Chemosensory detection of polyamine metabolites guides C. elegans to nutritive microbes.

Much is known about molecular mechanisms by which animals detect pathogenic microbes, but how animals sense beneficial microbes remains poorly understood. The roundworm Caenorhabditis elegans is a microbivore that must distinguish nutritive microbes from pathogens. We characterized a neural circuit used by C. elegans to rapidly discriminate between nutritive bacteria and pathogens. Distinct sensory neuron populations responded to chemical cues from nutritive Escherichia coli and pathogenic Enterococcus faecalis, and these neural signals are decoded by downstream AIB interneurons. The polyamine metabolites cadaverine, putrescine, and spermidine produced by E. coli activate this neural circuit and elicit positive chemotaxis. Our study shows how polyamine odorants can be sensed by animals as proxies for microbe identity and suggests that, hence, polyamines might have widespread roles brokering host-microbe interactions.

Lewy body dementia: Overcoming barriers and identifying solutions.

Despite its high prevalence among dementias, Lewy body dementia (LBD) remains poorly understood with a limited, albeit growing, evidence base. The public-health burden that LBD imposes is worsened by overlapping pathologies, which contribute to misdiagnosis, and lack of treatments. For this report, we gathered and analyzed public-domain information on advocacy, funding, research outputs, and the therapeutic pipeline to identify gaps in each of these key elements. To further understand the current gaps, we also conducted interviews with leading experts in regulatory/governmental agencies, LBD advocacy, academic research, and biopharmaceutical research, as well as with funding sources. We identified wide gaps across the entire landscape, the most critical being in research. Many of the experts participated in a workshop to discuss the prioritization of research areas with a view to accelerating therapeutic development and improving patient care. This white paper outlines the opportunities for bridging the major LBD gaps and creates the framework for collaboration in that endeavor. HIGHLIGHTS: A group representing academia, government, industry, and consulting expertise was convened to discuss current progress in Dementia with Lewy Body care and research. Consideration of expert opinion,natural language processing of the literature as well as publicly available data bases, and Delphi inspired discussion led to a proposed consensus document of priorities for the field.

High-fidelity encoding of mechanostimuli by tactile food-sensing neurons requires an ensemble of ion channels.

The nematode C. elegans uses mechanosensitive neurons to detect bacteria, which are food for worms. These neurons release dopamine to suppress foraging and promote dwelling. Through a screen of genes highly expressed in dopaminergic food-sensing neurons, we identify a K2P-family potassium channel-TWK-2-that damps their activity. Strikingly, loss of TWK-2 restores mechanosensation to neurons lacking the NOMPC-like channel transient receptor potential 4 (TRP-4), which was thought to be the primary mechanoreceptor for tactile food sensing. The alternate mechanoreceptor mechanism uncovered by TWK-2 mutation requires three Deg/ENaC channel subunits: ASIC-1, DEL-3, and UNC-8. Analysis of cell-physiological responses to mechanostimuli indicates that TRP and Deg/ENaC channels work together to set the range of analog encoding of stimulus intensity and to improve signal-to-noise characteristics and temporal fidelity of food-sensing neurons. We conclude that a specialized mechanosensory modality-tactile food sensing-emerges from coordination of distinct force-sensing mechanisms housed in one type of sensory neuron.

Controlling human organoid symmetry breaking reveals signaling gradients drive segmentation clock waves.

Axial development of mammals involves coordinated morphogenetic events, including axial elongation, somitogenesis, and neural tube formation. To gain insight into the signals controlling the dynamics of human axial morphogenesis, we generated axially elongating organoids by inducing anteroposterior symmetry breaking of spatially coupled epithelial cysts derived from human pluripotent stem cells. Each organoid was composed of a neural tube flanked by presomitic mesoderm sequentially segmented into somites. Periodic activation of the somite differentiation gene MESP2 coincided in space and time with anteriorly traveling segmentation clock waves in the presomitic mesoderm of the organoids, recapitulating critical aspects of somitogenesis. Timed perturbations demonstrated that FGF and WNT signaling play distinct roles in axial elongation and somitogenesis, and that FGF signaling gradients drive segmentation clock waves. By generating and perturbing organoids that robustly recapitulate the architecture of multiple axial tissues in human embryos, this work offers a means to dissect mechanisms underlying human embryogenesis.

