecule level and cross-bridges work as an ensemble within a highly-ordered lattice filaments in muscle.  Therefore, I have 
been learning and developing mechanical system analysis methods throughout my post-doctoral training at University of Vermont.
I was awarded a postdoctoral fellowship from the National Science Foundation to develop stochastic system analysis methods
to quantify the effect of strain on myosin cycling kinetics in muscle fibers.  These methods enabled the first measure of strain-dependent myosin attachment time in a muscle fiber during periods of linear shortening and lengthening. Ongoing experimental 
and computational studies are building on this analysis technique to investigate the molecular basis of power output in oscillatory muscle systems such as insect-flight and cardiac muscles. Back to Top


Applied computational physiology and biophysics

Norman et al. 2002

   While my training primarily has primarily focused on muscle mechanics at the molecular and cellular level, I have a broad appreciation for the powerful role that physics and mathematics can play in quantitative descriptions of biological system behavior.  The computational tools I employ are applicable to studying a wide range of network behavior in biological systems—from genomes to ecosystems.



My earliest training in computational biophysics.
Image credit: Figure 1 Norman et al. 2003.


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