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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2016

Direct coevolutionary couplings reflect biophysical residue interactions in proteins

Coevolution of residues in contact imposes strong statistical constraints on the sequence variability between homologous proteins. Direct-Coupling Analysis (DCA), a global statistical inference method, successfully models this variability across homologous protein families to infer structural information about proteins. For each residue pair, DCA infers 21x21 matrices describing the coevolutionary coupling for each pair of amino acids (or gaps). To achieve the residue-residue contact prediction, these matrices are mapped onto simple scalar parameters; the full information they contain gets lost. Here, we perform a detailed spectral analysis of the coupling matrices resulting from 70 protein families, to show that they contain quantitative information about the physico-chemical properties of amino-acid interactions. Results for protein families are corroborated by the analysis of synthetic data from lattice-protein models, which emphasizes the critical effect of sampling quality and regularization on the biochemical features of the statistical coupling matrices.

Biophysics↗

bioRxiv2016

Biophysical assay for tethered signaling reactions reveals tether-controlled activity for the phosphatase SHP-1

Tethered enzymatic reactions are ubiquitous in signalling networks but are poorly understood. Here, a novel mathematical analysis is established for tethered signalling reactions in surface plasmon resonance (SPR). Applying the method to the phosphatase SHP-1 interacting with a phosphorylated tether corresponding to an immune receptor cytoplasmic tail provides 5 biophysical/biochemical constants from a single SPR experiment: two binding rates, two catalytic rates, and a reach parameter. Tether binding increased the activity of SHP-1 by 900-fold through a binding-induced allosteric activation (20-fold) and a more significant increase in local sub-strate concentration (45-fold). The reach parameter indicates that this local substrate concentration is exquisitely sensitive to receptor clustering. We further show that truncation of the tether leads not only to a lower reach but also to lower binding and catalysis. The work establishes a new framework for studying tethered signalling processes and highlights the tether as a control parameter in clustered signalling.

Biophysics↗

bioRxiv2018

A biophysical model of molecular clusters: interplay of multivalency, membrane localization, steric hindrance, molecular flexibility and intracellular crowding

Dynamic molecular clusters are assembled through weak multivalent interactions and are platforms for cellular functions, especially receptor-mediated signaling. Clustering is also a prerequisite for liquid-liquid phase separation. But it is not well understood how molecular structure and cellular organization control clustering. Using coarse-grain kinetic Langevin dynamics, we performed computational experiments on a prototypical ternary system modeled after membrane-bound nephrin, the adaptor Nck1 and the actin nucleation promoting factor NWASP. Steady state cluster size distributions favored stoichiometries that optimized binding (stoichiometry matching), but still were quite broad. At high concentrations, the system can be driven beyond the saturation boundary such that cluster size is limited only by the number of available molecules. This behavior would be predictive of phase separation. Domains close to binding sites sterically inhibited clustering much less than terminal domains because the latter effectively restrict access to the cluster interior. Increased flexibility of interacting molecules diminished clustering by shielding binding sites within compact conformations. Membrane association of nephrin increased the cluster size distribution in a density-dependent manner. These properties provide insights into how molecular ensembles function to localize and amplify cell signaling.

biophysics↗

bioRxiv2016

Floral Radiometry: A Biophysical Basis to Characterize Landscapes.

This paper presents early results on studies of floral spectral reflectance of angiosperms and introduces floral radiometry as an emergent dimension of ecological research in India. Floral spectral reflectance of 121 angiosperm species was measured using hand-held spectroradiometer. The authors describe spectral reflectance of seven representative species within 350-800 nanometer region of the electromagnetic spectrum. Characteristic absorption and reflection of flowers, in ultraviolet and visible regions of the spectrum is reported. Near infrared reflectance was consistently high for all species studied. Flower color is unique to a species and importance of understanding flower color from pollinators perspective is highlighted.

ecology↗

bioRxiv2016

Relationships between chromosomal aberration breakpoints and chromosomal contacts: biophysical modeling study

Radiation-induced chromosomal exchange aberrations (CAs) are formed presumably at contacts of damaged chromosomal loci. For sparsely ionizing radiation, distribution of aberrations along the chromosome should depend on distribution of contacts, i.e. on 3D organization of the chromosome. The progress in experimental techniques for study of chromosomal contacts and for precise localization of aberration breakpoints allows to verify contacts-based mechanisms of CA formation experimentally. In the present work, the polymer model of mouse interphase chromosome 18 is developed. On this basis the experimental data on contacts and aberrations are jointly analyzed. We demonstrate high correlation between chromosomal contacts and aberrations breakpoint distributions. Possible factors and alternative mechanisms which could modify breakpoint distributions are discussed.