Controlling organoid symmetry breaking uncovers an excitable system underlying human axial elongation.

The human embryo breaks symmetry to form the anterior-posterior axis of the body. As the embryo elongates along this axis, progenitors in the tail bud give rise to tissues that generate spinal cord, skeleton, and musculature. This raises the question of how the embryo achieves axial elongation and patterning. While ethics necessitate in vitro studies, the variability of organoid systems has hindered mechanistic insights. Here, we developed a bioengineering and machine learning framework that optimizes organoid symmetry breaking by tuning their spatial coupling. This framework enabled reproducible generation of axially elongating organoids, each possessing a tail bud and neural tube. We discovered that an excitable system composed of WNT/FGF signaling drives elongation by inducing a neuromesodermal progenitor-like signaling center. We discovered that instabilities in the excitable system are suppressed by secreted WNT inhibitors. Absence of these inhibitors led to ectopic tail buds and branches. Our results identify mechanisms governing stable human axial elongation.

Modulating mesendoderm competence during human germ layer differentiation.

As pluripotent human embryonic stem cells progress toward one germ layer fate, they lose the ability to adopt alternative fates. Using a low-dimensional reaction coordinate to monitor progression toward ectoderm, we show that a differentiating stem cell's probability of adopting a mesendodermal fate given appropriate signals falls sharply at a point along the ectoderm trajectory. We use this reaction coordinate to prospectively isolate and profile differentiating cells based on their mesendoderm competence and analyze their RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) profiles to identify transcription factors that control the cell's mesendoderm competence. By modulating these key transcription factors, we can expand or contract the window of competence to adopt the mesendodermal fate along the ectodermal differentiation trajectory. The ability of the underlying gene regulatory network to modulate competence is essential for understanding human development and controlling the fate choices of stem cells in vitro.

Discovering a sparse set of pairwise discriminating features in high-dimensional data.

MOTIVATION: Recent technological advances produce a wealth of high-dimensional descriptions of biological processes, yet extracting meaningful insight and mechanistic understanding from these data remains challenging. For example, in developmental biology, the dynamics of differentiation can now be mapped quantitatively using single-cell RNA sequencing, yet it is difficult to infer molecular regulators of developmental transitions. Here, we show that discovering informative features in the data is crucial for statistical analysis as well as making experimental predictions. RESULTS: We identify features based on their ability to discriminate between clusters of the data points. We define a class of problems in which linear separability of clusters is hidden in a low-dimensional space. We propose an unsupervised method to identify the subset of features that define a low-dimensional subspace in which clustering can be conducted. This is achieved by averaging over discriminators trained on an ensemble of proposed cluster configurations. We then apply our method to single-cell RNA-seq data from mouse gastrulation, and identify 27 key transcription factors (out of 409 total), 18 of which are known to define cell states through their expression levels. In this inferred subspace, we find clear signatures of known cell types that eluded classification prior to discovery of the correct low-dimensional subspace. AVAILABILITY AND IMPLEMENTATION: https://github.com/smelton/SMD. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mouse embryo geometry drives formation of robust signaling gradients through receptor localization.

Morphogen signals are essential for cell fate specification during embryogenesis. Some receptors that sense these morphogens are known to localize to only the apical or basolateral membrane of polarized cell lines in vitro. How such localization affects morphogen sensing and patterning in the developing embryo remains unknown. Here, we show that the formation of a robust BMP signaling gradient in the early mouse embryo depends on the restricted, basolateral localization of BMP receptors. The mis-localization of receptors to the apical membrane results in ectopic BMP signaling in the mouse epiblast in vivo. With evidence from mathematical modeling, human embryonic stem cells in vitro, and mouse embryos in vivo, we find that the geometric compartmentalization of BMP receptors and ligands creates a signaling gradient that is buffered against fluctuations. Our results demonstrate the importance of receptor localization and embryo geometry in shaping morphogen signaling during embryogenesis.

A compressed sensing framework for efficient dissection of neural circuits.

