by Ayal Lavi, Omri Perez, Uri Ashery

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.

by Hannah Edwards, Charlotte M. Deane

Several protein structure classification schemes exist that partition the protein universe into structural units called folds. Yet these schemes do not discuss how these units sit relative to each other in a global structure space. In this paper we construct networks that describe such global relationships between folds in the form of structural bridges. We generate these networks using four different structural alignment methods across multiple score thresholds. The networks constructed using the different methods remain a similar distance apart regardless of the probability threshold defining a structural bridge. This suggests that at least some structural bridges are method specific and that any attempt to build a picture of structural space should not be reliant on a single structural superposition method. Despite these differences all representations agree on an organisation of fold space into five principal community structures: all-α, all-β sandwiches, all-β barrels, α/β and α + β. We project estimated fold ages onto the networks and find that not only are the pairings of unconnected folds associated with higher age differences than bridged folds, but this difference increases with the number of networks displaying an edge. We also examine different centrality measures for folds within the networks and how these relate to fold age. While these measures interpret the central core of fold space in varied ways they all identify the disposition of ancestral folds to fall within this core and that of the more recently evolved structures to provide the peripheral landscape. These findings suggest that evolutionary information is encoded along these structural bridges. Finally, we identify four highly central pivotal folds representing dominant topological features which act as key attractors within our landscapes.

Abstract

Acetylation of surface lysine residues of proteins has been observed in Escherichia coli (E. coli), an organism that has been extensively utilized for recombinant protein expression. This post-translational modification is shown to be important in various processes such as metabolism, stress-response, transcription, and translation. As such, utilization of E. coli expression systems for protein production may yield non-native acetylation events of surface lysine residues. Here we present the crystal structures of wild-type and a variant of human carbonic anhydrase II (hCA II) that have been expressed in E. coli and exhibit surface lysine acetylation and we speculate on the effect this has on the conformational stability of each enzyme. Both structures were determined to 1.6 Å resolution and show clear electron density for lysine acetylation. The lysine acetylation does not distort the structure and the surface lysine acetylation events most likely do not interfere with the biological interpretation. However, there is a reduction in conformational stability in the hCA II variant compared to wild type (∼4°C decrease). This may be due to other lysine acetylation events that have occurred but are not visible in the crystal structure due to intrinsic disorder. Therefore, surface lysine acetylation events may affect overall protein stability and crystallization, and should be considered when using E. coli expression systems.

by Stephan Köhler, Friederike Schmid, Giovanni Settanni

Fibrinogen is a serum multi-chain protein which, when activated, aggregates to form fibrin, one of the main components of a blood clot. Fibrinolysis controls blood clot dissolution through the action of the enzyme plasmin, which cleaves fibrin at specific locations. Although the main biochemical factors involved in fibrin formation and lysis have been identified, a clear mechanistic picture of how these processes take place is not available yet. This picture would be instrumental, for example, for the design of improved thrombolytic or anti-haemorrhagic strategies, as well as, materials with improved biocompatibility. Here, we present extensive molecular dynamics simulations of fibrinogen which reveal large bending motions centered at a hinge point in the coiled-coil regions of the molecule. This feature, likely conserved across vertebrates according to our analysis, suggests an explanation for the mechanism of exposure to lysis of the plasmin cleavage sites on fibrinogen coiled-coil region. It also explains the conformational variability of fibrinogen observed during its adsorption on inorganic surfaces and it is supposed to play a major role in the determination of the hydrodynamic properties of fibrinogen. In addition the simulations suggest how the dynamics of the D region of fibrinogen may contribute to the allosteric regulation of the blood coagulation cascade through a dynamic coupling between the a- and b-holes, important for fibrin polymerization, and the integrin binding site P1.