cancer biology↗

bioRxiv2017

Biophysics of object segmentation in a collision-detecting neuron

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. The most studied such collision-detecting neuron within the optic lobe of grasshoppers has long served as a model for understanding collision avoidance behaviors and their underlying neural computations. Here, we demonstrate that this neuron detects the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation as its pharmacological block abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Our results elucidate how active dendritic channels produce neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.

neuroscience↗

bioRxiv2018

The expa1-1 mutant reveals a new biophysical lateral root organogenesis checkpoint

In plants, post-embryonic formation of new organs helps shape the adult organism. This requires the tight regulation of when and where a new organ is formed, and a coordination of the underlying cell divisions. To build a root system, new lateral roots are continuously developing, and this process requires asymmetric cell division in adjacent pericycle cells. Characterization of an expansin a1 (expa1) mutant has revealed a novel checkpoint during lateral root formation. Specifically, a minimal pericycle width was found to be necessary and sufficient to trigger asymmetric pericycle cell divisions during auxin-driven lateral root formation. We conclude that a localized radial expansion of adjacent pericycle cells is required to position the asymmetric cell divisions and generate a core of small daughter cells, which is a prerequisite for lateral root organogenesis.\n\nSIGNFICANCE STATEMENTOrgan formation is an essential process in plants and animals, driven by cell division and cell identity establishment. Root branching, where lateral roots form along the primary root axis, increases the root system and aids capture of water and nutrients. We have discovered that tight control of cell width is necessary to co-ordinate asymmetric cell divisions in cells that give rise to a new lateral root organ. While biomechanical processes have been shown to play a role in plant organogenesis, including lateral root formation, our data give new mechanistic insights into the cell size checkpoint during lateral root initiation.

plant biology↗

bioRxiv2018

Determination of biophysical parameters for enhancement of human osteoblast proliferation by mechanical vibration in the infrasonic frequency range

Experimental methods for studying an enhancement of osteoblast proliferation in vitro provide tools for the research of biochemical processes involved in bone turnover in vivo. Some of the current methods used for this purpose are based on the ability of the osteoblasts to enhance proliferation by mechanical stimulation. We describe an experimental approach of biomechanical stimulation of cultured human osteoblast-like cells by vibration. This method is based on the specially designed controlled vibration setup that consists of an electric actuator, with horizontally mounted well plate containing cell cultures. Previously this method found to be effective to enhance cell proliferation, but the exact mechanical parameters of effective vibration were elusive. The current low friction system for mechanical stimulation of osteoblast-like cells in vitro provides recording of narrow range mechanical parameters in the infrasonic spectrum.\n\nWe exposed human osteoblast-like cells in explant monolayer culture to mechanical vibration in the 10-70Hz range of frequencies and found that 50-70 Hz of vibration frequency is optimal for inducing osteoblast proliferation that was deduced from interrelation between unchanged cell number in culture samples with significant decrease in cell death rate (decreased LDH activity in culture media, p<.05) and with parallel decrease of their maturation level (p<.01).\n\nIn this report we determined the optimal mechanical parameters and excitation protocol for induction of osteoblast proliferation in vitro by using a tunable and versatile mechanical platform, which can be used in the research of cell mechanotransduction.

cell biology↗

bioRxiv2018

Analysis of proteins in computational models of synaptic plasticity

The desire to explain how synaptic plasticity arises from interactions between ions, proteins and other signalling molecules has propelled the development of biophysical models of molecular pathways in hippocampal, striatal and cerebellar synapses. The experimental data underpinning such models is typically obtained from low-throughput, hypothesis-driven experiments. We used high-throughput proteomic data and bioinformatics datasets to assess the coverage of biophysical models.\n\nTo determine which molecules have been modelled, we surveyed biophysical models of synaptic plasticity, identifying which proteins are involved in each model. We were able to map 4.2% of previously reported synaptic proteins to entities in biophysical models. Linking the modelled protein list to Gene Ontology terms shows that modelled proteins are focused on functions such as calmodulin binding, cellular responses to glucagon stimulus, G-alpha signalling and DARPP-32 events.\n\nWe cross-linked the set of modelled proteins with sets of genes associated with common neurological diseases. We find some examples of disease-associated molecules that are well represented in models, such as voltage-dependent calcium channel family (CACNA1C), dopamine D1 receptor, and glutamate ionotropic NMDA type 2A and 2B receptors. Many other disease-associated genes have not been included in models of synaptic plasticity, for example catechol-O-methyltransferase (COMT) and MAO A. By incorporating pathway enrichment results, we identify LAMTOR, a gene uniquely associated with Schizophrenia, which is closely linked to the MAPK pathway found in some models.\n\nOur analysis provides a map of how molecular pathways underpinning neurological diseases relate to synaptic biophysical models that can in turn be used to explore how these molecular events might bridge scales into cellular processes and beyond. The map illustrates disease areas where biophysical models have good coverage as well as domain gaps that require significant further research.\n\nAuthor summaryThe 100 billion neurons in the human brain are connected by a billion trillion structures called synapses. Each synapse contains hundreds of different proteins. Some proteins sense the activity of the neurons connecting the synapse. Depending on what they sense, the proteins in the synapse are rearranged and new proteins are synthesised. This changes how strongly the synapse influences its target neuron, and underlies learning and memory. Scientists build computational models to reason about the complex interactions between proteins. Here we list the proteins that have been included in computational models to date. For good reasons, models do not always specify proteins precisely, so to make the list we had to translate the names used for proteins in models to gene names, which are used to identify proteins. Our translation could be used to label computational models in the future. We found that the list of modelled proteins contains only 4.2% of proteins associated with synapses, suggesting more proteins should be added to models. We used lists of genes associated with neurological diseases to suggest proteins to include in future models.

