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Abstract
In dense biofilm settings, the bacterium Myxococcus xanthus exhibits a remarkable repertoireof collective multi-cellular dynamics, including both rippling wave motion and aggregate formation,
which are inducible by various experimental conditions. In this dissertation, we
explore the emergence of such behavior within a collective continuous-time random walk
model. The model describes the random locomotion of individual cells whose biased random
navigation decisions are conditional upon external cues, i.e., signals, generated by the
ambient cell population. The model is formulated in terms of a recently proposed integral
equation (IE) formalism which directly provides particle and current densities that are
already averaged over the entire space of all random trajectories, without requiring the generation
of large random trajectory samples, in contrast to agent-based simulation approaches.
Essential to our modeling approach is the incorporation of experimentally derived data bases
of random trajectory components and their associated local cues generated by the ambient
cell population. These data bases are the crucial input to construct the navigational Markov
chain transition probability which defines our random walk model. Assuming strong nematic
cell alignment, the model is reduced to one dimension (1D). Both total and partial, left- and
right-moving cell densities are explored as possible external signals which bias the 1D cellular
random walks, along the population's local nematic alignment axis. Two experimental data
bases are examined as model inputs: a rippling data base (RDB), from a rippling experiment,
and an aggregation data base (ADB), from an aggregation experiment. The model
solutions are very sensitive to even small input parameter changes and exhibit a wide, diverse
range of collective dynamical patterns, including multiple variants of both rippling and
aggregation behaviors. The model results are qualitatively consistent with the underlying
experiments, in that rippling is seen predominantly in RDB-derived model results, whereas
aggregation is predominant in ADB-derived results. Consistent with experiments, examples
of co-occurrence of both aggregation and rippling wave activity is found. Exotic, heretofore
unobserved patterns are also reported, including a pattern we termed "anti-rippling",
where local cell density depletions, rather than density accumulations, perform coordinated
rippling-type wave motions.