Estimating the probability of initiated cell death before tumor induction

The effects of cell toxicity are known to be inherent in carcinogenesis induced by radiation or chemical carcinogens. The event of cell death precludes tumor induction from occurring. A long standing problem is to estimate the proportion of initiated cells that die before tumor induction. No experimental techniques are currently available for directly gauging the rate of cell death over extended periods of time. The obstacle can be surmounted by newly developed theoretical methods of carcinogenesis modeling. In this paper, we apply such methods to published data on multiple lung tumors in mice receiving different schedules of urethane. Bioassays of this type play an important role in testing environmental chemicals for carcinogenic activity. Our estimates for urethane-induced carcinogenesis show that, unexpectedly, many initiated cells die early in the course of tumor promotion. We present numerical estimates for the probability of initiated cell death for different schedules (and doses) of urethane administration.

Insecticide resistance resulting from an absence of target-site gene product

Genetic changes in insects that lead to insecticide resistance include point mutations and up-regulation/amplification of detoxification genes. Here, we report a third mechanism, resistance caused by an absence of gene product. Mutations of the Methoprene-tolerant (Met) gene of Drosophila melanogaster result in resistance to both methoprene, a juvenile hormone (JH) agonist insecticide, and JH. Previous results have demonstrated a mechanism of resistance involving an intracellular JH binding protein that has reduced ligand affinity in Met flies. We show that a γ-ray induced allele, Met27, completely lacks Met transcript during the insecticide-sensitive period in development. Although Met27 homozygotes have reduced oogenesis, they are viable, demonstrating that Met is not a vital gene. Most target-site resistance genes encode vital proteins and thus have few mutational changes that permit both resistance and viability. In contrast, resistance genes such as Met that encode nonvital insecticide target proteins can have a variety of mutational changes that result in an absence of functional gene product and thus should show higher rates of resistance evolution.

Activation of target-tissue immune-recognition molecules by double-stranded polynucleotides

Abnormal expression of major histocompatibility complex (MHC) class I and class II in various tissues is associated with autoimmune disease. Autoimmune responses can be triggered by viral infections or tissue injuries. We show that the ability of a virus or a tissue injury to increase MHC gene expression is duplicated by any fragment of double-stranded (ds) DNA or dsRNA introduced into the cytoplasm of nonimmune cells. Activation is sequence-independent, is induced by ds polynucleotides as small as 25 bp in length, and is not duplicated by single-stranded polynucleotides. In addition to causing abnormal MHC expression, the ds nucleic acids increase the expression of genes necessary for antigen processing and presentation: proteasome proteins (e.g., LMP2), transporters of antigen peptides; invariant chain, HLA-DM, and the costimulatory molecule B7.1. The mechanism is different from and additive to that of γ-interferon (γIFN), i.e., ds polynucleotides increase class I much more than class II, whereas γIFN increases class II more than class I. The ds nucleic acids also induce or activate Stat1, Stat3, mitogen-activated protein kinase, NF-κB, the class II transactivator, RFX5, and the IFN regulatory factor 1 differently from γIFN. CpG residues are not responsible for this effect, and the action of the ds polynucleotides could be shown in a variety of cell types in addition to thyrocytes. We suggest that this phenomenon is a plausible mechanism that might explain how viral infection of tissues or tissue injury triggers autoimmune disease; it is potentially relevant to host immune responses induced during gene therapy.

Reduced sympathetic innervation after alteration of target cell neurotransmitter phenotype in transgenic mice.

Neurotransmitters play a variety of important roles during nervous system development. In the present study, we hypothesized that neurotransmitter phenotype of both projecting and target cells is an important factor for the final synaptic linkage and its specificity. To test this hypothesis, we used transgenic techniques to convert serotonin/melatonin-producing cells of the pineal gland into cells that also produce dopamine and investigated the innervation of the phenotypically altered target cells. This phenotypic alteration markedly reduced the noradrenergic innervation originating from the superior cervical ganglia. Although the mechanism by which the reduction occurs is presently unknown, quantitative enzyme-linked immunoassay showed the presence of the equivalent amounts of nerve growth factor (NGF) in the control and transgenic pineal glands, suggesting that it occurred in a NGF-independent manner. The results suggest that target neurotransmitter phenotype influences the formation of afferent connections during development.

Calculating the probability of multitaxon evolutionary trees: bootstrappers Gambit.

The reconstruction of multitaxon trees from molecular sequences is confounded by the variety of algorithms and criteria used to evaluate trees, making it difficult to compare the results of different analyses. A global method of multitaxon phylogenetic reconstruction described here, Bootstrappers Gambit, can be used with any four-taxon algorithm, including distance, maximum likelihood, and parsimony methods. It incorporates a Bayesian-Jeffreys'-bootstrap analysis to provide a uniform probability-based criterion for comparing the results from diverse algorithms. To examine the usefulness of the method, the origin of the eukaryotes has been investigated by the analysis of ribosomal small subunit RNA sequences. Three common algorithms (paralinear distances, Jukes-Cantor distances, and Kimura distances) support the eocyte topology, whereas one (maximum parsimony) supports the archaebacterial topology, suggesting that the eocyte prokaryotes are the closest prokaryotic relatives of the eukaryotes.

Estimating the probability for a protein to have a new fold: A statistical computational model

Structural genomics aims to solve a large number of protein structures that represent the protein space. Currently an exhaustive solution for all structures seems prohibitively expensive, so the challenge is to define a relatively small set of proteins with new, currently unknown folds. This paper presents a method that assigns each protein with a probability of having an unsolved fold. The method makes extensive use of protomap, a sequence-based classification, and scop, a structure-based classification. According to protomap, the protein space encodes the relationship among proteins as a graph whose vertices correspond to 13,354 clusters of proteins. A representative fold for a cluster with at least one solved protein is determined after superposition of all scop (release 1.37) folds onto protomap clusters. Distances within the protomap graph are computed from each representative fold to the neighboring folds. The distribution of these distances is used to create a statistical model for distances among those folds that are already known and those that have yet to be discovered. The distribution of distances for solved/unsolved proteins is significantly different. This difference makes it possible to use Bayes' rule to derive a statistical estimate that any protein has a yet undetermined fold. Proteins that score the highest probability to represent a new fold constitute the target list for structural determination. Our predicted probabilities for unsolved proteins correlate very well with the proportion of new folds among recently solved structures (new scop 1.39 records) that are disjoint from our original training set.

Enhancers increase the probability but not the level of gene expression.

We have studied enhancer function in transient and stable expression assays in mammalian cells by using systems that distinguish expressing from nonexpressing cells. When expression is studied in this way, enhancers are found to increase the probability of a construct being active but not the level of expression per template. In stably integrated constructs, large differences in expression level are observed but these are not related to the presence of an enhancer. Together with earlier studies, these results suggest that enhancers act to affect a binary (on/off) switch in transcriptional activity. Although this idea challenges the widely accepted model of enhancer activity, it is consistent with much, if not all, experimental evidence on this subject. We hypothesize that enhancers act to increase the probability of forming a stably active template. When randomly integrated into the genome, enhancers may affect a metastable state of repression/activity, permitting expression in regions that would not permit activity of an isolated promoter.