by Joseph Snider, Dongpyo Lee, Howard Poizner, Sergei Gepshtein

The future is uncertain because some forthcoming events are unpredictable and also because our ability to foresee the myriad consequences of our own actions is limited. Here we studied how humans select actions under such extrinsic and intrinsic uncertainty, in view of an exponentially expanding number of prospects on a branching multivalued visual stimulus. A triangular grid of disks of different sizes scrolled down a touchscreen at a variable speed. The larger disks represented larger rewards. The task was to maximize the cumulative reward by touching one disk at a time in a rapid sequence, forming an upward path across the grid, while every step along the path constrained the part of the grid accessible in the future. This task captured some of the complexity of natural behavior in the risky and dynamic world, where ongoing decisions alter the landscape of future rewards. By comparing human behavior with behavior of ideal actors, we identified the strategies used by humans in terms of how far into the future they looked (their “depth of computation”) and how often they attempted to incorporate new information about the future rewards (their “recalculation period”). We found that, for a given task difficulty, humans traded off their depth of computation for the recalculation period. The form of this tradeoff was consistent with a complete, brute-force exploration of all possible paths up to a resource-limited finite depth. A step-by-step analysis of the human behavior revealed that participants took into account very fine distinctions between the future rewards and that they abstained from some simple heuristics in assessment of the alternative paths, such as seeking only the largest disks or avoiding the smaller disks. The participants preferred to reduce their depth of computation or increase the recalculation period rather than sacrifice the precision of computation.

by Alexander Ullrich, Mathias A. Böhme, Johannes Schöneberg, Harald Depner, Stephan J. Sigrist, Frank Noé

Synaptic vesicle fusion is mediated by SNARE proteins forming in between synaptic vesicle (v-SNARE) and plasma membrane (t-SNARE), one of which is Syntaxin-1A. Although exocytosis mainly occurs at active zones, Syntaxin-1A appears to cover the entire neuronal membrane. By using STED super-resolution light microscopy and image analysis of Drosophila neuro-muscular junctions, we show that Syntaxin-1A clusters are more abundant and have an increased size at active zones. A computational particle-based model of syntaxin cluster formation and dynamics is developed. The model is parametrized to reproduce Syntaxin cluster-size distributions found by STED analysis, and successfully reproduces existing FRAP results. The model shows that the neuronal membrane is adjusted in a way to strike a balance between having most syntaxins stored in large clusters, while still keeping a mobile fraction of syntaxins free or in small clusters that can efficiently search the membrane or be traded between clusters. This balance is subtle and can be shifted toward almost no clustering and almost complete clustering by modifying the syntaxin interaction energy on the order of only 1 kBT. This capability appears to be exploited at active zones. The larger active-zone syntaxin clusters are more stable and provide regions of high docking and fusion capability, whereas the smaller clusters outside may serve as flexible reserve pool or sites of spontaneous ectopic release.

by Sergei Maslov, Kim Sneppen

Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe reduction in size of the population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is characterized by cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances have bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b08186

ABSTRACT

For the template-based modeling (TBM) of CASP11 targets, we have developed three new protein modeling protocols (nns for server prediction and LEE and LEER for human prediction) by improving upon our previous CASP protocols (CASP7 through CASP10). We applied the powerful global optimization method of conformational space annealing to three stages of optimization, including multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain remodeling. For more successful fold recognition, a new alignment method called CRFalign was developed. It can incorporate sensitive positional and environmental dependence in alignment scores as well as strong nonlinear correlations among various features. Modifications and adjustments were made to the form of the energy function and weight parameters pertaining to the chain building procedure. For the side-chain remodeling step, residue-type dependence was introduced to the cutoff value that determines the entry of a rotamer to the side-chain modeling library. The improved performance of the nns server method is attributed to successful fold recognition achieved by combining several methods including CRFalign and to the current modeling formulation that can incorporate native-like structural aspects present in multiple templates. The LEE protocol is identical to the nns one except that CASP11-released server models are used as templates. The success of LEE in utilizing CASP11 server models indicates that proper template screening and template clustering assisted by appropriate cluster ranking promises a new direction to enhance protein 3D modeling. Proteins 2015. © 2015 Wiley Periodicals, Inc.

