The C2 domains of dysferlin: roles in membrane localization, Ca2+ signalling and sarcolemmal repair.

Dysferlin is an integral membrane protein of the transverse tubules of skeletal muscle that is mutated or absent in limb girdle muscular dystrophy 2B and Miyoshi myopathy. Here we examine the role of dysferlin's seven C2 domains, C2A through C2G, in membrane repair and Ca2+ release, as well as in targeting dysferlin to the transverse tubules of skeletal muscle. We report that deletion of either domain C2A or C2B inhibits membrane repair completely, whereas deletion of C2C, C2D, C2E, C2F or C2G causes partial loss of membrane repair that is exacerbated in the absence of extracellular Ca2+ . Deletion of C2C, C2D, C2E, C2F or C2G also causes significant changes in Ca2+ release, measured as the amplitude of the Ca2+ transient before or after hypo-osmotic shock and the appearance of Ca2+ waves. Most deletants accumulate in endoplasmic reticulum. Only the C2A domain can be deleted without affecting dysferlin trafficking to transverse tubules, but Dysf-ΔC2A fails to support normal Ca2+ signalling after hypo-osmotic shock. Our data suggest that (i) every C2 domain contributes to repair; (ii) all C2 domains except C2B regulate Ca2+ signalling; (iii) transverse tubule localization is insufficient for normal Ca2+ signalling; and (iv) Ca2+ dependence of repair is mediated by C2C through C2G. Thus, dysferlin's C2 domains have distinct functions in Ca2+ signalling and sarcolemmal membrane repair and may play distinct roles in skeletal muscle. KEY POINTS: Dysferlin, a transmembrane protein containing seven C2 domains, C2A through C2G, concentrates in transverse tubules of skeletal muscle, where it stabilizes voltage-induced Ca2+ transients and participates in sarcolemmal membrane repair. Each of dysferlin's C2 domains except C2B regulate Ca2+ signalling. Localization of dysferlin variants to the transverse tubules is not sufficient to support normal Ca2+ signalling or membrane repair. Each of dysferlin's C2 domains contributes to sarcolemmal membrane repair. The Ca2+ dependence of membrane repair is mediated by C2C through C2G. Dysferlin's C2 domains therefore have distinct functions in Ca2+ signalling and sarcolemmal membrane repair.

Bootstrapping language acquisition.

The semantic bootstrapping hypothesis proposes that children acquire their native language through exposure to sentences of the language paired with structured representations of their meaning, whose component substructures can be associated with words and syntactic structures used to express these concepts. The child's task is then to learn a language-specific grammar and lexicon based on (probably contextually ambiguous, possibly somewhat noisy) pairs of sentences and their meaning representations (logical forms). Starting from these assumptions, we develop a Bayesian probabilistic account of semantically bootstrapped first-language acquisition in the child, based on techniques from computational parsing and interpretation of unrestricted text. Our learner jointly models (a) word learning: the mapping between components of the given sentential meaning and lexical words (or phrases) of the language, and (b) syntax learning: the projection of lexical elements onto sentences by universal construction-free syntactic rules. Using an incremental learning algorithm, we apply the model to a dataset of real syntactically complex child-directed utterances and (pseudo) logical forms, the latter including contextually plausible but irrelevant distractors. Taking the Eve section of the CHILDES corpus as input, the model simulates several well-documented phenomena from the developmental literature. In particular, the model exhibits syntactic bootstrapping effects (in which previously learned constructions facilitate the learning of novel words), sudden jumps in learning without explicit parameter setting, acceleration of word-learning (the "vocabulary spurt"), an initial bias favoring the learning of nouns over verbs, and one-shot learning of words and their meanings. The learner thus demonstrates how statistical learning over structured representations can provide a unified account for these seemingly disparate phenomena.