mRNA translation is a key step in decoding genetic information. Genetic decoding is surprisingly heterogeneous, as multiple distinct polypeptides can be synthesized from a single mRNA sequence. To study translational heterogeneity, we developed the MoonTag, a new fluorescence labeling system to visualize translation of single mRNAs. When combined with the orthogonal SunTag system, the MoonTag enables dual readouts of translation, greatly expanding the possibilities to interrogate complex translational heterogeneity. By placing MoonTag and SunTag sequences in different translation reading frames, each driven by distinct translation start sites, start site selection of individual ribosomes can be visualized in real-time. We find that start site selection is largely stochastic, but that the probability of using a particular start site differs among mRNA molecules, and can be dynamically regulated over time. Together, this study provides key insights into translation start site selection heterogeneity, and provides a powerful toolbox to visualize complex translation dynamics.

Accurate tracking of the same neurons across multiple days is crucial for studying changes in neuronal activity during learning and adaptation. Advances in high-density extracellular electrophysiology recording probes, such as Neuropixels, provide a promising avenue to accomplish this goal. Identifying the same neurons in multiple recordings is, however, complicated by non-rigid movement of the tissue relative to the recording sites (drift) and loss of signal from some neurons. Here, we propose a neuron tracking method that can identify the same cells independent of firing statistics, that are used by most existing methods. Our method is based on between-day non-rigid alignment of spike-sorted clusters. We verified the same cell identity in mice using measured visual receptive fields. This method succeeds on datasets separated from 1 to 47 days, with an 84% average recovery rate.

Visually guided decision-making requires integration of information from distributed brain areas, necessitating a brain-wide approach to examine its neural mechanisms. New tools in Drosophila melanogaster enable circuits spanning the brain to be charted with single cell-type resolution. Here, we highlight recent advances uncovering the computations and circuits that transform and integrate visual information across the brain to make behavioral choices. Visual information flows from the optic lobes to three primary central brain regions: a sensorimotor mapping area and two 'higher' centers for memory or spatial orientation. Rapid decision-making during predator evasion emerges from the spike timing dynamics in parallel sensorimotor cascades. Goal-directed decisions may occur through memory, navigation and valence processing in the central complex and mushroom bodies.

Visually guided decision-making requires integration of information from distributed brain areas, necessitating a brain-wide approach to examine its neural mechanisms. New tools in Drosophila melanogaster enable circuits spanning the brain to be charted with single cell-type resolution. Here, we highlight recent advances uncovering the computations and circuits that transform and integrate visual information across the brain to make behavioral choices. Visual information flows from the optic lobes to three primary central brain regions: a sensorimotor mapping area and two 'higher' centers for memory or spatial orientation. Rapid decision-making during predator evasion emerges from the spike timing dynamics in parallel sensorimotor cascades. Goal-directed decisions may occur through memory, navigation and valence processing in the central complex and mushroom bodies.

Progress in modern neuroscience critically depends on our ability to observe the activity of large neuronal populations with cellular spatial and high temporal resolution. However, two bottlenecks constrain efforts towards fast imaging of large populations. First, the resulting large video data is challenging to analyze. Second, there is an explicit tradeoff between imaging speed, signal-to-noise, and field of view: with current recording technology we cannot image very large neuronal populations with simultaneously high spatial and temporal resolution. Here we describe multi-scale approaches for alleviating both of these bottlenecks. First, we show that spatial and temporal decimation techniques based on simple local averaging provide order-of-magnitude speedups in spatiotemporally demixing calcium video data into estimates of single-cell neural activity. Second, once the shapes of individual neurons have been identified at fine scale (e.g., after an initial phase of conventional imaging with standard temporal and spatial resolution), we find that the spatial/temporal resolution tradeoff shifts dramatically: after demixing we can accurately recover denoised fluorescence traces and deconvolved neural activity of each individual neuron from coarse scale data that has been spatially decimated by an order of magnitude. This offers a cheap method for compressing this large video data, and also implies that it is possible to either speed up imaging significantly, or to "zoom out" by a corresponding factor to image order-of-magnitude larger neuronal populations with minimal loss in accuracy or temporal resolution.

