ArfA rescues ribosomes stalled on truncated mRNAs by recruiting release factor RF2, which normally binds stop codons to catalyze peptide release. We report two 3.2-Å resolution cryo-EM structures - determined from a single sample - of the 70S ribosome with ArfA•RF2 in the A site. In both states, the ArfA C-terminus occupies the mRNA tunnel downstream of the A site. One state contains a compact inactive RF2 conformation. Ordering of the ArfA N-terminus in the second state rearranges RF2 into an extended conformation that docks the catalytic GGQ motif into the peptidyl-transferase center. Our work thus reveals the structural dynamics of ribosome rescue. The structures demonstrate how ArfA "senses" the vacant mRNA tunnel and activates RF2 to mediate peptide release without a stop codon, allowing stalled ribosomes to be recycled.

During active somatosensation, neural signals expected from movement of the sensors are suppressed in the cortex, whereas information related to touch is enhanced. This tactile suppression underlies low-noise encoding of relevant tactile features and the brain's ability to make fine tactile discriminations. Layer (L) 4 excitatory neurons in the barrel cortex, the major target of the somatosensory thalamus (VPM), respond to touch, but have low spike rates and low sensitivity to the movement of whiskers. Most neurons in VPM respond to touch and also show an increase in spike rate with whisker movement. Therefore, signals related to self-movement are suppressed in L4. Fast-spiking (FS) interneurons in L4 show similar dynamics to VPM neurons. Stimulation of halorhodopsin in FS interneurons causes a reduction in FS neuron activity and an increase in L4 excitatory neuron activity. This decrease of activity of L4 FS neurons contradicts the "paradoxical effect" predicted in networks stabilized by inhibition and in strongly-coupled networks. To explain these observations, we constructed a model of the L4 circuit, with connectivity constrained by in vitro measurements. The model explores the various synaptic conductance strengths for which L4 FS neurons actively suppress baseline and movement-related activity in layer 4 excitatory neurons. Feedforward inhibition, in concert with recurrent intracortical circuitry, produces tactile suppression. Synaptic delays in feedforward inhibition allow transmission of temporally brief volleys of activity associated with touch. Our model provides a mechanistic explanation of a behavior-related computation implemented by the thalamocortical circuit.

Discoveries spanning several decades have pointed to vital membrane lipid trafficking pathways involving both vesicular and non-vesicular carriers. But the relative contributions for distinct membrane delivery pathways in cell growth and organelle biogenesis continue to be a puzzle. This is because lipids flow from many sources and across many paths via transport vesicles, non-vesicular transfer proteins, and dynamic interactions between organelles at membrane contact sites. This forum presents our latest understanding, appreciation, and queries regarding the lipid transport mechanisms necessary to drive membrane expansion during organelle biogenesis and cell growth.

The dilemma that neurotheorists face is that (1) detailed biophysical models that can be constrained by direct measurements, while being of great importance, offer no immediate insights into cognitive processes in the brain, and (2) high-level abstract cognitive models, on the other hand, while relevant for understanding behavior, are largely detached from neuronal processes and typically have many free, experimentally unconstrained parameters that have to be tuned to a particular data set and, hence, cannot be readily generalized to other experimental paradigms. In this contribution, we propose a set of "first principles" for neurally inspired cognitive modeling of memory retrieval that has no biologically unconstrained parameters and can be analyzed mathematically both at neuronal and cognitive levels. We apply this framework to the classical cognitive paradigm of free recall. We show that the resulting model accounts well for puzzling behavioral data on human participants and makes predictions that could potentially be tested with neurophysiological recording techniques.

Seconds-scale network states, affecting many neurons within a network, modulate neural activity by complementing fast integration of neuron-specific inputs that arrive in the milliseconds before spiking. Non-rhythmic subthreshold dynamics at intermediate timescales, however, are less well-characterized. We found, using automated whole cell patch clamping in vivo, that spikes recorded in CA1 and barrel cortex in awake mice are often preceded not only by monotonic voltage rises lasting milliseconds, but also by more gradual (lasting 10s-100s of ms) depolarizations. The latter exert a gating function on spiking, in a fashion that depends on the gradual rise duration: the probability of spiking was higher for longer gradual rises, even controlling for the amplitude of the gradual rises. Barrel cortex double-autopatch recordings show that gradual rises are shared across some but not all neurons. The gradual rises may represent a new kind of state, intermediate both in timescale and in proportion of neurons participating, which gates a neuron's ability to respond to subsequent inputs.

Solving the atomic structure of metallic clusters is fundamental to understanding their optical, electronic, and chemical properties. We report the structure of Au146(p-MBA)57 at subatomic resolution (0.85 {\AA}) using electron diffraction (MicroED) and atomic resolution by X-ray diffraction. The 146 gold atoms may be decomposed into two constituent sets consisting of 119 core and 27 peripheral atoms. The core atoms are organized in a twinned FCC structure whereas the surface gold atoms follow a C2 rotational symmetry about an axis bisecting the twinning plane. The protective layer of 57 p-MBAs fully encloses the cluster and comprises bridging, monomeric, and dimeric staple motifs. Au146(p-MBA)57 is the largest cluster observed exhibiting a bulk-like FCC structure as well as the smallest gold particle exhibiting a stacking fault.

