Compensatory caspase activation in MPP+-induced cell death in dopaminergic neurons

Many have hypothesized that cell death in Parkinsons disease is via apoptosis and, specifically, by the mitochondrial-mediated apoptotic pathway. We tested this hypothesis using a mouse dopaminergic cell line of mesencephalic origin, MN9D, challenged with the Parkinsonism-causing neurotoxin MPP⁺ (1-methyl-4-phenylpyridinium ion). Apoptosis was the main mode of cell death when the cells were subjected to MPP⁺ treatment under serum-free conditions for 24 h. Caspase-3 and caspase-9, however, were not activated, thus indicating the existence of alternate or compensatory cell death pathway(s) in dopaminergic neuronal cells. Using caspase inhibitors, we demonstrated that these pathways involve caspase-2, –8, –6 and –7. A time-course study indicated that activation of caspase-2 and –8 occurred upstream of caspase-6 and caspase-7. Upon MPP⁺ challenge, the apoptosis-inducing factor was translocated from the mitochondria into the MN9D cytosol and nucleus. These results suggest the existence of alternative apoptotic pathways in dopaminergic neurons.Received 20 September 2004; received after revision 5 November 2004; accepted 22 November 2004     

Statistical tests on two characteristics of the shapes of cluster diagrams

A cluster diagram is a rooted planar tree that depicts the hierarchical agglomeration of objects into groups of increasing size. On the null hypothesis that at each stage of the clustering procedure all possible joins are equally probable, we derive the probability distributions for two properties of these diagrams: (1)S, the number of single objects previously ungrouped that are joined in the final stages of clustering, and (2)m _k, the number of groups ofk+1 objects that are formed during the process. Ecological applications of statistical tests for these properties are described and illustrated with data from weed communities of Saskatchewan fields.This work was supported by the Natural Sciences and Engineering Research Council of Canada.     

Programmable and autonomous computing machine made of biomolecules.

Devices that convert information from one form into another according to a definite procedure are known as automata. One such hypothetical device is the universal Turing machine, which stimulated work leading to the development of modern computers. The Turing machine and its special cases, including finite automata, operate by scanning a data tape, whose striking analogy to information-encoding biopolymers inspired several designs for molecular DNA computers. Laboratory-scale computing using DNA and human-assisted protocols has been demonstrated, but the realization of computing devices operating autonomously on the molecular scale remains rare. Here we describe a programmable finite automaton comprising DNA and DNA-manipulating enzymes that solves computational problems autonomously. The automaton's hardware consists of a restriction nuclease and ligase, the software and input are encoded by double-stranded DNA, and programming amounts to choosing appropriate software molecules. Upon mixing solutions containing these components, the automaton processes the input molecule via a cascade of restriction, hybridization and ligation cycles, producing a detectable output molecule that encodes the automaton's final state, and thus the computational result. In our implementation 1012 automata sharing the same software run independently and in parallel on inputs (which could, in principle, be distinct) in 120 microl solution at room temperature at a combined rate of 109 transitions per second with a transition fidelity greater than 99.8%, consuming less than 10-10 W.     

Crystal structure of the β2 adrenergic receptor-Gs protein complex

G protein-coupled receptors (GPCRs) are responsible for the majority of cellular responses to hormones and neurotransmitters as well as the senses of sight, olfaction and taste. The paradigm of GPCR signalling is the activation of a heterotrimeric GTP binding protein (G protein) by an agonist-occupied receptor. The β(2) adrenergic receptor (β(2)AR) activation of Gs, the stimulatory G protein for adenylyl cyclase, has long been a model system for GPCR signalling. Here we present the crystal structure of the active state ternary complex composed of agonist-occupied monomeric β(2)AR and nucleotide-free Gs heterotrimer. The principal interactions between the β(2)AR and Gs involve the amino- and carboxy-terminal α-helices of Gs, with conformational changes propagating to the nucleotide-binding pocket. The largest conformational changes in the β(2)AR include a 14 ? outward movement at the cytoplasmic end of transmembrane segment 6 (TM6) and an α-helical extension of the cytoplasmic end of TM5. The most surprising observation is a major displacement of the α-helical domain of Gαs relative to the Ras-like GTPase domain. This crystal structure represents the first high-resolution view of transmembrane signalling by a GPCR.     

Taming theory with thought experiments: Understanding and scientific progress

I claim that one way thought experiments contribute to scientific progress is by increasing scientific understanding. Understanding does not have a currently accepted characterization in the philosophical literature, but I argue that we already have ways to test for it. For instance, current pedagogical practice often requires that students demonstrate being in either or both of the following two states: 1) Having grasped the meaning of some relevant theory, concept, law or model, 2) Being able to apply that theory, concept, law or model fruitfully to new instances. Three thought experiments are presented which have been important historically in helping us pass these tests, and two others that cause us to fail. Then I use this operationalization of understanding to clarify the relationships between scientific thought experiments, the understanding they produce, and the progress they enable. I conclude that while no specific instance of understanding (thus conceived) is necessary for scientific progress, understanding in general is.     

Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets

We present the first analysis of the human proteome with regard to interactions between proteins. We also compare the human interactome with the available interaction datasets from yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans) and fly (Drosophila melanogaster). Of >70,000 binary interactions, only 42 were common to human, worm and fly, and only 16 were common to all four datasets. An additional 36 interactions were common to fly and worm but were not observed in humans, although a coimmunoprecipitation assay showed that 9 of the interactions do occur in humans. A re-examination of the connectivity of essential genes in yeast and humans indicated that the available data do not support the presumption that the number of interaction partners can accurately predict whether a gene is essential. Finally, we found that proteins encoded by genes mutated in inherited genetic disorders are likely to interact with proteins known to cause similar disorders, suggesting the existence of disease subnetworks. The human interaction map constructed from our analysis should facilitate an integrative systems biology approach to elucidating the cellular networks that contribute to health and disease states.