Many cellular functions rely on DNA-binding proteins finding and associating to specific sites in the genome. Yet the mechanisms underlying the target search remain poorly understood, especially in the case of the highly organized mammalian cell nucleus. Using as a model Tet repressors (TetRs) searching for a multi-array locus, we quantitatively analyse the search process in human cells with single-molecule tracking and single-cell protein-DNA association measurements. We find that TetRs explore the nucleus and reach their target by 3D diffusion interspersed with transient interactions with non-cognate sites, consistent with the facilitated diffusion model. Remarkably, nonspecific binding times are broadly distributed, underlining a lack of clear delimitation between specific and nonspecific interactions. However, the search kinetics is not determined by diffusive transport but by the low association rate to nonspecific sites. Altogether, our results provide a comprehensive view of the recruitment dynamics of proteins at specific loci in mammalian cells.

The mouse is an increasingly prominent model for the analysis of mammalian neuronal circuits. Neural circuits ultimately have to be probed during behaviors that engage the circuits. Linking circuit dynamics to behavior requires precise control of sensory stimuli and measurement of body movements. Head-fixation has been used for behavioral research, particularly in non-human primates, to facilitate precise stimulus control, behavioral monitoring and neural recording. However, choice-based, perceptual decision tasks by head-fixed mice have only recently been introduced. Training mice relies on motivating mice using water restriction. Here we describe procedures for head-fixation, water restriction and behavioral training for head-fixed mice, with a focus on active, whisker-based tactile behaviors. In these experiments mice had restricted access to water (typically 1 ml/day). After ten days of water restriction, body weight stabilized at approximately 80% of initial weight. At that point mice were trained to discriminate sensory stimuli using operant conditioning. Head-fixed mice reported stimuli by licking in go/no-go tasks and also using a forced choice paradigm using a dual lickport. In some cases mice learned to discriminate sensory stimuli in a few trials within the first behavioral session. Delay epochs lasting a second or more were used to separate sensation (e.g. tactile exploration) and action (i.e. licking). Mice performed a variety of perceptual decision tasks with high performance for hundreds of trials per behavioral session. Up to four months of continuous water restriction showed no adverse health effects. Behavioral performance correlated with the degree of water restriction, supporting the importance of controlling access to water. These behavioral paradigms can be combined with cellular resolution imaging, random access photostimulation, and whole cell recordings.

3D snapshot microscopy enables fast volumetric imaging by capturing a 3D volume in a single 2D camera image and performing computational reconstruction. Fast volumetric imaging has a variety of biological applications such as whole brain imaging of rapid neural activity in larval zebrafish. The optimal microscope design for this optical 3D-to-2D encoding is both sample- and task-dependent, with no general solution known. Deep learning based decoders can be combined with a differentiable simulation of an optical encoder for end-to-end optimization of both the deep learning decoder and optical encoder. This technique has been used to engineer local optical encoders for other problems such as depth estimation, 3D particle localization, and lensless photography. However, 3D snapshot microscopy is known to require a highly non-local optical encoder which existing UNet-based decoders are not able to engineer. We show that a neural network architecture based on global kernel Fourier convolutional neural networks can efficiently decode information from multiple depths in a volume, globally encoded across a 3D snapshot image. We show in simulation that our proposed networks succeed in engineering and reconstructing optical encoders for 3D snapshot microscopy where the existing state-of-the-art UNet architecture fails. We also show that our networks outperform the state-of-the-art learned reconstruction algorithms for a computational photography dataset collected on a prototype lensless camera which also uses a highly non-local optical encoding.

Liposomes are essential vehicles for membrane protein reconstitution and drug delivery, making them vital tools in both in vivo and in vitro studies. However, the lack of robust techniques for the precise arrangement of these synthetic vesicles limits their potential applications. Here, we present a modular polymerization platform based on square DNA origami to template the formation and organization of liposomes. By programming the sequence, number, position, chirality, and flexibility of sticky ends on each square, we assemble uniformly sized liposomes into diverse two-dimensional (2D) arrays, as well as finite lattices and rings. Additionally, we demonstrate stepwise assembly and targeted disassembly, enabling dynamic structural control. These complex liposome architectures represent a significant advancement in the fields of biotechnology, nanotechnology, and bottom-up biology.