Nature Methods 12, 1039 (2015). doi:10.1038/nmeth.3581

Authors: Owen Randlett, Caroline L Wee, Eva A Naumann, Onyeka Nnaemeka, David Schoppik, James E Fitzgerald, Ruben Portugues, Alix M B Lacoste, Clemens Riegler, Florian Engert & Alexander F Schier

Nature Methods 12, 1061 (2015). doi:10.1038/nmeth.3582

Authors: Bryce van de Geijn, Graham McVicker, Yoav Gilad & Jonathan K Pritchard

Allele-specific sequencing reads provide a powerful signal for identifying molecular quantitative trait loci (QTLs), but they are challenging to analyze and are prone to technical artifacts. Here we describe WASP, a suite of tools for unbiased allele-specific read mapping and discovery of molecular QTLs. Using simulated reads, RNA-seq reads and chromatin immunoprecipitation sequencing (ChIP-seq) reads, we demonstrate that WASP has a low error rate and is far more powerful than existing QTL-mapping approaches.

Nature Methods 12, 1091 (2015). doi:10.1038/nmeth.3584

Authors: Hannes Link, Tobias Fuhrer, Luca Gerosa, Nicola Zamboni & Uwe Sauer

Lithospheric controls on magma composition along Earth’s longest continental hotspot track

Nature 525, 7570 (2015). doi:10.1038/nature14903

Authors: D. R. Davies, N. Rawlinson, G. Iaffaldano & I. H. Campbell

Hotspots are anomalous regions of volcanism at Earth’s surface that show no obvious association with tectonic plate boundaries. Classic examples include the Hawaiian–Emperor chain and the Yellowstone–Snake River Plain province. The majority are believed to form as Earth’s tectonic plates move over long-lived mantle plumes: buoyant upwellings that bring hot material from Earth’s deep mantle to its surface. It has long been recognized that lithospheric thickness limits the rise height of plumes and, thereby, their minimum melting pressure. It should, therefore, have a controlling influence on the geochemistry of plume-related magmas, although unambiguous evidence of this has, so far, been lacking. Here we integrate observational constraints from surface geology, geochronology, plate-motion reconstructions, geochemistry and seismology to ascertain plume melting depths beneath Earth’s longest continental hotspot track, a 2,000-kilometre-long track in eastern Australia that displays a record of volcanic activity between 33 and 9 million years ago, which we call the Cosgrove track. Our analyses highlight a strong correlation between lithospheric thickness and magma composition along this track, with: (1) standard basaltic compositions in regions where lithospheric thickness is less than 110 kilometres; (2) volcanic gaps in regions where lithospheric thickness exceeds 150 kilometres; and (3) low-volume, leucitite-bearing volcanism in regions of intermediate lithospheric thickness. Trace-element concentrations from samples along this track support the notion that these compositional variations result from different degrees of partial melting, which is controlled by the thickness of overlying lithosphere. Our results place the first observational constraints on the sub-continental melting depth of mantle plumes and provide direct evidence that lithospheric thickness has a dominant influence on the volume and chemical composition of plume-derived magmas.

BET inhibitor resistance emerges from leukaemia stem cells

Nature 525, 7570 (2015). doi:10.1038/nature14888

Authors: Chun Yew Fong, Omer Gilan, Enid Y. N. Lam, Alan F. Rubin, Sarah Ftouni, Dean Tyler, Kym Stanley, Devbarna Sinha, Paul Yeh, Jessica Morison, George Giotopoulos, Dave Lugo, Philip Jeffrey, Stanley Chun-Wei Lee, Christopher Carpenter, Richard Gregory, Robert G. Ramsay, Steven W. Lane, Omar Abdel-Wahab, Tony Kouzarides, Ricky W. Johnstone, Sarah-Jane Dawson, Brian J. P. Huntly, Rab K. Prinjha, Anthony T. Papenfuss & Mark A. Dawson

