Detection of sequential polyubiquitylation on a millisecond timescale

The pathway by which ubiquitin chains are generated on substrate through a cascade of enzymes consisting of an E1, E2 and E3 remains unclear. Multiple distinct models involving chain assembly on E2 or substrate have been proposed. However, the speed and complexity of the reaction have precluded direct experimental tests to distinguish between potential pathways. Here we introduce new theoretical and experimental methodologies to address both limitations. A quantitative framework based on product distribution predicts that the really interesting new gene (RING) E3 enzymes SCF^(Cdc4) and SCF^(β-TrCP) work with the E2 Cdc34 to build polyubiquitin chains on substrates by sequential transfers of single ubiquitins. Measurements with millisecond time resolution directly demonstrate that substrate polyubiquitylation proceeds sequentially. Our results present an unprecedented glimpse into the mechanism of RING ubiquitin ligases and illuminate the quantitative parameters that underlie the rate and pattern of ubiquitin chain assembly

Dynamics and calcium association to the N-terminal regulatory domain of human cardiac troponin C: a multiscale computational study.

Troponin C (TnC) is an important regulatory molecule in cardiomyocytes. Calcium binding to site II in TnC initiates a series of molecular events that result in muscle contraction. The most direct change upon Ca(2+) binding is an opening motion of the molecule that exposes a hydrophobic patch on the surface allowing for Troponin I to bind. Molecular dynamics simulations were used to elucidate the dynamics of this crucial protein in three different states: apo, Ca(2+)-bound, and Ca(2+)-TnI-bound. Dynamics between the states are compared, and the Ca(2+)-bound system is investigated for opening motions. On the basis of the simulations, NMR chemical shifts and order parameters are calculated and compared with experimental observables. Agreement indicates that the simulations sample the relevant dynamics of the system. Brownian dynamics simulations are used to investigate the calcium association of TnC. We find that calcium binding gives rise to correlative motions involving the EF hand and collective motions conducive of formation of the TnI-binding interface. We furthermore indicate the essential role of electrostatic steering in facilitating diffusion-limited binding of Ca(2+)

Controlling and characterizing microstructure in lithium-ion battery electrodes

Lithium-ion battery electrodes consist of a functional composite containing electroactive solid particles where redox reactions occur, conductive additives, a polymeric binder to provide mechanical support, and void regions filled with electrolyte during cell fabrication. While much of the focus in the battery materials field is on the chemistry of the electroactive materials that dictate the fundamental limits on the energy density of the cell, the morphology of the electroactive materials and the microstructure of the electrode also have a significant influence on the resulting electrochemical properties. An example of an electrode microstructure is shown in Figure 1. For certain operating conditions and electrode architectures the transport of ions through the electrode microstructure can limit the performance of the cell, which means that controlling and understanding the microstructure can open up battery designs that improve the performance and energy density at the cell level. This strategy should be broadly applicable to multiple battery materials. In this paper, we will describe progress in our lab in synthesizing battery electroactive particles of controllable morphology and processing these particles into composite electrodes. The size, shape, and polydispersity of the particles results in different packing in the electrode and thus different electrode microstructures, while the active material composition is kept constant. Characterization of these electrodes to elucidate microstructure effects on electrochemical performance will also be described, in particular how different transport limitations become relevant for different electrode geometries. Measurements of the tortuosity of the electrodes will be detailed, and the conditions will be determined where transport is limited either within the electroactive particles or through the electrode microstructure. The electrodes described in this paper are functional composites for energy storage applications which is of relevance to the topical theme of this conference. Please click Additional Files below to see the full abstract

Toward a model of multiple paths to language learning: response to commentaries

Language learning, while seemingly effortless for young learners, is a complex process involving many interacting pieces, both within the child and in their language-learning environments, which can result in unique language learning trajectories and outcomes. How does the brain adjust to or accommodate the myriad variations that occur during this developmental process. How does it adapt and change over time? In our review, we proposed that the timing, quantity, and quality of children's early language experiences, particularly during an early sensitive period for the acquisition of phonology, shape the establishment of neural phonological representations that are used to establish and support phonological working memory (PWM). The efficiency of the PWM system in turn, we argued, influences the acquisition and processing of more complex aspects of language. In brief, we proposed that experience modulates later language outcomes through its early effects on PWM. We supported this claim by reviewing research from several unique groups of language learners who experience delayed exposure to language (children with cochlear implants [CI] or internationally adopted [IA] children, and children with either impoverished [signing deaf children with hearing parents)] or enriched [bilingual] early language experiences). By comparing PWM and language outcomes in these groups, we sought to highlight general patterns in language development that emerge based on variation in early language exposure. Moving forward, we also proposed that the language acquisition patterns in these groups, and others, can be used to understand how variability in early language input might affect the neural systems supporting language development and how this might affect language learning itself