Liposomes are essential vehicles for membrane protein reconstitution and drug delivery, making them vital tools in both in vivo and in vitro studies. However, the lack of robust techniques for the precise arrangement of these synthetic vesicles limits their potential applications. Here, we present a modular polymerization platform based on square DNA origami to template the formation and organization of liposomes. By programming the sequence, number, position, chirality, and flexibility of sticky ends on each square, we assemble uniformly sized liposomes into diverse two-dimensional (2D) arrays, as well as finite lattices and rings. Additionally, we demonstrate stepwise assembly and targeted disassembly, enabling dynamic structural control. These complex liposome architectures represent a significant advancement in the fields of biotechnology, nanotechnology, and bottom-up biology.

The brain receives information about the direction of object motion from several types of retinal ganglion cells (RGCs). On-Off direction-selective (DS) RGCs respond preferentially to stimuli moving quickly in one of four directions and provide a significant (but difficult to quantify) fraction of RGC input to the SC. On DS RGCs, in comparison, respond preferentially to stimuli moving slowly in one of three directions and are thought to only target retinorecipient nuclei comprising the accessory optic system, e.g., the medial terminal nucleus (MTN). To determine the fraction of SC-projecting RGCs that exhibit direction selectivity, and the specificity with which On-Off and On DS RGCs target retinorecipient areas, we performed optical and electrophysiological recordings from RGCs retrogradely labeled from the mouse SC and MTN. We found, surprisingly, that both On-Off and On DS RGCs innervate the SC; collectively they constitute nearly 40% of SC-projecting RGCs. In comparison, only On DS RGCs project to the MTN. Subsequent experiments revealed that individual On DS RGCs innervate either the SC or MTN and exhibit robust projection-specific differences in somatodendritic morphology, cellular excitability, and light-evoked activity; several projection-specific differences in the output of On DS RGCs correspond closely to differences in excitatory synaptic input the cells receive. Our results reveal a robust projection of On DS RGCs to the SC, projection-specific differences in the response properties of On DS RGCs, and biophysical and synaptic mechanisms that underlie these functional differences.

The Drosophila mushroom body (MB) is a key associative memory center that has also been implicated in the control of sleep. However, the identity of MB neurons underlying homeostatic sleep regulation, as well as the types of sleep signals generated by specific classes of MB neurons, has remained poorly understood. We recently identified two MB output neuron (MBON) classes whose axons convey sleep control signals from the MB to converge in the same downstream target region: a cholinergic sleep-promoting MBON class and a glutamatergic wake-promoting MBON class. Here, we deploy a combination of neurogenetic, behavioral, and physiological approaches to identify and mechanistically dissect sleep-controlling circuits of the MB. Our studies reveal the existence of two segregated excitatory synaptic microcircuits that propagate homeostatic sleep information from different populations of intrinsic MB "Kenyon cells" (KCs) to specific sleep-regulating MBONs: sleep-promoting KCs increase sleep by preferentially activating the cholinergic MBONs, while wake-promoting KCs decrease sleep by preferentially activating the glutamatergic MBONs. Importantly, activity of the sleep-promoting MB microcircuit is increased by sleep deprivation and is necessary for homeostatic rebound sleep (i.e., the increased sleep that occurs after, and in compensation for, sleep lost during deprivation). These studies reveal for the first time specific functional connections between subsets of KCs and particular MBONs and establish the identity of synaptic microcircuits underlying transmission of homeostatic sleep signals in the MB.

Locomotion requires coordinated motor activity throughout an animal's body. In both vertebrates and invertebrates, chains of coupled central pattern generators (CPGs) are commonly evoked to explain local rhythmic behaviors. In C. elegans, we report that proprioception within the motor circuit is responsible for propagating and coordinating rhythmic undulatory waves from head to tail during forward movement. Proprioceptive coupling between adjacent body regions transduces rhythmic movement initiated near the head into bending waves driven along the body by a chain of reflexes. Using optogenetics and calcium imaging to manipulate and monitor motor circuit activity of moving C. elegans held in microfluidic devices, we found that the B-type cholinergic motor neurons transduce the proprioceptive signal. In C. elegans, a sensorimotor feedback loop operating within a specific type of motor neuron both drives and organizes body movement.