A fundamental question in neuroscience is how neural networks generate behavior. The lack of genetic tools and unique promoters to functionally manipulate specific neuronal subtypes makes it challenging to determine the roles of individual subtypes in behavior. We describe a compressed sensing-based framework in combination with non-specific genetic tools to infer candidate neurons controlling behaviors with fewer measurements than previously thought possible. We tested this framework by inferring interneuron subtypes regulating the speed of locomotion of the nematode Caenorhabditis elegans. We developed a real-time stabilization microscope for accurate long-term, high-magnification imaging and targeted perturbation of neural activity in freely moving animals to validate our inferences. We show that a circuit of three interconnected interneuron subtypes, RMG, AVB and SIA control different aspects of locomotion speed as the animal navigates its environment. Our work suggests that compressed sensing approaches can be used to identify key nodes in complex biological networks.

Single-Cell Profiling of an In Vitro Model of Human Interneuron Development Reveals Temporal Dynamics of Cell Type Production and Maturation.

GABAergic interneurons are essential for neural circuit function, and their loss or dysfunction is implicated in human neuropsychiatric disease. In vitro methods for interneuron generation hold promise for studying human cellular and functional properties and, ultimately, for therapeutic cell replacement. Here we describe a protocol for generating cortical interneurons from hESCs and analyze the properties and maturation time course of cell types using single-cell RNA-seq. We find that the cell types produced mimic in vivo temporal patterns of neuron and glial production, with immature progenitors and neurons observed early and mature cortical neurons and glial cell types produced late. By comparing the transcriptomes of immature interneurons to those of more mature neurons, we identified genes important for human interneuron differentiation. Many of these genes were previously implicated in neurodevelopmental and neuropsychiatric disorders.

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states.

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development.

Discovering sparse transcription factor codes for cell states and state transitions during development.

Computational analysis of gene expression to determine both the sequence of lineage choices made by multipotent cells and to identify the genes influencing these decisions is challenging. Here we discover a pattern in the expression levels of a sparse subset of genes among cell types in B- and T-cell developmental lineages that correlates with developmental topologies. We develop a statistical framework using this pattern to simultaneously infer lineage transitions and the genes that determine these relationships. We use this technique to reconstruct the early hematopoietic and intestinal developmental trees. We extend this framework to analyze single-cell RNA-seq data from early human cortical development, inferring a neocortical-hindbrain split in early progenitor cells and the key genes that could control this lineage decision. Our work allows us to simultaneously infer both the identity and lineage of cell types as well as a small set of key genes whose expression patterns reflect these relationships.

A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development.

During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/ß-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders.

Fixed single-cell transcriptomic characterization of human radial glial diversity.

The diverse progenitors that give rise to the human neocortex have been difficult to characterize because progenitors, particularly radial glia (RG), are rare and are defined by a combination of intracellular markers, position and morphology. To circumvent these problems, we developed Fixed and Recovered Intact Single-cell RNA (FRISCR), a method for profiling the transcriptomes of individual fixed, stained and sorted cells. Using FRISCR, we profiled primary human RG that constitute only 1% of the midgestation cortex and classified them as ventricular zone-enriched RG (vRG) that express ANXA1 and CRYAB, and outer subventricular zone-localized RG (oRG) that express HOPX. Our study identified vRG and oRG markers and molecular profiles, an essential step for understanding human neocortical progenitor development. FRISCR allows targeted single-cell profiling of any tissues that lack live-cell markers.

Controlling interneuron activity in Caenorhabditis elegans to evoke chemotactic behaviour.

Animals locate and track chemoattractive gradients in the environment to find food. With its small nervous system, Caenorhabditis elegans is a good model system in which to understand how the dynamics of neural activity control this search behaviour. Extensive work on the nematode has identified the neurons that are necessary for the different locomotory behaviours underlying chemotaxis through the use of laser ablation, activity recording in immobilized animals and the study of mutants. However, we do not know the neural activity patterns in C. elegans that are sufficient to control its complex chemotactic behaviour. To understand how the activity in its interneurons coordinate different motor programs to lead the animal to food, here we used optogenetics and new optical tools to manipulate neural activity directly in freely moving animals to evoke chemotactic behaviour. By deducing the classes of activity patterns triggered during chemotaxis and exciting individual neurons with these patterns, we identified interneurons that control the essential locomotory programs for this behaviour. Notably, we discovered that controlling the dynamics of activity in just one interneuron pair (AIY) was sufficient to force the animal to locate, turn towards and track virtual light gradients. Two distinct activity patterns triggered in AIY as the animal moved through the gradient controlled reversals and gradual turns to drive chemotactic behaviour. Because AIY neurons are post-synaptic to most chemosensory and thermosensory neurons, it is probable that these activity patterns in AIY have an important role in controlling and coordinating different taxis behaviours of the animal.

