Birefringence Imaging Directly Reveals Architectural Dynamics of Filamentous Actin in Living Growth ConesV⃞

We have investigated the dynamic behavior of cytoskeletal fine structure in the lamellipodium of nerve growth cones using a new type of polarized light microscope (the Pol-Scope). Pol-Scope images display with exquisite resolution and definition birefringent fine structures, such as filaments and membranes, without having to treat the cell with exogenous dyes or fluorescent labels. Furthermore, the measured birefringence of protein fibers in the thin lamellipodial region can be interpreted in terms of the number of filaments in the bundles. We confirmed that birefringent fibers are actin-based using conventional fluorescence-labeling methods. By recording movies of time-lapsed Pol-Scope images, we analyzed the creation and dynamic composition of radial fibers, filopodia, and intrapodia in advancing growth cones. The strictly quantitative information available in time-lapsed Pol-Scope images confirms previously deduced behavior and provides new insight into the architectural dynamics of filamentous actin.

Thermodynamic parameters for the helix-coil transition of oligopeptides: molecular dynamics simulation with the peptide growth method.

The helix-coil transition equilibrium of polypeptides in aqueous solution was studied by molecular dynamics simulation. The peptide growth simulation method was introduced to generate dynamic models of polypeptide chains in a statistical (random) coil or an alpha-helical conformation. The key element of this method is to build up a polypeptide chain during the course of a molecular transformation simulation, successively adding whole amino acid residues to the chain in a predefined conformation state (e.g., alpha-helical or statistical coil). Thus, oligopeptides of the same length and composition, but having different conformations, can be incrementally grown from a common precursor, and their relative conformational free energies can be calculated as the difference between the free energies for growing the individual peptides. This affords a straightforward calculation of the Zimm-Bragg sigma and s parameters for helix initiation and helix growth. The calculated sigma and s parameters for the polyalanine alpha-helix are in reasonable agreement with the experimental measurements. The peptide growth simulation method is an effective way to study quantitatively the thermodynamics of local protein folding.

Variation in per capita interaction strength: Thresholds due to nonlinear dynamics and nonequilibrium conditions

I measured the strength of interaction between a marine herbivore and its growing resource over a realistic range of absolute and relative abundances. The herbivores (hermit crabs: Pagurus spp.) have slow and/or weak functional and numerical responses to epiphytic diatoms (Isthmia nervosa), which show logistic growth in the absence of consumers. By isolating this interaction in containers in the field, I mimicked many of the physical and biological variables characteristic of the intertidal while controlling the densities of focal species. The per capita effects of consumers on the population dynamics of their resource (i.e., interaction strength) were defined by using the relationship between hermit crab density and proportional change in the resource. When this relationship is fit by a Weibull function, a single parameter distinguishes constant interaction strength from one that varies as a function of density. Constant interaction strength causes the proportion of diatoms to fall linearly or proportionally as hermit crab density increases whereas per capita effects that increase with density cause an accelerating decline. Although many mathematical models of species interactions assume linear dynamics and invariant parameters, at least near equilibrium, the per capita effects of hermit crabs on diatoms varied substantially, apparently crossing a threshold from weak to strong when consumption exceeded resource production. This threshold separates a domain of coexistence from one of local extinction of the resource. Such thresholds may help explain trophic cascades, resource compensation, and context-dependent interaction strengths, while indicating a way to predict trophic effects, despite nonlinearities, as a function of vital rates.

Modeling the dynamics of human hair cycles by a follicular automaton

The hair follicle cycle successively goes through the anagen, catagen, telogen, and latency phases, which correspond, respectively, to hair growth, arrest, shedding, and absence before a new anagen phase is initiated. Experimental observations collected over a period of 14 years in a group of 10 male volunteers, alopecic and nonalopecic, allowed us to determine the characteristics of scalp hair follicle cycles. On the basis of these observations, we propose a follicular automaton model to simulate the dynamics of human hair cycles. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states anagen, telogen, and latency, and the subsequent return to anagen. The transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a variance. The follicular automaton model accounts both for the dynamical transitions observed in a single follicle and for the behavior of an ensemble of independently cycling follicles. Thus, the model successfully reproduces the evolution of the fractions of follicle populations in each of the three phases, which fluctuate around steady-state or slowly drifting values. We apply the follicular automaton model to the study of spatial patterns of follicular growth that result from a spatially heterogeneous distribution of parameters such as the mean duration of anagen phase. When considering that follicles die or miniaturize after going through a critical number of successive cycles, the model can reproduce the evolution to hair patterns similar to well known types of diffuse or androgenetic alopecia.

Spindle Dynamics and the Role of γ-Tubulin in Early Caenorhabditis elegans EmbryosV⃞

γ-Tubulin is a ubiquitous and highly conserved component of centrosomes in eukaryotic cells. Genetic and biochemical studies have demonstrated that γ-tubulin functions as part of a complex to nucleate microtubule polymerization from centrosomes. We show that, as in other organisms, Caenorhabditis elegans γ-tubulin is concentrated in centrosomes. To study centrosome dynamics in embryos, we generated transgenic worms that express GFP::γ-tubulin or GFP::β-tubulin in the maternal germ line and early embryos. Multiphoton microscopy of embryos produced by these worms revealed the time course of daughter centrosome appearance and growth and the differential behavior of centrosomes destined for germ line and somatic blastomeres. To study the role of γ-tubulin in nucleation and organization of spindle microtubules, we used RNA interference (RNAi) to deplete C. elegans embryos of γ-tubulin. γ-Tubulin (RNAi) embryos failed in chromosome segregation, but surprisingly, they contained extensive microtubule arrays. Moderately affected embryos contained bipolar spindles with dense and long astral microtubule arrays but with poorly organized kinetochore and interpolar microtubules. Severely affected embryos contained collapsed spindles with numerous long astral microtubules. Our results suggest that γ-tubulin is not absolutely required for microtubule nucleation in C. elegans but is required for the normal organization and function of kinetochore and interpolar microtubules.

Dynamics of maize endosperm development and DNA endoreduplication.

Endosperm development in Zea mays is characterized by a period of intense mitotic activity followed by a period in which mitosis is essentially eliminated and the cell cycle becomes one of alternating S and G phases, leading to endoreduplication of the nuclear DNA. The endosperm represents a significant contribution to the grain yield of maize; thus, methods that facilitate the study of cellular kinetics may be useful in discerning cellular and molecular components of grain yield. Two mathematical models have been developed to describe the kinetics of endosperm growth. The first describes the kinetics of mitosis during endosperm development; the second describes the kinetics of DNA endoreduplication during endosperm development. The mitotic model is a modification of standard growth curves. The endoreduplication model is composed of six differential equations that represent the progression of nuclei from one DNA content to another during the endoreduplication process. Total nuclei number per endosperm and the number of 3C, 6C, 12C, 24C, 48C, and 96C nuclei per endosperm (C is the haploid DNA content per nucleus) for inbred W64A from 8 to 18 days after pollination were determined by flow cytometry. The results indicate that the change in number of nuclei expressed as a function of the number of days after pollination is the same from one yearly crop to another. These data were used in the model to determine the endosperm growth rate, the maximum nuclei number per endosperm, and transition rates from one C value to the next higher C value. The kinetics of endosperm development are reasonably well represented by the models. Thus, the models provide a means to quantify the complex pattern of endosperm development.