Bipartite Interactions Research Articles

Small-Molecule Inhibitors Disrupt let-7 Oligouridylation and Release the Selective Blockade of let-7 Processing by LIN28

SUMMARYLIN28 is an RNA-binding protein that regulates the maturation of the let-7 family of microRNAs by bipartite interactions with let-7 precursors through its two distinct cold shock and zinc-knuckle domains. Through inhibition of let-7 biogenesis, LIN28 functions as a pluripotency factor, as well as a driver of tumorigenesis. Here, we report a fluorescence polarization assay to identify small-molecule inhibitors for both domains of LIN28 involved in let-7 interactions. Of 101,017 compounds screened, six inhibit LIN28:let-7 binding and impair LIN28-mediated let-7 oligouridylation. Upon further characterization, we demonstrate that the LIN28 inhibitor TPEN destabilizes the zinc-knuckle domain of LIN28, while LI71 binds the cold shock domain to suppress LIN28’s activity against let-7 in leukemia cells and embryonic stem cells. Our results demonstrate selective pharmacologic inhibition of individual domains of LIN28 and provide a foundation for therapeutic inhibition of the let-7 biogenesis pathway in LIN28-driven diseases.

Can niche plasticity promote biodiversity-productivity relationships through increased complementarity?

Most experimental biodiversity-ecosystem functioning research to date has addressed herbaceous plant communities. Comparably little is known about how forest communities will respond to species losses, despite their importance for global biogeochemical cycling. We studied tree species interactions in experimental subtropical tree communities with 33 distinct tree species mixtures and one, two, or four species. Plots were either exposed to natural light levels or shaded. Trees grew rapidly and were intensely competing above ground after 1.5 growing seasons when plots were thinned and the vertical distribution of leaves and wood determined by separating the biomass of harvested trees into 50cm height increments. Our aim was to analyze effects of species richness in relation to the vertical allocation of leaf biomass and wood, with an emphasis on bipartite competitive interactions among species. Aboveground productivity increased with species richness. The community-level vertical leaf and wood distribution depended on the species composition of communities. Mean height and breadth of species-level vertical leaf and wood distributions did not change with species richness. However, the extra biomass produced by mixtures compared to monocultures of the component species increased when vertical leaf distributions of monocultures were more different. Decomposition of biodiversity effects with the additive partitioning scheme indicated positive complementarity effects that were higher in light than in shade. Selection effects did not deviate from zero, irrespective of light levels. Vertical leaf distributions shifted apart in mixed stands as consequence of competition-driven phenotypic plasticity, promoting realized complementarity. Structural equation models showed that this effect was larger for species that differed more in growth strategies that were characterized by functional traits. In 13 of the 18 investigated two-species mixtures, both species benefitted relative to intraspecific competition in monoculture. In the remaining five pairwise mixtures, the relative yield gain of one species exceeded the relative yield loss of the other species, resulting in a relative yield total (RYT) exceeding 1. Overall, our analysis indicates that richness-productivity relationships are promoted by interspecific niche complementarity at early stages of stand development, and that this effect is enhanced by architectural plasticity.

Relative impacts of environmental variation and evolutionary history on the nestedness and modularity of tree-herbivore networks.

Nestedness and modularity are measures of ecological networks whose causative effects are little understood. We analyzed antagonistic plant–herbivore bipartite networks using common gardens in two contrasting environments comprised of aspen trees with differing evolutionary histories of defence against herbivores. These networks were tightly connected owing to a high level of specialization of arthropod herbivores that spend a large proportion of the life cycle on aspen. The gardens were separated by ten degrees of latitude with resultant differences in abiotic conditions. We evaluated network metrics and reported similar connectance between gardens but greater numbers of links per species in the northern common garden. Interaction matrices revealed clear nestedness, indicating subsetting of the bipartite interactions into specialist divisions, in both the environmental and evolutionary aspen groups, although nestedness values were only significant in the northern garden. Variation in plant vulnerability, measured as the frequency of herbivore specialization in the aspen population, was significantly partitioned by environment (common garden) but not by evolutionary origin of the aspens. Significant values of modularity were observed in all network matrices. Trait-matching indicated that growth traits, leaf morphology, and phenolic metabolites affected modular structure in both the garden and evolutionary groups, whereas extra-floral nectaries had little influence. Further examination of module configuration revealed that plant vulnerability explained considerable variance in web structure. The contrasting conditions between the two gardens resulted in bottom-up effects of the environment, which most strongly influenced the overall network architecture, however, the aspen groups with dissimilar evolutionary history also showed contrasting degrees of nestedness and modularity. Our research therefore shows that, while evolution does affect the structure of aspen–herbivore bipartite networks, the role of environmental variations is a dominant constraint.