neuroscience↗

bioRxiv2018

A national ‘safe and just operating space’ for all in India: Past, Present and Futurea

With 1.3 billion populaces on the commencement of the 21st century, India is currently impending towards upholding a subtle equilibrium between persisting social development and well-being without depleting existing biophysical resources at the national level or surpassing global average per capita obtainability. In this paper, we have structured a top-down per capita framework to explore national safe and just operating space (NSJOS) to apprehend not only past fluctuations that bring about the present conditions but also the plausible future consequences, with India as a case study. Coalescing 27 indicators, all pertaining to Sustainable Development Goals (except - SDG 17), accompanied by their corresponding environmental boundaries or preferred social thresholds, present study probes into both biophysical (for environmental stress) and social development (for social deficit) attributes of India. This analysis shows India has already crossed three of seven dimensions of biophysical boundaries (freshwater, nitrogen and phosphorus use). Also, at the existing rate, India is going to cross the remainder of the boundaries within 2045-2050 (climate change, arable land use, ecological and material footprint). Of 20 indicators used for social development, only five have already or will meet corresponding desired thresholds of United Nations Sustainable Development Goals 2015. Using tendencies of past variations, the results indicate that if lowest per capita consumption can be attained and uphold, even with projected population growth, total consumption of four biophysical resources (climate change, nitrogen use, ecological and material footprint) can be slashed from todays level in 2050. Adaptations in national policy are indispensable if India wants to accomplish sufficiency in biophysical resources whilst bestowing social equity in access and exploitation of those resources towards the continuance of social developments in forthcoming times.

ecology↗

bioRxiv2018

A comparative study of ‘safe and just operating space’ for the south and south-east Asian countries

The world is presently maintaining a delicate balance of continuing well-being and social development for the people through consumption of biophysical resources of nature without topping global average per capita availability. In this paper, we have framed a per capita top-down framework to survey national safe and just operating space (NSJOS) for the countries of south and southeast Asia to understand past variations and as a consequence, the present scenario. Amalgamating 27 indicators, all regarding Sustainable Development Goals (except - SDG 17), in consort with their respective environmental boundaries or desirable social development thresholds, this study explores into both biophysical (for ecological stress) and social development (for social deprivation) attributes of 19 countries of south and southeast Asia. This analysis shows, only 2 have remained either unchanged (political voice) or declining (social equity) among the 12 dimensions of social development in countries of this region. The remaining 10 dimensions of social development showing positive progress and will meet corresponding desired thresholds of United Nations Sustainable Development Goals 2015. All the 7 indicators showing tendencies of overconsumption of biophysical resources, that might be leading to exceeding per capita global average planetary boundaries in forthcoming future. However, ecological boundaries have remained protected to a decent degree so far for these countries. The challenge would be to maintain and increase the pace of social development and bringing it in equal strata of a global standard in future without depleting drivers of these, i.e. biophysical resources. National policy adaptations are crucial if these countries of south and southeast Asia desire to bring about adequacy in biophysical resources reserve whilst granting social equity in access and exploitation of these resources for the people towards the persistant social development in impending decades.

ecology↗

bioRxiv2016

NODDI-DTI: extracting neurite orientation and dispersion parameters from a diffusion tensor

