Cholecystokinin-expressing interneurons (CCKIs) are hypothesized to shape pyramidal cell-firing patterns and regulate network oscillations and related network state transitions. To directly probe their role in the CA1 region, we silenced their activity using optogenetic and chemogenetic tools in mice. Opto-tagged CCKIs revealed a heterogeneous population, and their optogenetic silencing triggered wide disinhibitory network changes affecting both pyramidal cells and other interneurons. CCKI silencing enhanced pyramidal cell burst firing and altered the temporal coding of place cells: theta phase precession was disrupted, whereas sequence reactivation was enhanced. Chemogenetic CCKI silencing did not alter the acquisition of spatial reference memories on the Morris water maze but enhanced the recall of contextual fear memories and enabled selective recall when similar environments were tested. This work suggests the key involvement of CCKIs in the control of place-cell temporal coding and the formation of contextual memories.

The brain generates diverse neuron types which express unique homeodomain transcription factors (TFs) and assemble into precise neural circuits. Yet a mechanistic framework is lacking for how homeodomain TFs specify both neuronal fate and synaptic connectivity. We use Drosophila lamina neurons (L1-L5) to show the homeodomain TF Brain-specific homeobox (Bsh) is initiated in lamina precursor cells (LPCs) where it specifies L4/L5 fate and suppresses homeodomain TF Zfh1 to prevent L1/L3 fate. Subsequently, Bsh activates the homeodomain TF Apterous (Ap) in L4 in a feedforward loop to express the synapse recognition molecule DIP-β, in part by Bsh direct binding a DIP-β intron. Thus, homeodomain TFs function hierarchically: primary homeodomain TF (Bsh) first specifies neuronal fate, and subsequently acts with secondary homeodomain TF (Ap) to activate DIP-β, thereby generating precise synaptic connectivity. We speculate that hierarchical homeodomain TF function may represent a general principle for coordinating neuronal fate specification and circuit assembly.

Most mammalian cells prevent viral infection and proliferation by expressing various restriction factors and sensors that activate the immune system. While anti-human immunodeficiency virus type 1 (HIV-1) host restriction factors have been identified, most of them are antagonized by viral proteins. This has severely hindered their development in anti-HIV-1 therapy. Here, we describe CCHC-type zinc-finger-containing protein 3 (ZCCHC3) as a novel anti-HIV-1 factor that is not antagonized by viral proteins. ZCCHC3 suppresses production of HIV-1 and other retroviruses. We show that ZCCHC3 acts by binding to Gag nucleocapsid protein via zinc-finger motifs. This prevents interaction between the Gag nucleocapsid protein and viral genome and results in production of genome-deficient virions. ZCCHC3 also binds to the long terminal repeat on the viral genome via the middle-folded domain, sequestering the viral genome to P-bodies, which leads to decreased viral replication and production. Such a dual antiviral mechanism is distinct from that of any other known host restriction factors. Therefore, ZCCHC3 is a novel potential target in anti-HIV-1 therapy.

The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population’s mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of an evolving population subject to a standard serial dilution protocol. We find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but has a negligible effect when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape.

Reducing fibrous aggregates of protein tau is a possible strategy for halting progression of Alzheimer’s disease (AD). Previously we found that in vitro the D-peptide D-TLKIVWC disassembles tau fibrils from AD brains (AD-tau) into benign segments with no energy source present beyond ambient thermal agitation. This disassembly by a short peptide was unexpected, given that AD-tau is sufficiently stable to withstand disassembly in boiling SDS detergent. To consider D peptide-mediated disassembly as a potential therapeutic for AD, it is essential to understand the mechanism and energy source of the disassembly action. We find assembly of D-peptides into amyloid-like fibrils is essential for tau fibril disassembly. Cryo-EM and atomic force microscopy reveal that these D-peptide fibrils have a right-handed twist and embrace tau fibrils which have a left-handed twist. In binding to the AD-tau fibril, the oppositely twisted D-peptide fibril produces a strain, which is relieved by disassembly of both fibrils. This strain-relief mechanism appears to operate in other examples of amyloid fibril disassembly and provides a new direction for the development of first-in-class therapeutics for amyloid diseases.

