Sharad Ramanathan

Genetic studies of human embryonic morphogenesis are constrained by ethical and practical challenges, restricting insights into developmental mechanisms and disorders. Human pluripotent stem cell (hPSC)–derived organoids provide a powerful alternative for the study of embryonic morphogenesis. However, screening for genetic drivers of morphogenesis in vitro has been infeasible due to organoid variability and the high costs of performing scaled tissue-wide single-gene perturbations. By overcoming both these limitations, we developed a platform that integrates reproducible organoid morphogenesis with uniform single-gene perturbations, enabling high-throughput arrayed CRISPR interference (CRISPRi) screening in hPSC-derived organoids. To demonstrate the power of this platform, we screened 77 transcription factors in an organoid model of anterior neurulation to identify ZIC2, SOX11, and ZNF521 as essential regulators of neural tube closure. We discovered that ZIC2 and SOX11 are required for closure, while ZNF521 prevents ectopic closure points. Single-cell transcriptomic analysis of perturbed organoids revealed co-regulated gene targets of ZIC2 and SOX11 and an opposing role for ZNF521, suggesting that these transcription factors jointly govern a gene regulatory program driving neural tube closure in the anterior forebrain region. Our single-gene perturbation platform enables high-throughput genetic screening of in vitro models of human embryonic morphogenesis.

An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode Caenorhabditis elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn-specific stalling but allow the animal to enter nonpathogenic Escherichia coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

Experiment RH281 contains wildtype neural tube organoid data (after 2 days of BMP4 treatment). Experiment RH282 and RH294 contain neural tube organoid data (After 4 days of BMP4 treatment) after perturbation with scramble guides or guides targeting neural transcription factors.

Experiment RH281 contains wildtype neural tube organoid data (after 2 days of BMP4 treatment). Experiment RH282 and RH294 contain neural tube organoid data (After 4 days of BMP4 treatment) after perturbation with scramble guides or guides targeting neural transcription factors.

Acknowledgements: We are grateful to the Institute Pasteur for hosting the meeting that led to this paper and Doug Sipp for contributions to the initial discussions and the kickoff meeting that informed the early development of this manuscript.

Genetic studies of human embryonic morphogenesis are constrained by ethical and practical challenges, restricting insights into developmental mechanisms and disorders. Human pluripotent stem cell (hPSC)–derived organoids provide a powerful alternative for the study of embryonic morphogenesis. However, screening for genetic drivers of morphogenesis in vitro has been infeasible due to organoid variability and the high costs of performing scaled tissue-wide single-gene perturbations. By overcoming both these limitations, we developed a platform that integrates reproducible organoid morphogenesis with uniform single-gene perturbations, enabling high-throughput arrayed CRISPR interference (CRISPRi) screening in hPSC-derived organoids. To demonstrate the power of this platform, we screened 77 transcription factors in an organoid model of anterior neurulation to identify ZIC2, SOX11, and ZNF521 as essential regulators of neural tube closure. We discovered that ZIC2 and SOX11 are required for closure, while ZNF521 prevents ectopic closure points. Single-cell transcriptomic analysis of perturbed organoids revealed co-regulated gene targets of ZIC2 and SOX11 and an opposing role for ZNF521, suggesting that these transcription factors jointly govern a gene regulatory program driving neural tube closure in the anterior forebrain region. Our single-gene perturbation platform enables high-throughput genetic screening of in vitro models of human embryonic morphogenesis.

Abstract Genetic studies of human embryonic morphogenesis are constrained by ethical and practical challenges, restricting insights into developmental mechanisms and disorders. Human pluripotent stem cell (hPSC)–derived organoids provide a powerful alternative for the study of embryonic morphogenesis. However, screening for genetic drivers of morphogenesis in vitro has been infeasible due to organoid variability and the high costs of performing scaled tissue-wide single-gene perturbations. By overcoming both these limitations, we developed a platform that integrates reproducible organoid morphogenesis with uniform single-gene perturbations, enabling high-throughput arrayed CRISPR interference (CRISPRi) screening in hPSC-derived organoids. To demonstrate the power of this platform, we screened 77 transcription factors in an organoid model of anterior neurulation to identify ZIC2, SOX11, and ZNF521 as essential regulators of neural tube closure. We discovered that ZIC2 and SOX11 are required for closure, while ZNF521 prevents ectopic closure points. Single-cell transcriptomic analysis of perturbed organoids revealed co-regulated gene targets of ZIC2 and SOX11 and an opposing role for ZNF521, suggesting that these transcription factors jointly govern a gene regulatory program driving neural tube closure in the anterior forebrain region. Our single-gene perturbation platform enables high-throughput genetic screening of in vitro models of human embryonic morphogenesis.