Bromodomain and extra terminal protein (BET) inhibitors are first-in-class targeted therapies that deliver a new therapeutic opportunity by directly targeting bromodomain proteins that bind acetylated chromatin marks. Early clinical trials have shown promise, especially in acute myeloid leukaemia, and therefore the evaluation of resistance mechanisms is crucial to optimize the clinical efficacy of these drugs. Here we use primary mouse haematopoietic stem and progenitor cells immortalized with the fusion protein MLL–AF9 to generate several single-cell clones that demonstrate resistance, in vitro and in vivo, to the prototypical BET inhibitor, I-BET. Resistance to I-BET confers cross-resistance to chemically distinct BET inhibitors such as JQ1, as well as resistance to genetic knockdown of BET proteins. Resistance is not mediated through increased drug efflux or metabolism, but is shown to emerge from leukaemia stem cells both ex vivo and in vivo. Chromatin-bound BRD4 is globally reduced in resistant cells, whereas the expression of key target genes such as Myc remains unaltered, highlighting the existence of alternative mechanisms to regulate transcription. We demonstrate that resistance to BET inhibitors, in human and mouse leukaemia cells, is in part a consequence of increased Wnt/β-catenin signalling, and negative regulation of this pathway results in restoration of sensitivity to I-BET in vitro and in vivo. Together, these findings provide new insights into the biology of acute myeloid leukaemia, highlight potential therapeutic limitations of BET inhibitors, and identify strategies that may enhance the clinical utility of these unique targeted therapies.

Transcriptional plasticity promotes primary and acquired resistance to BET inhibition

Nature 525, 7570 (2015). doi:10.1038/nature14898

Authors: Philipp Rathert, Mareike Roth, Tobias Neumann, Felix Muerdter, Jae-Seok Roe, Matthias Muhar, Sumit Deswal, Sabine Cerny-Reiterer, Barbara Peter, Julian Jude, Thomas Hoffmann, Łukasz M. Boryń, Elin Axelsson, Norbert Schweifer, Ulrike Tontsch-Grunt, Lukas E. Dow, Davide Gianni, Mark Pearson, Peter Valent, Alexander Stark, Norbert Kraut, Christopher R. Vakoc & Johannes Zuber

Following the discovery of BRD4 as a non-oncogene addiction target in acute myeloid leukaemia (AML), bromodomain and extra terminal protein (BET) inhibitors are being explored as a promising therapeutic avenue in numerous cancers. While clinical trials have reported single-agent activity in advanced haematological malignancies, mechanisms determining the response to BET inhibition remain poorly understood. To identify factors involved in primary and acquired BET resistance in leukaemia, here we perform a chromatin-focused RNAi screen in a sensitive MLL–AF9;NrasG12D-driven AML mouse model, and investigate dynamic transcriptional profiles in sensitive and resistant mouse and human leukaemias. Our screen shows that suppression of the PRC2 complex, contrary to effects in other contexts, promotes BET inhibitor resistance in AML. PRC2 suppression does not directly affect the regulation of Brd4-dependent transcripts, but facilitates the remodelling of regulatory pathways that restore the transcription of key targets such as Myc. Similarly, while BET inhibition triggers acute MYC repression in human leukaemias regardless of their sensitivity, resistant leukaemias are uniformly characterized by their ability to rapidly restore MYC transcription. This process involves the activation and recruitment of WNT signalling components, which compensate for the loss of BRD4 and drive resistance in various cancer models. Dynamic chromatin immunoprecipitation sequencing and self-transcribing active regulatory region sequencing of enhancer profiles reveal that BET-resistant states are characterized by remodelled regulatory landscapes, involving the activation of a focal MYC enhancer that recruits WNT machinery in response to BET inhibition. Together, our results identify and validate WNT signalling as a driver and candidate biomarker of primary and acquired BET resistance in leukaemia, and implicate the rewiring of transcriptional programs as an important mechanism promoting resistance to BET inhibitors and, potentially, other chromatin-targeted therapies.

by Daniel Nichol, Peter Jeavons, Alexander G. Fletcher, Robert A. Bonomo, Philip K. Maini, Jerome L. Paul, Robert A. Gatenby, Alexander R.A. Anderson, Jacob G. Scott

