The mechanisms underlying the evolution of morphology are poorly understood. Distantly related taxa sometimes exhibit correlations between morphological differences and patterns of gene expression, but such comparisons cannot establish how mechanisms evolve to generate diverse morphologies. Answers to these questions require resolution of the nature of developmental evolution within and between closely related species. Here I show how the detailed regulation of the Hox gene Ultrabithorax patterns trichomes on the posterior femur of the second leg in Drosophila melanogaster, and that evolution of Ultrabithorax has contributed to divergence of this feature among closely related species. The cis-regulatory regions of Ultrabithorax, and not the protein itself, appear to have evolved. This study provides experimental evidence that cis-regulatory evolution is one way in which conserved proteins have promoted morphological diversity.

A room-temperature molten salt has been prepared from AuCl3 and 1-ethyl-3-methylimidazolium chloride (EMIC). At a ratio of 1 mol of AuCl3 to 2 mol of EMIC, the salt is a bright yellow-orange and shows Raman spectral features at 170, 328, and 352 cm-1, indicating the presence of AuCl4-. Ab initio calculations indicate that a dinuclear Au2Cl7- species containing a bridging chlorine should be stable, but no such species has been observed.

Navigating animals continuously integrate velocity signals to update internal representations of their directional heading and spatial location in the environment. How neural circuits combine sensory and motor information to construct these velocity estimates and how these self-motion signals, in turn, update internal representations that support navigational computations are not well understood. Recent work in Drosophila has identified a neural circuit that performs angular path integration to compute the fly's head direction, but the nature of the velocity signal is unknown. Here we identify a pair of neurons necessary for angular path integration that encode the fly's rotational velocity with high accuracy using both visual optic flow and motor information. This estimate of rotational velocity does not rely on a moment-to-moment integration of sensory and motor information. Rather, when visual and motor signals are congruent, these neurons prioritize motor information over visual information, and when the two signals are in conflict, reciprocal inhibition selects either the motor or visual signal. Together, our results suggest that flies update their head direction representation by constructing an estimate of rotational velocity that relies primarily on motor information and only incorporates optic flow signals in specific sensorimotor contexts, such as when the motor signal is absent.

Summary Solute carrier family 11 member 1 (SLC11A1) is critical for host resistance to diverse intracellular pathogens. During infection, SLC11A1 limits Salmonella’s access to iron, zinc, and magnesium, but only magnesium deprivation significantly impairs Salmonella replication. To understand the unexpected minor impact of iron, we determined Salmonella’s iron access in infected SLC11A1-deficient and normal mice. Using reporter strains and mass spectrometry of Salmonella purified from the spleen, we found that SLC11A1 caused growth-restricting iron deprivation in a subset of Salmonella. Volume electron microscopy revealed that another Salmonella subset circumvented iron restriction by targeting iron-rich endosomes in macrophages degrading red blood cells (erythrophagocytosis). These iron-replete bacteria dominated overall Salmonella growth, masking the effects of the other Salmonella subset’s iron deprivation. Thus, SLC11A1 effectively sequesters iron, but heterogeneous Salmonella populations partially bypass this nutritional immunity by targeting iron-rich tissue microenvironments.

Serial-section electronmicroscopy (ssEM) is themethod of choice for studyingmacroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so called connectomes. In order to use this data, consisting of up to 10 individual EM images, it must be assembled into a volume, requiring seamless 2D stitching from each physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP (Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of the Render (27) services used in the volume assembly of the brain of adult Drosophilamelanogaster (30). It achieves high throughput by operating on themeta-data and transformations of each image stored in a database, thus eliminating the need to render intermediate output. ASAP ismodular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous stitching of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex (28; 8) at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a prominent tool to study computations in the brain. With an increasing size and complexity of neural recordings, there is a need for fast algorithms that can scale to large datasets. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation allows training networks to reproduce neural activity of an order of millions neurons at order of magnitude times faster than the CPU implementation. We demonstrate this by applying our algorithm to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables efficient training of large-scale spiking models, thus allowing for in-silico study of the dynamics and connectivity underlying multi-area computations.

Morphogen gradients are used in developing embryos, where they subdivide a field of cells into territories characterized by distinct cell fate potentials. Such systems require both a spatially-graded distribution of the morphogen, and an ability to encode different responses at different target genes. However, the potential for different temporal responses is also present because morphogen gradients typically provide temporal cues, which may be a potential source of conflict. Thus, a low threshold response adapted for an early temporal onset may be inappropriate when the desired spatial response is a spatially-limited, high-threshold expression pattern. Here, we identify such a case with the Drosophila vnd locus, which is a target of the dorsal (dl) nuclear concentration gradient that patterns the dorsal/ventral (D/V) axis of the embryo. The vnd gene plays a critical role in the "ventral dominance" hierarchy of vnd, ind, and msh, which individually specify distinct D/V neural columnar fates in increasingly dorsal ectodermal compartments. The role of vnd in this regulatory hierarchy requires early temporal expression, which is characteristic of low-threshold responses, but its specification of ventral neurogenic ectoderm demands a relatively high-threshold response to dl. We show that the Neurogenic Ectoderm Enhancer (NEE) at vnd takes additional input from the complementary Dpp gradient via a conserved Schnurri/Mad/Medea silencer element (SSE) unlike NEEs at brk, sog, rho, and vn. These results show how requirements for conflicting temporal and spatial responses to the same gradient can be solved by additional inputs from complementary gradients.

Climbing over chasms larger than step size is vital to fruit flies, since foraging and mating are achieved while walking. Flies avoid futile climbing attempts by processing parallax-motion vision to estimate gap width. To identify neuronal substrates of climbing control, we screened a large collection of fly lines with temporarily inactivated neuronal populations in a novel high-throughput assay described here. The observed climbing phenotypes were classified; lines in each group are reported. Selected lines were further analysed by high-resolution video cinematography. One striking class of flies attempts to climb chasms of unsurmountable width; expression analysis guided us to C2 optic-lobe interneurons. Inactivation of C2 or the closely related C3 neurons with highly specific intersectional driver lines consistently reproduced hyperactive climbing whereas strong or weak artificial depolarization of C2/C3 neurons strongly or mildly decreased climbing frequency. Contrast-manipulation experiments support our conclusion that C2/C3 neurons are part of the distance-evaluation system.

ro(Dom) is a dominant allele of rough (ro) that results in reduced eye size due to premature arrest in morphogenetic furrow (MF) progression. We found that the ro(Dom) stop-furrow phenotype was sensitive to the dosage of genes known to affect retinal differentiation, in particular members of the hedgehog (hh) signaling cascade. We demonstrate that ro(Dom) interferes with Hh's ability to induce the retina-specific proneural gene atonal (ato) in the MF and that normal eye size can be restored by providing excess Ato protein. We used ro(Dom) as a sensitive genetic background in which to identify mutations that affect hh signal transduction or regulation of ato expression. In addition to mutations in several unknown loci, we recovered multiple alleles of groucho (gro) and Hairless (H). Analysis of their phenotypes in somatic clones suggests that both normally act to restrict neuronal cell fate in the retina, although they control different aspects of ato's complex expression pattern.

Precise, repeatable genetic access to specific neurons via GAL4/UAS and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which generally lack the single-cell resolution required for reliable cell type identification. Here we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 74,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between neurons identified by electron or light microscopy. Identifying individual neurons that make up each GAL4 expression pattern improves the prediction of split-GAL4 combinations targeting particular neurons. To this end we have made the images searchable on the NeuronBridge website. We demonstrate the potential of NeuronBridge to rapidly and effectively identify neuron matches based on morphology across imaging modalities and datasets.