Exploring the DNA-recognition potential of homeodomains

The recognition potential of most families of DNA-binding domains (DBDs) remains relatively unexplored. Homeodomains (HDs), like many other families of DBDs, display limited diversity in their preferred recognition sequences. To explore the recognition potential of HDs, we utilized a bacterial selection system to isolate HD variants, from a randomized library, that are compatible with each of the 64 possible 3′ triplet sites (i.e., TAANNN). The majority of these selections yielded sets of HDs with overrepresented residues at specific recognition positions, implying the selection of specific binders. The DNA-binding specificity of 151 representative HD variants was subsequently characterized, identifying HDs that preferentially recognize 44 of these target sites. Many of these variants contain novel combinations of specificity determinants that are uncommon or absent in extant HDs. These novel determinants, when grafted into different HD backbones, produce a corresponding alteration in specificity. This information was used to create more explicit HD recognition models, which can inform the prediction of transcriptional regulatory networks for extant HDs or the engineering of HDs with novel DNA-recognition potential. The diversity of recovered HD recognition sequences raises important questions about the fitness barrier that restricts the evolution of alternate recognition modalities in natural systems

Variations in phonological working memory: linking early language experiences and language learning outcomes

In order to build complex language from perceptual input, children must have access to a powerful information processing system that can analyze, store, and use regularities in the signal to which the child is exposed. In this article, we propose that one of the most important parts of this underlying machinery is the linked set of cognitive and language processing components that comprise the child's developing working memory (WM). To examine this hypothesis, we explore how variations in the timing, quality, and quantity of language input during the earliest stages of development are related to variations in WM, especially phonological WM (PWM), and in turn language learning outcomes. In order to tease apart the relationships between early language experience, WM, and language development, we review research findings from studies of groups of language learners who clearly differ with respect to these aspects of input. Specifically, we consider the development of PWM in children with delayed exposure to language, that is, children born profoundly deaf and exposed to oral language following cochlear implantation and internationally adopted children who have delayed exposed to the adoption language; children who experience impoverished language input, that is, children who experience early bouts of otitis media and signing deaf children born to nonsigning hearing parents; and children with enriched early language input, that is, simultaneous bilinguals and second language learners

HMG20B stabilizes association of LSD1 with GFI1 on chromatin to confer transcription repression and leukemia cell differentiation block

Pharmacologic inhibition of LSD1 induces molecular and morphologic differentiation of blast cells in acute myeloid leukemia (AML) patients harboring MLL gene translocations. In addition to its demethylase activity, LSD1 has a critical scaffolding function at genomic sites occupied by the SNAG domain transcription repressor GFI1. Importantly, inhibitors block both enzymatic and scaffolding activities, in the latter case by disrupting the protein:protein interaction of GFI1 with LSD1. To explore the wider consequences of LSD1 inhibition on the LSD1 protein complex we applied mass spectrometry technologies. We discovered that the interaction of the HMG-box protein HMG20B with LSD1 was also disrupted by LSD1 inhibition. Downstream investigations revealed that HMG20B is co-located on chromatin with GFI1 and LSD1 genome-wide; the strongest HMG20B binding co-locates with the strongest GFI1 and LSD1 binding. Functional assays demonstrated that HMG20B depletion induces leukemia cell differentiation and further revealed that HMG20B is required for the transcription repressor activity of GFI1 through stabilizing LSD1 on chromatin at GFI1 binding sites. Interaction of HMG20B with LSD1 is through its coiled-coil domain. Thus, HMG20B is a critical component of the GFI1:LSD1 transcription repressor complex which contributes to leukemia cell differentiation block

Tensile Fracture of Welded Polymer Interfaces: Miscibility, Entanglements and Crazing

Large-scale molecular simulations are performed to investigate tensile failure of polymer interfaces as a function of welding time $t$. Changes in the tensile stress, mode of failure and interfacial fracture energy $G_I$ are correlated to changes in the interfacial entanglements as determined from Primitive Path Analysis. Bulk polymers fail through craze formation, followed by craze breakdown through chain scission. At small $t$ welded interfaces are not strong enough to support craze formation and fail at small strains through chain pullout at the interface. Once chains have formed an average of about one entanglement across the interface, a stable craze is formed throughout the sample. The failure stress of the craze rises with welding time and the mode of craze breakdown changes from chain pullout to chain scission as the interface approaches bulk strength. The interfacial fracture energy $G_I$ is calculated by coupling the simulation results to a continuum fracture mechanics model. As in experiment, $G_I$ increases as $t^{1/2}$ before saturating at the average bulk fracture energy $G_b$. As in previous simulations of shear strength, saturation coincides with the recovery of the bulk entanglement density. Before saturation, $G_I$ is proportional to the areal density of interfacial entanglements. Immiscibiltiy limits interdiffusion and thus suppresses entanglements at the interface. Even small degrees of immisciblity reduce interfacial entanglements enough that failure occurs by chain pullout and $G_I \ll G_b$