TY - JOUR AB - The differentiation of cells depends on a precise control of their internal organization, which is the result of a complex dynamic interplay between the cytoskeleton, molecular motors, signaling molecules, and membranes. For example, in the developing neuron, the protein ADAP1 (ADP-ribosylation factor GTPase-activating protein [ArfGAP] with dual pleckstrin homology [PH] domains 1) has been suggested to control dendrite branching by regulating the small GTPase ARF6. Together with the motor protein KIF13B, ADAP1 is also thought to mediate delivery of the second messenger phosphatidylinositol (3,4,5)-trisphosphate (PIP3) to the axon tip, thus contributing to PIP3 polarity. However, what defines the function of ADAP1 and how its different roles are coordinated are still not clear. Here, we studied ADAP1’s functions using in vitro reconstitutions. We found that KIF13B transports ADAP1 along microtubules, but that PIP3 as well as PI(3,4)P2 act as stop signals for this transport instead of being transported. We also demonstrate that these phosphoinositides activate ADAP1’s enzymatic activity to catalyze GTP hydrolysis by ARF6. Together, our results support a model for the cellular function of ADAP1, where KIF13B transports ADAP1 until it encounters high PIP3/PI(3,4)P2 concentrations in the plasma membrane. Here, ADAP1 disassociates from the motor to inactivate ARF6, promoting dendrite branching. AU - Düllberg, Christian F AU - Auer, Albert AU - Canigova, Nikola AU - Loibl, Katrin AU - Loose, Martin ID - 8988 IS - 1 JF - PNAS SN - 00278424 TI - In vitro reconstitution reveals phosphoinositides as cargo-release factors and activators of the ARF6 GAP ADAP1 VL - 118 ER - TY - JOUR AB - N-1-naphthylphthalamic acid (NPA) is a key inhibitor of directional (polar) transport of the hormone auxin in plants. For decades, it has been a pivotal tool in elucidating the unique polar auxin transport-based processes underlying plant growth and development. Its exact mode of action has long been sought after and is still being debated, with prevailing mechanistic schemes describing only indirect connections between NPA and the main transporters responsible for directional transport, namely PIN auxin exporters. Here we present data supporting a model in which NPA associates with PINs in a more direct manner than hitherto postulated. We show that NPA inhibits PIN activity in a heterologous oocyte system and that expression of NPA-sensitive PINs in plant, yeast, and oocyte membranes leads to specific saturable NPA binding. We thus propose that PINs are a bona fide NPA target. This offers a straightforward molecular basis for NPA inhibition of PIN-dependent auxin transport and a logical parsimonious explanation for the known physiological effects of NPA on plant growth, as well as an alternative hypothesis to interpret past and future results. We also introduce PIN dimerization and describe an effect of NPA on this, suggesting that NPA binding could be exploited to gain insights into structural aspects of PINs related to their transport mechanism. AU - Abas, Lindy AU - Kolb, Martina AU - Stadlmann, Johannes AU - Janacek, Dorina P. AU - Lukic, Kristina AU - Schwechheimer, Claus AU - Sazanov, Leonid A AU - Mach, Lukas AU - Friml, Jiří AU - Hammes, Ulrich Z. ID - 8993 IS - 1 JF - PNAS SN - 00278424 TI - Naphthylphthalamic acid associates with and inhibits PIN auxin transporters VL - 118 ER - TY - JOUR AB - The brain represents and reasons probabilistically about complex stimuli and motor actions using a noisy, spike-based neural code. A key building block for such neural computations, as well as the basis for supervised and unsupervised learning, is the ability to estimate the surprise or likelihood of incoming high-dimensional neural activity patterns. Despite progress in statistical modeling of neural responses and deep learning, current approaches either do not scale to large neural populations or cannot be implemented using biologically realistic mechanisms. Inspired by the sparse and random connectivity of real neuronal circuits, we present a model for neural codes that accurately estimates the likelihood of individual spiking patterns and has a straightforward, scalable, efficient, learnable, and realistic neural implementation. This model’s performance on simultaneously recorded spiking activity of >100 neurons in the monkey visual and prefrontal cortices is comparable with or better than that of state-of-the-art models. Importantly, the model can be learned using a small number of samples and using a local learning rule that utilizes