Abstract Genetic studies of human embryonic morphogenesis are constrained by ethical and practical challenges, restricting insights into developmental mechanisms and disorders. Human pluripotent stem cell (hPSC)–derived organoids provide a powerful alternative for the study of embryonic morphogenesis. However, screening for genetic drivers of morphogenesis in vitro has been infeasible due to organoid variability and the high costs of performing scaled tissue-wide single-gene perturbations. By overcoming both these limitations, we developed a platform that integrates reproducible organoid morphogenesis with uniform single-gene perturbations, enabling high-throughput arrayed CRISPR interference (CRISPRi) screening in hPSC-derived organoids. To demonstrate the power of this platform, we screened 77 transcription factors in an organoid model of anterior neurulation to identify ZIC2 , SOX11 , and ZNF521 as essential regulators of neural tube closure. We discovered that ZIC2 and SOX11 are required for closure, while ZNF521 prevents ectopic closure points. Single-cell transcriptomic analysis of perturbed organoids revealed co-regulated gene targets of ZIC2 and SOX11 and an opposing role for ZNF521 , suggesting that these transcription factors jointly govern a gene regulatory program driving neural tube closure in the anterior forebrain region. Our single-gene perturbation platform enables high-throughput genetic screening of in vitro models of human embryonic morphogenesis.

Surface energy and water balance calculations across crop surfaces improve comprehension of water balance and facilitates water usage which is cost-effective. With this idea, field trails were conducted at Tamil Nadu Agricultural University, Coimbatore during two cropping seasons i.e.,winter (Jan-March) and kharif (June-Sep), 2022 to study crop development, energy balance partitioning and evapotranspiration rate at various growth stage of baby corn under different sowing windows. Energy balance components were studied using Bowen Ratio Energy Balance method (BREB). Crop evapotranspiration was measured and simulated using AquaCrop model. Results clearly indicated that maximum energy balance components such as net radiation (Rn), Latent Heat Flux (LE), Sensible heat flux (H), Ground heat flux (G) were recorded at maturity stage, among crop growing cycle. Early sowing accumulated more amount of energy balance than mid and late sown crops during both seasons. Daily Kc values varied significantly from 0.05 to 1.01 and 0.01 to 0.96 for winter and kharif seasons, respectively. Good correlation was observed between calculated and simulated daily crop evapotranspiration (Etc). The total measured Etc was 486 and 624.4 mm for winter and kharif, respectively whereas AquaCrop simulated ETc of 438.8 mm and 500.4 mm. The digital agricultural technologies like crop simulation models would be useful to increase the accuracy of ET calculation in agricultural water management. This study examines the effective approaches used in estimating ET for baby corn water management which could be made to boost the precision of ET estimation and achieve precise water management.

Abstract An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode C. elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn specific stalling but allow the animal to enter nonpathogenic E. coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode C. elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn specific stalling but allow the animal to enter nonpathogenic E. coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode Caenorhabditis elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn-specific stalling but allow the animal to enter nonpathogenic Escherichia coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode C. elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn specific stalling but allow the animal to enter nonpathogenic E. coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode C. elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn specific stalling but allow the animal to enter nonpathogenic E. coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode C. elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn specific stalling but allow the animal to enter nonpathogenic E. coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

Abstract An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode C. elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn specific stalling but allow the animal to enter nonpathogenic E. coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

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. When networks have a choice between different tasks, they can form preferences that depend on patterns of noise and initialization, and we show that these preferences can be biased by network architectures or by changing learning rates. Our algorithm presents a flexible, biologically plausible way of interacting with environments without requiring an explicit environmental reward function, allowing for behavior that is both highly adaptable and autonomous. Code is available at https://github.com/ccli3896/PaN.

Abstract An animal’s survival hinges on its ability to integrate past information to modify future behavior. The nematode C. elegans 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. We overcame this challenge using methods based on compressed sensing to efficiently determine the roles of individual neuron types in learned avoidance behavior. Our screen revealed that distinct sets of neurons drive exit from lawns of pathogenic bacteria and prevent lawn re-entry. Using calcium imaging of freely behaving animals and optogenetic perturbations, we determined the neural dynamics that regulate one key behavioral transition after infection: stalled re-entry into bacterial lawns. We find that key neuron types govern pathogen lawn specific stalling but allow the animal to enter nonpathogenic E. coli lawns. Our study shows that learned pathogen avoidance requires coordinated transitions in discrete neural circuits and reveals the modular structure of this complex adaptive behavioral response to infection.

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.

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.

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.

Summary The human embryo breaks symmetry to form the anterior-posterior axis of the body. As the embryo elongates along this axis, progenitors in the tailbud 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 tailbud 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 tailbuds and branches. Our results identify mechanisms governing stable human axial elongation.

Summary 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.