The mammalian brain is best understood as a multi-scale hierarchical neural system, in the sense that connection and function occur on multiple scales from micro to macro. Modern genomic-scale expression profiling can provide insight into methodologies that elucidate this architecture. We present a methodology for understanding the relationship of gene expression and neuroanatomy based on correlation between gene expression profiles across tissue samples. A resulting tool, NeuroBlast, can identify networks of genes co-expressed within or across neuroanatomic structures. The method applies to any data modality that can be mapped with sufficient spatial resolution, and provides a computation technique to elucidate neuroanatomy via patterns of gene expression on spatial and temporal scales. In addition, from the perspective of spatial location, we discuss a complementary technique that identifies gene classes that contribute to defining anatomic patterns.

During development, coordinated cell behaviors orchestrate tissue and organ morphogenesis. Detailed descriptions of cell lineages and behaviors provide a powerful framework to elucidate the mechanisms of morphogenesis. To study the cellular basis of limb development, we imaged transgenic fluorescently-labeled embryos from the crustacean Parhyale hawaiensis with multi-view light-sheet microscopy at high spatiotemporal resolution over several days of embryogenesis. The cell lineage of outgrowing thoracic limbs was reconstructed at single-cell resolution with new software called Massive Multi-view Tracker (MaMuT). In silico clonal analyses suggested that the early limb primordium becomes subdivided into anterior-posterior and dorsal-ventral compartments whose boundaries intersect at the distal tip of the growing limb. Limb-bud formation is associated with spatial modulation of cell proliferation, while limb elongation is also driven by preferential orientation of cell divisions along the proximal-distal growth axis. Cellular reconstructions were predictive of the expression patterns of limb development genes including the BMP morphogen Decapentaplegic.

The choroid plexus is a major site for cerebrospinal fluid (CSF) production, characterized by a multiciliated epithelial monolayer that regulates CSF production. We demonstrate that defective choroid plexus ciliogenesis or intraflagellar transport yields neonatal hydrocephalus, at least in part due to increased water channel Aqp1 and ion transporter Atp1a2 expression. We demonstrate choroid plexus multicilia as sensory cilia, transducing both canonical and non-canonical Sonic Hedgehog (Shh) signaling. Interestingly, it is the non-canonical Shh signaling that represses Aqp1 and Atp1a2 expression by the Smoothened (Smo)/Gαi/cyclic AMP (cAMP) pathway. Choroid plexus multicilia exhibit unique ciliary ultrastructure, carrying features of both primary and motile cilia. Unlike most cilia that elongate during maturation, choroid plexus ciliary length decreases during development, causing a decline of Shh signaling intensity in the developing choroid plexus, a derepression of Aqp1 and Atp1a2, and, ultimately, increased CSF production. Hence, the developmental dynamics of choroid plexus multicilia dampens the Shh signaling intensity to promote CSF production.

bioRxiv Preprint: https://www.biorxiv.org/content/early/2025/01/22/2025.01.21.633415

Recent methods have revealed that cells on planar substrates exert both shear (in-plane) and normal (out-of-plane) tractions against the extracellular matrix (ECM). However, the location and origin of the normal tractions with respect to the adhesive and cytoskeletal elements of cells have not been elucidated. We developed a high-spatiotemporal-resolution, multidimensional (2.5D) traction force microscopy to measure and model the full 3D nature of cellular forces on planar 2D surfaces. We show that shear tractions are centered under elongated focal adhesions whereas upward and downward normal tractions are detected on distal (toward the cell edge) and proximal (toward the cell body) ends of adhesions, respectively. Together, these forces produce significant rotational moments about focal adhesions in both protruding and retracting peripheral regions. Temporal 2.5D traction force microscopy analysis of migrating and spreading cells shows that these rotational moments are highly dynamic, propagating outward with the leading edge of the cell. Finally, we developed a finite element model to examine how rotational moments could be generated about focal adhesions in a thin lamella. Our model suggests that rotational moments can be generated largely via shear lag transfer to the underlying ECM from actomyosin contractility applied at the intracellular surface of a rigid adhesion of finite thickness. Together, these data demonstrate and probe the origin of a previously unappreciated multidimensional stress profile associated with adhesions and highlight the importance of new approaches to characterize cellular forces.