noise intrinsic to neural circuits. Slower, structural changes in random connectivity, consistent with rewiring and pruning processes, further improve the efficiency and sparseness of the resulting neural representations. Our results merge insights from neuroanatomy, machine learning, and theoretical neuroscience to suggest random sparse connectivity as a key design principle for neuronal computation. AU - Maoz, Ori AU - Tkačik, Gašper AU - Esteki, Mohamad Saleh AU - Kiani, Roozbeh AU - Schneidman, Elad ID - 8698 IS - 40 JF - Proceedings of the National Academy of Sciences of the United States of America SN - 00278424 TI - Learning probabilistic neural representations with randomly connected circuits VL - 117 ER - TY - JOUR AB - In the high spin–orbit-coupled Sr2IrO4, the high sensitivity of the ground state to the details of the local lattice structure shows a large potential for the manipulation of the functional properties by inducing local lattice distortions. We use epitaxial strain to modify the Ir–O bond geometry in Sr2IrO4 and perform momentum-dependent resonant inelastic X-ray scattering (RIXS) at the metal and at the ligand sites to unveil the response of the low-energy elementary excitations. We observe that the pseudospin-wave dispersion for tensile-strained Sr2IrO4 films displays large softening along the [h,0] direction, while along the [h,h] direction it shows hardening. This evolution reveals a renormalization of the magnetic interactions caused by a strain-driven cross-over from anisotropic to isotropic interactions between the magnetic moments. Moreover, we detect dispersive electron–hole pair excitations which shift to lower (higher) energies upon compressive (tensile) strain, manifesting a reduction (increase) in the size of the charge gap. This behavior shows an intimate coupling between charge excitations and lattice distortions in Sr2IrO4, originating from the modified hopping elements between the t2g orbitals. Our work highlights the central role played by the lattice degrees of freedom in determining both the pseudospin and charge excitations of Sr2IrO4 and provides valuable information toward the control of the ground state of complex oxides in the presence of high spin–orbit coupling. AU - Paris, Eugenio AU - Tseng, Yi AU - Paerschke, Ekaterina AU - Zhang, Wenliang AU - Upton, Mary H AU - Efimenko, Anna AU - Rolfs, Katharina AU - McNally, Daniel E AU - Maurel, Laura AU - Naamneh, Muntaser AU - Caputo, Marco AU - Strocov, Vladimir N AU - Wang, Zhiming AU - Casa, Diego AU - Schneider, Christof W AU - Pomjakushina, Ekaterina AU - Wohlfeld, Krzysztof AU - Radovic, Milan AU - Schmitt, Thorsten ID - 8699 IS - 40 JF - Proceedings of the National Academy of Sciences of the United States of America SN - 00278424 TI - Strain engineering of the charge and spin-orbital interactions in Sr2IrO4 VL - 117 ER - TY - JOUR AB - In prokaryotes, thermodynamic models of gene regulation provide a highly quantitative mapping from promoter sequences to gene-expression levels that is compatible with in vivo and in vitro biophysical measurements. Such concordance has not been achieved for models of enhancer function in eukaryotes. In equilibrium models, it is difficult to reconcile the reported short transcription factor (TF) residence times on the DNA with the high specificity of regulation. In nonequilibrium models, progress is difficult due to an explosion in the number of parameters. Here, we navigate this complexity by looking for minimal nonequilibrium enhancer models that yield desired regulatory phenotypes: low TF residence time, high specificity, and tunable cooperativity. We find that a single extra parameter, interpretable as the “linking rate,” by which bound TFs interact with Mediator components, enables our models to escape equilibrium bounds and access optimal regulatory phenotypes, while remaining consistent with the reported phenomenology and simple enough to be inferred from upcoming experiments. We further find that high specificity in nonequilibrium models is in a trade-off with gene-expression noise, predicting bursty dynamics—an experimentally observed hallmark of eukaryotic transcription. By drastically reducing the vast parameter space of nonequilibrium enhancer models to a much smaller subspace that optimally realizes biological function, we deliver a rich class of models that could be tractably inferred from data in the near future. AU - Grah, Rok AU - Zoller, Benjamin AU - Tkačik, Gašper ID - 9000 IS - 50 JF - PNAS SN - 00278424 TI - Nonequilibrium models of optimal enhancer function VL - 117 ER -