Discrete restricted Boltzmann machines

We describe discrete restricted Boltzmann machines: probabilistic graphical models with bipartite interactions between visible and hidden discrete variables. Examples are binary restricted Boltzman...

Subanesthetic Ketamine Treatment Promotes Abnormal Interactions between Neural Subsystems and Alters the Properties of Functional Brain Networks

Acute treatment with subanesthetic ketamine, a non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist, is widely utilized as a translational model for schizophrenia. However, how acute NMDA receptor blockade impacts on brain functioning at a systems level, to elicit translationally relevant symptomatology and behavioral deficits, has not yet been determined. Here, for the first time, we apply established and recently validated topological measures from network science to brain imaging data gained from ketamine-treated mice to elucidate how acute NMDA receptor blockade impacts on the properties of functional brain networks. We show that the effects of acute ketamine treatment on the global properties of these networks are divergent from those widely reported in schizophrenia. Where acute NMDA receptor blockade promotes hyperconnectivity in functional brain networks, pronounced dysconnectivity is found in schizophrenia. We also show that acute ketamine treatment increases the connectivity and importance of prefrontal and thalamic brain regions in brain networks, a finding also divergent to alterations seen in schizophrenia. In addition, we characterize how ketamine impacts on bipartite functional interactions between neural subsystems. A key feature includes the enhancement of prefrontal cortex (PFC)-neuromodulatory subsystem connectivity in ketamine-treated animals, a finding consistent with the known effects of ketamine on PFC neurotransmitter levels. Overall, our data suggest that, at a systems level, acute ketamine-induced alterations in brain network connectivity do not parallel those seen in chronic schizophrenia. Hence, the mechanisms through which acute ketamine treatment induces translationally relevant symptomatology may differ from those in chronic schizophrenia. Future effort should therefore be dedicated to resolve the conflicting observations between this putative translational model and schizophrenia.

Molecular Bacteria-Fungi Interactions: Effects on Environment, Food, and Medicine

This review focuses on bacteria-fungi interactions mediated by secondary metabolites that occur in the environment and have implications for medicine and biotechnology. Bipartite interactions that affect agriculture as well as relationships involving additional partners (plants and animals) are discussed. The advantages of microbial interplay for food production and the risks regarding food safety are presented. Furthermore, recent developments in decoding the impact of bacteria-fungi interactions on infection processes and their implications for human health are highlighted. In addition, this reviews aims to demonstrate how the understanding of complex microbial interactions found in nature can be exploited for the discovery of new therapeutics.

Information sharing and sorting in a community

We present the results of a detailed numerical study of a model for the sharing and sorting of information in a community consisting of a large number of agents. The information gathering takes place in a sequence of mutual bipartite interactions where randomly selected pairs of agents communicate with each other to enhance their knowledge and sort out the common information. Although our model is less restricted compared to the well-established naming game, the numerical results strongly indicate that the whole set of exponents characterizing this model are different from those of the naming game and they assume nontrivial values. Finally, it appears that in analogy to the emergence of clusters in the phenomenon of percolation, one can define clusters of agents here having the same information. We have studied in detail the growth of the largest cluster in this article and performed its finite-size scaling analysis.