In the perception of color, wavelengths of light reflected off objects are transformed into the derived quantities of brightness, saturation and hue. Neurons responding selectively to hue have been reported in primate cortex, but it is unknown how their narrow tuning in color space is produced by upstream circuit mechanisms. We report the discovery of neurons in the Drosophila optic lobe with hue-selective properties, which enables circuit-level analysis of color processing. From our analysis of an electron microscopy volume of a whole Drosophila brain, we construct a connectomics-constrained circuit model that accounts for this hue selectivity. Our model predicts that recurrent connections in the circuit are critical for generating hue selectivity. Experiments using genetic manipulations to perturb recurrence in adult flies confirm this prediction. Our findings reveal a circuit basis for hue selectivity in color vision.

We developed a significantly improved genetically encoded quantitative adenosine triphosphate (ATP) sensor to provide real-time dynamics of ATP levels in subcellular compartments. iATPSnFR2 is a variant of iATPSnFR1, a previously developed sensor that has circularly permuted super-folder GFP inserted between the ATP-binding helices of the ε-subunit of a bacterial F0-F1 ATPase. Optimizing the linkers joining the two domains resulted in a ∼ 5-6 fold improvement in the dynamic range compared to the previous generation sensor, with excellent discrimination against other analytes and affinity variants varying from 4 μM to 500 μM. A chimeric version of this sensor fused to either the HaloTag protein or a suitably spectrally separated fluorescent protein, provides a ratiometric readout allowing comparisons of ATP across cellular regions. Subcellular targeting of the sensor to nerve terminals reveals previously uncharacterized single synapse metabolic signatures, while targeting to the mitochondrial matrix allowed direct quantitative probing of oxidative phosphorylation dynamics.

Light sheet microscopy is a powerful technique for visualizing dynamic biological processes in 3D. Studying large specimens or recording time series with high spatial and temporal resolution generates large datasets, often exceeding terabytes and potentially reaching petabytes in size. Handling these massive datasets is challenging for conventional data processing tools with their memory and performance limitations. To overcome these issues, we developed LLSM5DTools, a software solution specifically designed for the efficient management of petabyte-scale light sheet microscopy data. This toolkit, optimized for memory and per-formance, features fast image readers and writers, efficient geometric transformations, high-performance Richardson-Lucy deconvolution, and scalable Zarr-based stitching. These advancements enable LLSM5DTools to perform over ten times faster than current state-of-the-art methods, facilitating real-time processing of large datasets and opening new avenues for biological discoveries in large-scale imaging experiments.

All multicellular systems produce and dynamically regulate extracellular matrices (ECM) that play important roles in both biochemical and mechanical signaling. Though the spatial arrangement of these extracellular assemblies is critical to their biological functions, visualization of ECM structure is challenging, in part because the biomolecules that compose the ECM are difficult to fluorescently label individually and collectively. Here, we present a cell-impermeable small molecule fluorophore, termed Rhobo6, that turns on and red shifts upon reversible binding to glycans. Given that most ECM components are densely glycosylated, the dye enables wash-free visualization of ECM, in systems ranging from in vitro substrates to in vivo mouse mammary tumors. Relative to existing techniques, Rhobo6 provides a broad substrate profile, superior tissue penetration, nonperturbative labeling, and negligible photobleaching. This work establishes a straightforward method for imaging the distribution of ECM in live tissues and organisms, lowering barriers for investigation of extracellular biology.

The nervous system evolved to enable navigation throughout the environment in the pursuit of resources. Evolutionarily newer structures allowed increasingly complex adaptations but necessarily added redundancy. A dominant view of movement neuroscientists is that there is a one-to-one mapping between brain region and function. However, recent experimental data is hard to reconcile with the most conservative interpretation of this framework, suggesting a degree of functional redundancy during the performance of well-learned, constrained behaviors. This apparent redundancy likely stems from the bidirectional interactions between the various cortical and subcortical structures involved in motor control. We posit that these bidirectional connections enable flexible interactions across structures that change depending upon behavioral demands, such as during acquisition, execution or adaptation of a skill. Observing the system across both multiple actions and behavioral timescales can help isolate the functional contributions of individual structures, leading to an integrated understanding of the neural control of movement.