Genetic instability and clonal expansion

Inactivation of tumor suppressor genes can lead to clonal expansion. We study the evolutionary dynamics of this process and calculate the probability that inactivation of a tumor suppressor gene is preceded by mutations in genes that confer genetic instability. Unstable cells might have a slower rate of clonal expansion than stable cells because of an increased probability of generating lethal mutations or inducing apoptosis. We show that the different growth rates of genetically stable and unstable cells during clonal expansion represent, in general, only a small disadvantage for genetic instability. The intuitive reason for this conclusion is that robust clonal expansion, where cellular birth rates are significantly greater than death rates, occurs on a much faster time scale than waiting for those mutations that allow clonal expansion. Moreover, in special cases where clonal expansion is very slow, genetically unstable cells have a higher probability to accumulate additional mutations during clonal expansion that confer a selective advantage. Clonal expansion represents a major disadvantage for genetic instability only when inactivation of the tumor suppressor gene leads to a very small increase of the cellular reproductive rate that is cancelled by the increased mortality of unstable cells.     

Genetic addiction: selfish gene's strategy for symbiosis in the genome

The evolution and maintenance of the phenomenon of postsegregational host killing or genetic addiction are paradoxical. In this phenomenon, a gene complex, once established in a genome, programs death of a host cell that has eliminated it. The intact form of the gene complex would survive in other members of the host population. It is controversial as to why these genetic elements are maintained, due to the lethal effects of host killing, or perhaps some other properties are beneficial to the host. We analyzed their population dynamics by analytical methods and computer simulations. Genetic addiction turned out to be advantageous to the gene complex in the presence of a competitor genetic element. The advantage is, however, limited in a population without spatial structure, such as that in a well-mixed liquid culture. In contrast, in a structured habitat, such as the surface of a solid medium, the addiction gene complex can increase in frequency, irrespective of its initial density. Our demonstration that genomes can evolve through acquisition of addiction genes has implications for the general question of how a genome can evolve as a community of potentially selfish genes.     

Rho-dependent, Rho kinase-independent inhibitory regulation of Rac and cell migration by LPA1 receptor in Gi-inactivated CHO cells

Lysophosphatidic acid (LPA) is a major serum lysophospholipid that stimulates cell migration in diverse cell types including ovarian cancer cells. We report here that in the absence of Gi function, LPA induces inhibition, rather than stimulation, of cellular Rac activity, lamellipodium formation, and cell migration in response to insulin like growth factor I (IGF-I) in Chinese hamster ovary (CHO) cells, which solely express LPA1 as a LPA receptor. The inhibitory effects of LPA are abrogated by the expression of either Galpha13 C-terminal peptide or C3 toxin pretreatment, but not a Rho kinase inhibitor. Without PTX pretreatment, LPA stimulates Rac and cell migration yet similarly activates Rho, indicating that Rho activation by itself is not sufficient for inhibition of cell migration. Conversely, the expression of a dominant negative Rac mutant sufficiently mimics the LPA inhibition of cell migration. LPA inhibits IGF I-induced Akt activation by only 40% in a manner dependent on Rho kinase. These results demonstrate that inhibition of Gi function converts LPA regulation on Rac and cell migration to an inhibitory mode, which is mediated by G13 and Rho but not Rho kinase, and raise a possibility of Gi as a new therapeutic target for LPA-dependent tumor progression.     

Incorporating an ontogenetic perspective into evolutionary theory of sexual size dimorphism

Sexual size dimorphism (SSD) describes divergent body sizes of adult males and females. While SSD has traditionally been explained by sexual and fecundity selection, recent advances in physiology and developmental biology emphasize that SSD would occur proximately because of sexual differences in ontogenetic growth trajectories (i.e., growth rate and duration). Notably, these ontogenetic traits are subject to energetic or time constraints and thus traded off with fitness components (e.g., survival and reproduction). To elucidate the importance of such ontogenetic trade‐offs in the evolution of SSD, we developed a new theoretical framework by extending quantitative genetic models for the evolution of sexual dimorphism in which we reinterpret the trait as body size and reformulate sex‐specific fitness in size‐dependent manners. More specifically, we assume that higher growth rate or longer growth duration leads to larger body size and higher reproductive success but incurs the cost of lower survivorship or shorter reproduction period. We illustrate how two sexes would optimize ontogenetic growth trajectories in sex‐specific ways and exhibit divergent body sizes. The present framework provides new insights into the evolutionary theory of SSD and predictions for empirical testing.     

