The lepidopteran mitochondrial control region: structure and evolution

For several species of lepidoptera, most of the approximately 350-bp mitochondrial control-region sequences were determined. Six of these species are in one genus, Jalmenus; are closely related; and are believed to have undergone recent rapid speciation. Recent speciation was supported by the observation of low interspecific sequence divergence. Thus, no useful phylogeny could be constructed for the genus. Despite a surprising conservation of control-region length, there was little conservation of primary sequences either among the three lepidopteran genera or between lepidoptera and Drosophila. Analysis of secondary structure indicated only one possible feature in common--inferred stem loops with higher-than-random folding energies-- although the positions of the structures in different species were unrelated to regions of primary sequence similarity. We suggest that the conserved, short length of control regions is related to the observed lack of heteroplasmy in lepidopteran mitochondrial genomes. In addition, determination of flanking sequences for one Jalmenus species indicated (i) only weak support for the available model of insect 12S rRNA structure and (ii) that tRNA translocation is a frequent event in the evolution of insect mitochondrial genomes.      

Ancient Evolutionary Trade-Offs between Yeast Ploidy States

The number of chromosome sets contained within the nucleus of eukaryotic organisms is a fundamental yet evolutionarily poorly characterized genetic variable of life. Here, we mapped the impact of ploidy on the mitotic fitness of baker''s yeast and its never domesticated relative Saccharomyces paradoxus across wide swaths of their natural genotypic and phenotypic space. Surprisingly, environment-specific influences of ploidy on reproduction were found to be the rule rather than the exception. These ploidy–environment interactions were well conserved across the 2 billion generations separating the two species, suggesting that they are the products of strong selection. Previous hypotheses of generalizable advantages of haploidy or diploidy in ecological contexts imposing nutrient restriction, toxin exposure, and elevated mutational loads were rejected in favor of more fine-grained models of the interplay between ecology and ploidy. On a molecular level, cell size and mating type locus composition had equal, but limited, explanatory power, each explaining 12.5%–17% of ploidy–environment interactions. The mechanism of the cell size–based superior reproductive efficiency of haploids during Li⁺ exposure was traced to the Li⁺ exporter ENA. Removal of the Ena transporters, forcing dependence on the Nha1 extrusion system, completely altered the effects of ploidy on Li⁺ tolerance and evoked a strong diploid superiority, demonstrating how genetic variation at a single locus can completely reverse the relative merits of haploidy and diploidy. Taken together, our findings unmasked a dynamic interplay between ploidy and ecology that was of unpredicted evolutionary importance and had multiple molecular roots.     

Statistical epistasis is a generic feature of gene regulatory networks

Functional dependencies between genes are a defining characteristic of gene networks underlying quantitative traits. However, recent studies show that the proportion of the genetic variation that can be attributed to statistical epistasis varies from almost zero to very high. It is thus of fundamental as well as instrumental importance to better understand whether different functional dependency patterns among polymorphic genes give rise to distinct statistical interaction patterns or not. Here we address this issue by combining a quantitative genetic model approach with genotype-phenotype models capable of translating allelic variation and regulatory principles into phenotypic variation at the level of gene expression. We show that gene regulatory networks with and without feedback motifs can exhibit a wide range of possible statistical genetic architectures with regard to both type of effect explaining phenotypic variance and number of apparent loci underlying the observed phenotypic effect. Although all motifs are capable of harboring significant interactions, positive feedback gives rise to higher amounts and more types of statistical epistasis. The results also suggest that the inclusion of statistical interaction terms in genetic models will increase the chance to detect additional QTL as well as functional dependencies between genetic loci over a broad range of regulatory regimes. This article illustrates how statistical genetic methods can fruitfully be combined with nonlinear systems dynamics to elucidate biological issues beyond reach of each methodology in isolation.     

