Real-time lineage tracing in flies gets a boost with three techniques to specifically label a progenitor’s daughter cells.

The shapes of dendritic arbors are fascinating and important, yet the principles underlying these complex and diverse structures remain unclear. Here, we analyzed basal dendritic arbors of 2,171 pyramidal neurons sampled from mammalian brains and discovered 3 statistical properties: the dendritic arbor size scales with the total dendritic length, the spatial correlation of dendritic branches within an arbor has a universal functional form, and small parts of an arbor are self-similar. We proposed that these properties result from maximizing the repertoire of possible connectivity patterns between dendrites and surrounding axons while keeping the cost of dendrites low. We solved this optimization problem by drawing an analogy with maximization of the entropy for a given energy in statistical physics. The solution is consistent with the above observations and predicts scaling relations that can be tested experimentally. In addition, our theory explains why dendritic branches of pyramidal cells are distributed more sparsely than those of Purkinje cells. Our results represent a step toward a unifying view of the relationship between neuronal morphology and function.

Gene expression patterns can be useful in understanding the structural organization of the brain and the regulatory logic that governs its myriad cell types. A particularly rich source of spatial expression data is the Allen Brain Atlas (ABA), a comprehensive genome-wide in situ hybridization study of the adult mouse brain. Here, we present an open-source program, ALLENMINER, that searches the ABA for genes that are expressed, enriched, patterned or graded in a user-specified region of interest.

In holometabolous insects, a species-specific size, known as critical weight, needs to be reached for metamorphosis to be initiated in the absence of further nutritional input. Previously, we found that reaching critical weight depends on the insulin-dependent growth of the prothoracic glands (PGs) in Drosophila larvae. Because the PGs produce the molting hormone ecdysone, we hypothesized that ecdysone signaling switches the larva to a nutrition-independent mode of development post-critical weight. Wing discs from pre-critical weight larvae [5 hours after third instar ecdysis (AL3E)] fed on sucrose alone showed suppressed Wingless (WG), Cut (CT) and Senseless (SENS) expression. Post-critical weight, a sucrose-only diet no longer suppressed the expression of these proteins. Feeding larvae that exhibit enhanced insulin signaling in their PGs at 5 hours AL3E on sucrose alone produced wing discs with precocious WG, CT and SENS expression. In addition, knocking down the Ecdysone receptor (EcR) selectively in the discs also promoted premature WG, CUT and SENS expression in the wing discs of sucrose-fed pre-critical weight larvae. EcR is involved in gene activation when ecdysone is present, and gene repression in its absence. Thus, knocking down EcR derepresses genes that are normally repressed by unliganded EcR, thereby allowing wing patterning to progress. In addition, knocking down EcR in the wing discs caused precocious expression of the ecdysone-responsive gene broad. These results suggest that post-critical weight, EcR signaling switches wing discs to a nutrition-independent mode of development via derepression.

A comprehensive understanding of the brain requires the analysis of individual neurons. We used twin-spot mosaic analysis with repressible cell markers (twin-spot MARCM) to trace cell lineages at high resolution by independently labeling paired sister clones. We determined patterns of neurogenesis and the influences of lineage on neuron-type specification. Notably, neural progenitors were able to yield intermediate precursors that create one, two or more neurons. Furthermore, neurons acquired stereotyped projections according to their temporal position in various brain sublineages. Twin-spot MARCM also permitted birth dating of mutant clones, enabling us to detect a single temporal fate that required chinmo in a sublineage of six Drosophila central complex neurons. In sum, twin-spot MARCM can reveal the developmental origins of neurons and the mechanisms that underlie cell fate.

The Escherichia coli chemotaxis network is a model system for biological signal processing. In E. coli, transmembrane receptors responsible for signal transduction assemble into large clusters containing several thousand proteins. These sensory clusters have been observed at cell poles and future division sites. Despite extensive study, it remains unclear how chemotaxis clusters form, what controls cluster size and density, and how the cellular location of clusters is robustly maintained in growing and dividing cells. Here, we use photoactivated localization microscopy (PALM) to map the cellular locations of three proteins central to bacterial chemotaxis (the Tar receptor, CheY, and CheW) with a precision of 15 nm. We find that cluster sizes are approximately exponentially distributed, with no characteristic cluster size. One-third of Tar receptors are part of smaller lateral clusters and not of the large polar clusters. Analysis of the relative cellular locations of 1.1 million individual proteins (from 326 cells) suggests that clusters form via stochastic self-assembly. The super-resolution PALM maps of E. coli receptors support the notion that stochastic self-assembly can create and maintain approximately periodic structures in biological membranes, without direct cytoskeletal involvement or active transport.

Commentary: Our goal as tool developers is to invent methods capable of uncovering new biological insights unobtainable by pre-existing technologies. A terrific example is given by this paper, where grad students Derek Greenfield and Ann McEvoy in Jan Liphardt’s group at Berkeley used our PALM to image the size and position distributions of chemotaxis proteins in E. Coli with unprecedented precision and sensitivity. Their analysis revealed that the cluster sizes follow a stretched exponential distribution, and the density of clusters is highest furthest away from the largest (e.g., polar) clusters. Both observations support a model for passive self-assembly rather than active cytoskeletal assembly of the chemotaxis network.

We have demonstrated super-resolution imaging of protein distributions in cells at depth at multiple layers with a lateral localization precision better than 50 nm. The approach is based on combining photoactivated localization microscopy with temporal focusing.