Profit sharing and agroforestry: a theoretical study of potential conflicts in managing illegal logging risk in tropical forests

Partnership programs have gained importance in forestry management. In Indonesia, profit sharing and agroforestry are examples of partnership programs between forest managers and local communities. In this paper, we analyze potential conflicts among participants in these programs. First, we derive a recursive formula to determine the future value of a compartment of plantation to the society, which includes both the forest owner and the local community. While trees are young, the land is also used for agriculture, which is an agroforestry program. When there is a high rate of future discounting and a high rate of natural disturbances, the society may find it profitable to continue the agricultural use of the land. Second, we calculate the profit for the forest owner and the local community separately. To prevent illegal logging, the owner shares a fraction of the profit obtained by selling logs with the local people, which is a profit-sharing program. Illegal logging greatly reduces the profit for the forest owner, especially when trees are tall. Illegal logging of old cohorts is harmful to the local people as well. In contrast, illegal logging of young cohorts provides profit to the local people because they will be hired to replant young trees. Our analysis shows an “overlooking period” in which a conflict of interest exists between the forest owner and the local community. We indicate that the overlooking period can be mitigated by coordination of the shared profit and the wage for the workers.     

Mis16 and Mis18 are required for CENP-A loading and histone deacetylation at centromeres

Centromeres contain specialized chromatin that includes the centromere-specific histone H3 variant, spCENP-A/Cnp1. Here we report identification of five fission yeast centromere proteins, Mis14-18. Mis14 is recruited to kinetochores independently of CENP-A, and, conversely, CENP-A does not require Mis14 to associate with centromeres. In contrast, Mis15, Mis16 (strong similarity with human RbAp48 and RbAp46), Mis17, and Mis18 are all part of the CENP-A recruitment pathway. Mis15 and Mis17 form an evolutionarily conserved complex that also includes Mis6. Mis16 and Mis18 form a complex and maintain the deacetylated state of histones specifically in the central core of centromeres. Mis16 and Mis18 are the most upstream factors in kinetochore assembly as they can associate with kinetochores in all kinetochore mutants except for mis18 and mis16, respectively. RNAi knockdown in human cells shows that Mis16 function is conserved as RbAp48 and RbAp46 are both required for localization of human CENP-A.     

Extinction risk of a meta-population: aggregation approach

Aggregation of variables of a complex mathematical model with realistic structure gives a simplified model which is more suitable than the original one when the amount of data for parameter estimation is limited. Here we explore use of a formula derived for a single unstructured population (canonical model) in predicting the extinction time for a population living in multiple habitats. In particular we focus multiple populations each following logistic growth with demographic and environmental stochasticities, and examine how the mean extinction time depends on the migration and environmental correlation. When migration rate and/or environmental correlation are very large or very small, we may express the mean extinction time exactly using the formula with properly modified parameters. When parameters are of intermediate magnitude, we generate a Monte Carlo time series of the population size for the realistic structured model, estimate the "effective parameters" by fitting the time series to the canonical model, and then calculate the mean extinction time using the formula for a single population. The mean extinction time predicted by the formula was close to those obtained from direct computer simulation of structured models. We conclude that the formula for an unstructured single-population model has good approximation capability and can be applicable in estimating the extinction risk of the structured meta-population model for a limited data set.     

Labyrinthine versus straight-striped patterns generated by two-dimensional Turing systems

Striped patterns are often observed on fish skin. Such patterns have been accounted for by reaction-diffusion (RD) Turing-type models, in which two substances can spontaneously form a spatially heterogeneous pattern in a homogeneous field. Among the striped patterns generated by Turing-type models, some are "straight-striped patterns," with many stripes running in parallel, while others are "labyrinthine patterns," in which the stripes often change direction, merge with each other, and frequently branch out. RD models differ in terms of their tendency to generate either labyrinthine or straight-striped patterns. Here, we studied the conditions under which either a labyrinthine or straight-striped pattern would emerge. First, we defined an index for stripe clearness, Sh. Straight-striped patterns (large Sh) are formed if only a narrow range of spatial periods corresponds to an unstable mode. Labyrinthine patterns (small Sh) are formed when a wide range of spatial periods is unstable. More specifically, labyrinthine patterns are formed when the maximum spatial period of unstable modes is more than twice that of the minimum spatial period of unstable modes; otherwise, straight-striped patterns are formed. We then examined RD models with nonlinear reaction terms, including both activator-inhibitor and substrate-depletion models, and we demonstrated that the same conclusions hold with respect to the conditions required for labyrinthine versus straight-striped patterns.