Sequential quantum cloning under real-life conditions

We consider a sequential implementation of the optimal quantum cloning machine of Gisin and Massar and propose optimization protocols for experimental realization of such a quantum cloner subject to the real-life restrictions. We demonstrate how exploiting the matrix-product state (MPS) formalism and the ensuing variational optimization techniques reveals the intriguing algebraic structure of the Gisin-Massar output of the cloning procedure and brings about significant improvements to the optimality of the sequential cloning prescription of Delgado et al [Phys. Rev. Lett. 98, 150502 (2007)]. Our numerical results show that the orthodox paradigm of optimal quantum cloning can in practice be realized in a much more economical manner by utilizing a considerably lesser amount of informational and numerical resources than hitherto estimated. Instead of the previously predicted linear scaling of the required ancilla dimension D with the number of qubits n, our recipe allows a realization of such a sequential cloning setup with an experimentally manageable ancilla of dimension at most D=3 up to n=15 qubits. We also address satisfactorily the possibility of providing an optimal range of sequential ancilla-qubit interactions for optimal cloning of arbitrary states under realistic experimental circumstances when only a restricted class of such bipartite interactions can be engineered in practice.

Bipartite syntaxin 1A interactions mediate Ca V2.2 calcium channel regulation

Functional interactions between syntaxin 1A and Ca V2 calcium channels are critical for fast neurotransmitter release in the mammalian brain, and coexpression of syntaxin 1A with these channels not only regulates channel availability, but also promotes G-protein inhibition. Both the syntaxin 1A C-terminal H3 domain, and N-terminal Ha domain have been shown to interact with the Ca V2.2 channel synprint region, suggesting a bipartite model of functional interaction, however the molecular determinants of this interaction have not been closely investigated. We used in vitro binding assays to assess interactions of syntaxin 1A truncation mutants with Ca V2.2 synprint and Ca V2.3 II–III linker regions. We identified two distinct interactions between the Ca V2.2 synprint region and syntaxin 1A: the first between C-terminal H3c domain of syntaxin 1A and residues 822–872 of Ca V2.2; and the second between the N-terminal 10 residues of the syntaxin 1A Ha region and residues 718–771 of Ca V2.2. The N-terminal syntaxin 1A fragment also interacted with the Ca V2.3 II–III linker. We then performed whole cell patch clamp recordings to test the effects of a putative interacting syntaxin 1A N-terminus peptide with Ca V2.2 and Ca V2.3 channels in a recombinant expression system. A YFP-tagged peptide corresponding to the N-terminal 10 residues of the syntaxin 1A Ha domain was sufficient to allosterically inhibit both Ca V2.2 and Ca V2.3 channel function but had no effect on G-protein mediated inhibition. Our results support a model of bipartite functional interactions between syntaxin 1A and Ca V2.2 channels and add accuracy to the two putative interacting domains, consistent with previous studies. Furthermore, we highlight the syntaxin 1A N-terminus as the minimal determinant for functional regulation of Ca V2.2 and Ca V2.3 channels.

Interacting non-Abelian anyons as Majorana fermions in the honeycomb lattice model

We study the collective states of interacting non-Abelian anyons that emerge in Kitaev's honeycomb lattice model. Vortex–vortex interactions are shown to lead to the lifting of topological degeneracy and the energy is found to exhibit oscillations that are consistent with Majorana fermions being localized at vortex cores. We show how to construct states corresponding to the fusion channel degrees of freedom and obtain the energy gaps characterizing the stability of the topological low-energy spectrum. To study the collective behavior of many vortices, we introduce an effective lattice model of Majorana fermions. We find the necessary conditions for the model to approximate the spectrum of the honeycomb lattice model, and show that bi-partite interactions are responsible for the lifting of degeneracy also in many-vortex systems.