The increasing rate of antibiotic resistance and slowing discovery of novel antibiotic treatments presents a growing threat to public health. Here, we consider a simple model of evolution in asexually reproducing populations which considers adaptation as a biased random walk on a fitness landscape. This model associates the global properties of the fitness landscape with the algebraic properties of a Markov chain transition matrix and allows us to derive general results on the non-commutativity and irreversibility of natural selection as well as antibiotic cycling strategies. Using this formalism, we analyze 15 empirical fitness landscapes of E. coli under selection by different β-lactam antibiotics and demonstrate that the emergence of resistance to a given antibiotic can be either hindered or promoted by different sequences of drug application. Specifically, we demonstrate that the majority, approximately 70%, of sequential drug treatments with 2–4 drugs promote resistance to the final antibiotic. Further, we derive optimal drug application sequences with which we can probabilistically ‘steer’ the population through genotype space to avoid the emergence of resistance. This suggests a new strategy in the war against antibiotic–resistant organisms: drug sequencing to shepherd evolution through genotype space to states from which resistance cannot emerge and by which to maximize the chance of successful therapy.

by Elizabeth A. Hobson, Simon DeDeo

Dominance hierarchies are group-level properties that emerge from the aggression of individuals. Although individuals can gain critical benefits from their position in a hierarchy, we do not understand how real-world hierarchies form. Nor do we understand what signals and decision-rules individuals use to construct and maintain hierarchies in the absence of simple cues such as size or spatial location. A study of conflict in two groups of captive monk parakeets (Myiopsitta monachus) found that a transition to large-scale order in aggression occurred in newly-formed groups after one week, with individuals thereafter preferring to direct aggression more frequently against those nearby in rank. We consider two cognitive mechanisms underlying the emergence of this order: inference based on overall levels of aggression, or on subsets of the aggression network. Both mechanisms were predictive of individual decisions to aggress, but observed patterns were better explained by rank inference through subsets of the aggression network. Based on these results, we present a new theory, of a feedback loop between knowledge of rank and consequent behavior. This loop explains the transition to strategic aggression and the formation and persistence of dominance hierarchies in groups capable of both social memory and inference.

by Santiago Schnell

ABSTRACT

Escherichia coli ClpB is a heat shock protein that belongs to the AAA+ protein superfamily. Studies have shown that ClpB and its homologue in yeast, Hsp104, can disrupt protein aggregates in vivo. It is thought that ClpB requires binding of nucleoside triphosphate to assemble into hexameric rings with protein binding activity. In addition, it is widely assumed that ClpB is uniformly hexameric in the presence of nucleotides. Here we report, in the absence of nucleotide, that increasing ClpB concentration leads to ClpB hexamer formation, decreasing NaCl concentration stabilizes ClpB hexamers, and the ClpB assembly reaction is best described by a monomer, dimer, tetramer, hexamer equilibrium under the three salt concentrations examined. Further, we found that ClpB oligomers exhibit relatively fast dissociation on the time scale of sedimentation. We anticipate our studies on ClpB assembly to be a starting point to understand how ClpB assembly is linked to the binding and disaggregation of denatured proteins. Proteins 2015; 83:2008–2024. © 2015 Wiley Periodicals, Inc.

ABSTRACT

We examine the utility of informatic-based methods in computational protein biophysics. To do so, we use newly developed metric functions to define completely independent sequence and structure spaces for a large database of proteins. By investigating the relationship between these spaces, we demonstrate quantitatively the limits of knowledge-based correlation between the sequences and structures of proteins. It is shown that there are well-defined, nonlinear regions of protein space in which dissimilar structures map onto similar sequences (the conformational switch), and dissimilar sequences map onto similar structures (remote homology). These nonlinearities are shown to be quite common—almost half the proteins in our database fall into one or the other of these two regions. They are not anomalies, but rather intrinsic properties of structural encoding in amino acid sequences. It follows that extreme care must be exercised in using bioinformatic data as a basis for computational structure prediction. The implications of these results for protein evolution are examined. Proteins 2015; 83:1923–1928. © 2015 Wiley Periodicals, Inc.