Theoretical calculations suggest that crystals exceeding 100 nm thickness are excluded by dynamical scattering from successful structure determination using microcrystal electron diffraction (MicroED). These calculations are at odds with experimental results where MicroED structures have been determined from significantly thicker crystals. Here we systematically evaluate the influence of thickness on the accuracy of MicroED intensities and the ability to determine structures from protein crystals one micrometer thick. To do so, we compare ab initio structures of a human prion protein segment determined from thin crystals to those determined from crystals up to one micrometer thick. We also compare molecular replacement solutions from crystals of varying thickness for a larger globular protein, proteinase K. Our results indicate that structures can be reliably determined from crystals at least an order of magnitude thicker than previously suggested by simulation, opening the possibility for an even broader range of MicroED experiments.

Population activity measurement by calcium imaging can be combined with cellular resolution optogenetic activity perturbations to enable the mapping of neural connectivity in vivo. This requires accurate inference of perturbed and unperturbed neural activity from calcium imaging measurements, which are noisy and indirect, and can also be contaminated by photostimulation artifacts. We have developed a new fully Bayesian approach to jointly inferring spiking activity and neural connectivity from in vivo all-optical perturbation experiments. In contrast to standard approaches that perform spike inference and analysis in two separate maximum-likelihood phases, our joint model is able to propagate uncertainty in spike inference to the inference of connectivity and vice versa. We use the framework of variational autoencoders to model spiking activity using discrete latent variables, low-dimensional latent common input, and sparse spike-and-slab generalized linear coupling between neurons. Additionally, we model two properties of the optogenetic perturbation: off-target photostimulation and photostimulation transients. Our joint model includes at least two sets of discrete random variables; to avoid the dramatic slowdown typically caused by being unable to differentiate such variables, we introduce two strategies that have not, to our knowledge, been used with variational autoencoders. Using this model, we were able to fit models on 30 minutes of data in just 10 minutes. We performed an all-optical circuit mapping experiment in primary visual cortex of the awake mouse, and use our approach to predict neural connectivity between excitatory neurons in layer 2/3. Predicted connectivity is sparse and consistent with known correlations with stimulus tuning, spontaneous correlation and distance.

Histone CENP-A-containing nucleosomes play an important role in nucleating kinetochores at centromeres for chromosome segregation. However, the molecular mechanisms by which CENP-A nucleosomes engage with kinetochore proteins are not well understood. Here, we report the finding of a new function for the budding yeast Cse4/CENP-A histone-fold domain interacting with inner kinetochore protein Mif2/CENP-C. Strikingly, we also discovered that AT-rich centromere DNA has an important role for Mif2 recruitment. Mif2 contacts one side of the nucleosome dyad, engaging with both Cse4 residues and AT-rich nucleosomal DNA. Both interactions are directed by a contiguous DNA- and histone-binding domain (DHBD) harboring the conserved CENP-C motif, an AT hook, and RK clusters (clusters enriched for arginine-lysine residues). Human CENP-C has two related DHBDs that bind preferentially to DNA sequences of higher AT content. Our findings suggest that a DNA composition-based mechanism together with residues characteristic for the CENP-A histone variant contribute to the specification of centromere identity.

Insects, like most animals, tend to steer away from imminent threats [1-7]. Drosophila melanogaster, for example, generally initiate an escape take-off in response to a looming visual stimulus, mimicking a potential predator [8]. The escape response to a visual threat is, however, flexible [9-12] and can alternatively consist of walking backward away from the perceived threat [11], which may be a more effective response to ambush predators such as nymphal praying mantids [7]. Flexibility in escape behavior may also add an element of unpredictability that makes it difficult for predators to anticipate or learn the prey's likely response [3-6]. Whereas the fly's escape jump has been well studied [8, 9, 13-18], the neuronal underpinnings of evasive walking remain largely unexplored. We previously reported the identification of a cluster of descending neurons-the moonwalker descending neurons (MDNs)-the activity of which is necessary and sufficient to trigger backward walking [19], as well as a population of visual projection neurons-the lobula columnar 16 (LC16) cells-that respond to looming visual stimuli and elicit backward walking and turning [11]. Given the similarity of their activation phenotypes, we hypothesized that LC16 neurons induce backward walking via MDNs and that turning while walking backward might reflect asymmetric activation of the left and right MDNs. Here, we present data from functional imaging, behavioral epistasis, and unilateral activation experiments that support these hypotheses. We conclude that LC16 and MDNs are critical components of the neural circuit that transduces threatening visual stimuli into directional locomotor output.