Compressed sensing based approach identifies modular neural circuitry driving learned pathogen avoidance.

An animal's survival hinges on its ability to integrate past information to modify future behavior. The nematode adapts its behavior based on prior experiences with pathogen exposure, transitioning from attraction to avoidance of the pathogen. A systematic screen for the neural circuits that integrate the information of previous pathogen exposure to modify behavior has not been feasible because of the lack of tools for neuron type specific perturbations.

Neuron-level Prediction and Noise can Implement Flexible Reward-Seeking Behavior.

We show that neural networks can implement reward-seeking behavior using only local predictive updates and internal noise. These networks are capable of autonomous interaction with an environment and can switch between explore and exploit behavior, which we show is governed by attractor dynamics. Networks can adapt to changes in their architectures, environments, or motor interfaces without any external control signals.

Chemosensory detection of polyamine metabolites guides 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 is a microbivore that must distinguish nutritive microbes from pathogens. We characterized a neural circuit used by to rapidly discriminate between nutritive bacteria and pathogens.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Modularity of MAP kinases allows deformation of their signalling pathways.

Eukaryotic protein kinase pathways have both grown in number and changed their network architecture during evolution. We wondered if there are pivotal proteins in these pathways that have been repeatedly responsible for forming new connections through evolution, thus changing the topology of the network; and if so, whether the underlying properties of these proteins could be exploited to re-engineer and rewire these pathways. We addressed these questions in the context of the mitogen-activated protein kinase (MAPK) pathways.

In vivo measurement of signaling cascade dynamics.

Genetic and biochemical studies yield information about the component proteins and interactions involved in a cellular signaling pathway. However this parts inventory often does not immediately reveal the in vivo signal processing capabilities and function of the pathway. Signaling pathways are complex systems with dynamic behavior and a systems level approach is needed to understand the physiological roles they play within the cell.