CD4<Superscript>+</Superscript> T cells kill Id<Superscript>+</Superscript> B-lymphoma cells: FasLigand-Fas interaction is dominant in vitro but is redundant in vivo

B-lymphoma cells express a highly tumor-specific antigen, monoclonal Ig, which is a promising target for immunotherapy. Previous work has demonstrated that B-lymphoma cells spontaneously process their endogenous monoclonal Ig and present variable (V) region peptides (Id-peptides) on their MHC class II molecules to CD4⁺ T cells. Id-specific CD4⁺ T cells protect mice against B-lymphoma cells in the absence of anti-idiotypic antibodies. The molecular mechanism by which Id-specific CD4⁺ T cells kill B-lymphoma cells is hitherto unknown. We here demonstrate in an Id-specific T-cell receptor (TCR)–transgenic mouse model that Id-specific CD4⁺ T cells induce apoptosis of Fas⁺ B-lymphoma cells in vitro by FasLigand (FasL)–Fas interaction. Moreover, the rare B lymphomas that had escaped rejection in TCR-transgenic mice had down-regulated their sensitivity to Fas-mediated apoptosis. Although these results suggest that FasL-Fas interaction is important, Id-specific CD4⁺ T cells could eliminate Id⁺ B-lymphoma cells in vivo by other mechanisms, since three independent ways of blocking FasL-Fas–mediated killing failed to abrogate tumor protection in TCR-transgenic mice. These results suggest that there are several redundant pathways by which Id-specific CD4⁺ T cells eliminate Id⁺ B-lymphoma cells in vivo, of which FasL-Fas interaction is only one.Supported by grants from the Norwegian Cancer Society, the Research Council of Norway, and the Multiple Myeloma Research Foundation.     

Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

Background

Network inference methods reconstruct mathematical models of molecular or genetic networks directly from experimental data sets. We have previously reported a mathematical method which is exclusively data-driven, does not involve any heuristic decisions within the reconstruction process, and deliveres all possible alternative minimal networks in terms of simple place/transition Petri nets that are consistent with a given discrete time series data set.

Results

We fundamentally extended the previously published algorithm to consider catalysis and inhibition of the reactions that occur in the underlying network. The results of the reconstruction algorithm are encoded in the form of an extended Petri net involving control arcs. This allows the consideration of processes involving mass flow and/or regulatory interactions. As a non-trivial test case, the phosphate regulatory network of enterobacteria was reconstructed using in silico-generated time-series data sets on wild-type and in silico mutants.

Conclusions

The new exact algorithm reconstructs extended Petri nets from time series data sets by finding all alternative minimal networks that are consistent with the data. It suggested alternative molecular mechanisms for certain reactions in the network. The algorithm is useful to combine data from wild-type and mutant cells and may potentially integrate physiological, biochemical, pharmacological, and genetic data in the form of a single model.     

From sequence to consequence and back

The genotype–phenotype relation is at the core of theoretical biology. It is argued why a mathematically based explanatory structure of this relation is in principle possible, and why it has to embrace both sequence to consequence and consequence to sequence phenomena. It is suggested that the primary role of DNA in the chain of causality is that its presence allows a living system to induce perturbations of its own dynamics as a function of its own system state or phenome, i.e. it capacitates living systems to self-transcend beyond those morphogenetic limits that exist for non-living open physical systems in general. Dynamic models bridging genotypes with phenotypic variation in a causally cohesive way are shown to provide explanations of genetic phenomena that go well beyond the explanatory domains of statistically oriented genetics theory construction. A theory originally proposed by Rupert Riedl, which implies that the morphospace that is reachable by the standing genetic variation in a population is quite restricted due to systemic constraints, is shown to provide a foundation for a mathematical conceptualization of numerous evolutionary phenomena associated with the phenotypic consequence to sequence relation. The paper may be considered a call to arms to mathematicians and the mathematically inclined to rise to the challenge of developing new formalisms capable of dealing with the deep defining characteristics of living systems.     

A methodological basis for description and analysis of systems with complex switch-like interactions

 A wide range of complex systems appear to have switch-like interactions, i.e. below (or above) a certain threshold x has no or little influence on y, while above (or below) this threshold the effect of x on y saturates rapidly to a constant level. Switching functions are frequently described by sigmoid functions or combinations of these. Within the context of ordinary differential equations we present a very general methodological basis for designing and analysing models involving complicated switching functions together with any other non-linearities. A procedure to determine position and stability properties of all stationary points lying close to a threshold for one or several variables, so-called singular stationary points, is developed. Such points may represent homeostatic states in models, and are therefore of considerable interest. The analysis provides a profound insight into the generic effects of steep sigmoid interactions on the dynamics around homeostatic points. It leads to qualitative as well as quantitative predictions without using advanced mathematical methods. Thus, it may have an important heuristic function in connection with numerical simulations aimed at unfolding the predictive potential of realistic models. Received 25 January 1996; received in revised form 29 June 1997