Humans Differ from Other Hominids in Lacking an Activating NK Cell Receptor That Recognizes the C1 Epitope of MHC Class I

Modulation of human NK cell function by killer cell Ig-like receptors (KIR) and MHC class I is dominated by the bipartite interactions of inhibitory lineage III KIR with the C1 and C2 epitopes of HLA-C. In comparison, the ligand specificities and functional contributions of the activating lineage III KIR remain poorly understood. Using a robust, sensitive assay of KIR binding and a representative panel of 95 HLA class I targets, we show that KIR2DS1 binds C2 with ~50% the avidity of KIR2DL1, whereas KIR2DS2, KIR2DS3, and KIR2DS5 have no detectable avidity for C1, C2, or any other HLA class I epitope. In contrast, the chimpanzee has activating C1- and C2-specific lineage III KIR with strong avidity, comparable to those of their paired inhibitory receptors. One variant of chimpanzee Pt-KIR3DS2, the activating C2-specific receptor, has the same avidity for C2 as does inhibitory Pt-KIR3DL4, and a second variant has ~73% the avidity. Chimpanzee Pt-KIR3DS6, the activating C1-specific receptor, has avidity for C1 that is ~70% that of inhibitory Pt-KIR2DL6. In both humans and chimpanzees we observe an evolutionary trend toward reducing the avidity of the activating C1- and C2-specific receptors through selective acquisition of attenuating substitutions. However, the extent of attenuation has been extreme in humans, as exemplified by KIR2DS2, an activating C1-specific receptor that has lost all detectable avidity for HLA class I. Supporting such elimination of activating C1-specific receptors as a uniquely human phenomenon is the presence of a high-avidity activating C1-specific receptor (Gg-KIR2DSa) in gorilla.

Optimal purification of thermal graph states

In this paper, a purification protocol is presented and its performance is proven to be optimal when applied to a particular subset of graph states that are subject to local Z-noise. Such mixed states can be produced by bringing a system into thermal equilibrium, when it is described by a Hamiltonian which has a particular graph state as its unique ground state. From this protocol, we derive the exact value of the critical temperature Tcrit above which purification is impossible, as well as the related optimal purification rates. A possible simulation of graph Hamiltonians is proposed, which requires only bipartite interactions and local magnetic fields, enabling the tuning of the system temperature.

Role of the membrane fusion protein in the assembly of resistance-nodulation-cell division multidrug efflux pump in Pseudomonas aeruginosa

The tripartite xenobiotic–antibiotic transporter of Pseudomonas aeruginosa consists of the inner membrane transporter (e.g., MexB, MexY), the periplasmic membrane-fusion-protein (e.g., MexA, MexX), and the outer membrane channel protein (e.g., OprM). These subunits were assumed to assemble into a transporter unit during export of the substrates. However, subunit interaction and their specificity in native form remained to be elucidated. To address these important questions, we analyzed the role of the individual subunits for the assembly of MexAB–OprM by pull-down assay tagging only one of the subunits. We found stable MexA–MexB–OprM complex without chemical cross-linking that withstand all purification procedures. Results of bi-partite interactions analysis showed tight association between MexA and OprM in the absence of MexB, whereas the expression systems lacking MexA failed to co-purify MexB or OprM. None of the heterologous subunit combinations such as MexA+MexYhis+OprM and MexX+MexBhis+OprM showed interaction. These results implied that the membrane fusion protein is central to the tripartite xenobiotic transporter assembly.

AcrA, AcrB, and TolC of Escherichia coli Form a Stable Intermembrane Multidrug Efflux Complex

Many transporters of Gram-negative bacteria involved in the extracellular secretion of proteins and the efflux of toxic molecules operate by forming intermembrane complexes. These complexes are proposed to span both inner and outer membranes and create a bridge across the periplasm. In this study, we analyzed interactions between the inner and outer membrane components of the tri-partite multidrug efflux pump AcrAB-TolC from Escherichia coli. We found that, once assembled, the intermembrane AcrAB-TolC complex is stable during the separation of the inner and outer membranes and subsequent purification. All three components of the complex co-purify when the affinity tag is attached to either of the proteins suggesting bi-partite interactions between AcrA, AcrB, and TolC. We show that antibiotics, the substrates of AcrAB-TolC, stabilize interactions within the complex. However, the formation of the AcrAB-TolC complex does not require an input of energy.