Differential diffusivity of Nodal and Lefty underlies a reaction-diffusion patterning system.

Biological systems involving short-range activators and long-range inhibitors can generate complex patterns. Reaction-diffusion models postulate that differences in signaling range are caused by differential diffusivity of inhibitor and activator. Other models suggest that differential clearance underlies different signaling ranges. To test these models, we measured the biophysical properties of the Nodal/Lefty activator/inhibitor system during zebrafish embryogenesis. Analysis of Nodal and Lefty gradients revealed that Nodals have a shorter range than Lefty proteins. Pulse-labeling analysis indicated that Nodals and Leftys have similar clearance kinetics, whereas fluorescence recovery assays revealed that Leftys have a higher effective diffusion coefficient than Nodals. These results indicate that differential diffusivity is the major determinant of the differences in Nodal/Lefty range and provide biophysical support for reaction-diffusion models of activator/inhibitor-mediated patterning.

Pluripotency factors in embryonic stem cells regulate differentiation into germ layers.

Cell fate decisions are fundamental for development, but we do not know how transcriptional networks reorganize during the transition from a pluripotent to a differentiated cell state. Here, we asked how mouse embryonic stem cells (ESCs) leave the pluripotent state and choose between germ layer fates. By analyzing the dynamics of the transcriptional circuit that maintains pluripotency, we found that Oct4 and Sox2, proteins that maintain ESC identity, also orchestrate germ layer fate selection. Oct4 suppresses neural ectodermal differentiation and promotes mesendodermal differentiation; Sox2 inhibits mesendodermal differentiation and promotes neural ectodermal differentiation. Differentiation signals continuously and asymmetrically modulate Oct4 and Sox2 protein levels, altering their binding pattern in the genome, and leading to cell fate choice. The same factors that maintain pluripotency thus also integrate external signals and control lineage selection. Our study provides a framework for understanding how complex transcription factor networks control cell fate decisions in progenitor cells.

Measuring in vivo signaling kinetics in a mitogen-activated kinase pathway using dynamic input stimulation.

Determining the in vivo kinetics of a signaling pathway is a challenging task. We can measure a property we termed pathway bandwidth to put in vivo bounds on the kinetics of the mitogen-activated protein kinase (MAPk) signaling cascade in Saccharomyces cerevisiae that responds to hyperosmotic stress [the High Osmolarity Glycerol (HOG) pathway]. Our method requires stimulating cells with square waves of oscillatory hyperosmotic input (1 M sorbitol) over a range of frequencies and measuring the activity of the HOG pathway in response to this oscillatory input. The input frequency at which the pathway's steady-state activity drops precipitously because the stimulus is changing too rapidly for the pathway to respond faithfully is defined as the pathway bandwidth. In this chapter, we provide details of the techniques required to measure pathway bandwidth in the HOG pathway. These methods are generally useful and can be applied to signaling pathways in S. cerevisiae and other organisms whenever a rapid reporter of pathway activity is available.

Optical interrogation of neural circuits in Caenorhabditis elegans.

The nematode Caenorhabditis elegans has a compact nervous system with only 302 neurons. Whereas most of the synaptic connections between these neurons have been identified by electron microscopy serial reconstructions, functional connections have been inferred between only a few neurons through combinations of electrophysiology, cell ablation, in vivo calcium imaging and genetic analysis. To map functional connections between neurons, we combined in vivo optical stimulation with simultaneous calcium imaging. We analyzed the connections from the ASH sensory neurons and RIM interneurons to the command interneurons AVA and AVD. Stimulation of ASH or RIM neurons using channelrhodopsin-2 (ChR2) resulted in activation of AVA neurons, evoking an avoidance behavior. Our results demonstrate that we can excite specific neurons expressing ChR2 while simultaneously monitoring G-CaMP fluorescence in several other neurons, making it possible to rapidly decipher functional connections in C. elegans neural circuits.