Biomedical Engineering Reference
In-Depth Information
2.6 Conclusions
The underlying dynamics of numerous molecular components determine be-
havior at the cellular level and dictate properties such as cell shape and
speed. Understanding the mechanisms responsible for this remarkable self-
organization is a central challenge in cell motility research. Keratocytes are
one of the fastest moving animal cells, and as such are characterized by rapid
dynamics at the molecular level. At the same time, their behavior at the cel-
lular level is remarkably robust, exhibiting nearly constant shape and speed.
This combination makes keratocytes an excellent model system for studying
the nature of large-scale coordination in cell motility. Further work exploring
the natural variation in cell behavior among a population of cells and its cor-
relation with variations in the molecular composition [24], as well as the effect
of various mechanical and molecular perturbations on cellular behavior, will
help elucidate the self-organizational principles underlying cell motility.
The interplay between biochemical processes and mechanical processes
plays a central role in cell motility. The coupling between biochemical and
biophysical processes is evident at all levels of organization. Molecular pro-
cesses such as actin polymerization or adhesion formation are dependent on
the mechanical forces acting on the molecules. At the same time, biochemi-
cal processes and regulation determine the mechanical properties of cellular
subsystems such as the cell membrane and the cytoskeleton. In addition, me-
chanical coupling provides the means for rapid large-scale coordination. For
example, membrane tension effectively couples biochemical processes at the
front and at the rear of the cell. Mechanical coordination is more apparent in
keratocytes, in which motility is rapid and not dependent on external cues.
The relative role of such mechanical coordination and biochemical signaling
for large-scale coordination in keratocyte motility remains to be determined.
Understanding how motility at the cellular level arises from the action of
numerous interacting molecular components is inherently dicult and non-
intuitive. This emphasizes the role of mathematical modeling as a means for
integrating the large amounts of experimental data into a systematic under-
standing of this process. Indeed, cell motility has been a subject of mathe-
matical modeling for a long time. These studies have contributed substantially
to our understanding of the process of cell motility, but until recently most
of them focused on individual reactions or modules involved in cell motil-
ity [21, 55, 93, 108, 109]. As noted above, quantitative understanding of cell
motility must involve an integrative view of the cell as a whole. Initial at-
tempts to model motility at the cellular level were mostly phenomenological
[39]. However, in the last few years, several models have been put forth that
attempt to link the physical and biochemical understanding at the molecular
level with a cellular level description [22, 23, 24]. While a complete model that
quantitatively accounts for the spatio-temporal dynamics of a moving cell is
still lacking, progress toward this goal proceeds both by more rigorous and
quantitative experimental measurements of the biochemical and biophysical