NODDI-DTI is a simplification of the NODDI model that, when its underlying assumptions are met, allows extraction of biophysical parameters from standard single-shell DTI data, permitting biophysical analysis of DTI datasets.\n\nIn contrast to the NODDI signal model, the NODDI-DTI signal model contains no CSF compartment, restricting its application to voxels with very low CSF partial-volume contamination. This simplification allowed derivation of simple analytical relations between parameters representing axon density, v and dispersion,{tau} , and DTI invariants (MD and FA) through moment expansion of the NODDI-DTI signal model. These relations formally allow extraction of biophysical parameters from DTI data. It should be emphasised that the NODDI-DTI model inherits the strong assumptions of the NODDI model, and so is nominally restricted to analysis of healthy brains.\n\nNODDI-DTI parameter estimates were computed by applying the proposed analytical relations to DTI parameters extracted from the first shell of data, and compared to parameters extracted by fitting the NODDI-DTI model to (i) both shells (recommended) and (ii) the first shell (as for DTI) of data in the white matter of three different in vivo diffusion datasets. NODDI-DTI parameters estimated from DTI and NODDI-DTI parameters estimated by fitting the model to the first shell of data gave similar errors compared to two-shell NODDI-DTI estimates. The NODDI-DTI method gave unphysical parameter estimates in a small percentage of voxels, reflecting voxelwise DTI estimation error or NODDI-DTI model invalidity. In the course of evaluating the NODDI-DTI model it was found that diffusional kurtosis strongly biased DTI-based MD values, and so a novel heuristic correction requiring only DTI data was derived and used to account for this bias.\n\nOur results demonstrate that NODDI-DTI is a promising model and technique to interpret restricted datasets acquired for DTI analysis with greater biophysical specificity, though its limitations must be borne in mind.

Biophysics↗

bioRxiv2015

A literature-based meta-analysis of brain-wide electrophysiological diversity

For decades, neurophysiologists have characterized the biophysical properties of a rich diversity of neuron types. However, identifying common features and computational roles shared across neuron types is made more difficult by inconsistent conventions for collecting and reporting biophysical data. Here, we leverage NeuroElectro, a literature-based database of electrophysiological properties (www.neuroelectro.org), to better understand neuronal diversity - both within and across neuron types - and the confounding influences of methodological variability. We show that experimental conditions (e.g., electrode types, recording temperatures, or animal age) can explain a substantial degree of the literature-reported biophysical variability observed within a neuron type. Critically, accounting for experimental metadata enables massive cross-study data normalization and reveals that electrophysiological data are far more reproducible across labs than previously appreciated. Using this normalized dataset, we find that neuron types throughout the brain cluster by biophysical properties into 6-9 super-classes. These classes include intuitive clusters, such as fast-spiking basket cells, as well as previously unrecognized clusters, including a novel class of cortical and olfactory bulb interneurons that exhibit persistent activity at theta-band frequencies.

Neuroscience↗

bioRxiv2017

Reactive astrocytes - comprehending when neurons play 4’33”

Homeostatic regulation is a powerful tool utilized by virtually all biological systems, brain included. Broadly speaking, each homeostatic process embodies two components: the sensing component, whereby a deviation is detected and quantified, and the effecting component that executes the homeostatic adjustment with the goal of alleviating the deviation. In the central nervous system, homeostatic plasticity has been suggested to play an important role in shaping the dynamics of single neurons and neuronal networks. However, existing \"biophysical\" models of homeostatic plasticity are exceedingly simplistic. These models usually describe the sensor component in terms of simple averaging over neuronal activity and offer no explanation of the relevant biochemical pathways. Here, we attempt to fill this gap in our understanding of homeostatic plasticity by proposing a biophysical framework to explain detection of prolonged synaptic inactivity that may occur in some scenarios of brain injury. We propose that sensing of, and response to, synaptic inactivity involves detection of the extracellular glutamate level and occurs via the activation of metabotropic glutamate receptors (mGluRs), while the inactivity-induced synthesis of one of the homeostatic plasticity effectors, tumor necrosis factor alpha (TNF), serves as an effecting component of the system. This model can help to explain the experimental observations linking prolonged neuronal inactivity to TNF signaling. Importantly, the proposed signaling scheme is not limited to mGluRs and astrocytes, but rather is potentially applicable to any cells expressing receptors that activate the relevant G protein units. The proposed signaling scheme is likely to be useful for developing pharmacological interventions targeting homeostatic plasticity pathways.\n\nAuthor summaryHomeostatic regulation refers to the self-regulation ability of a system aimed at remaining in the same (or nearly the same) state. Homeostatic plasticity, a form of homeostatic regulation that arises in the context of neural dynamics, has been shown to shape neuronal and network dynamics by attempting to maintain physiological levels of neuronal activity in brain networks. Thus, it changes the excitation-inhibition balance in a network when sufficiently large and long-lasting deviations from physiological levels of activity are detected. However, the biophysical mechanisms of homeostatic plasticity and in particular those related to the ability to sense neuronal inactivity, remain elusive. We propose a feasible biophysical model of a homeostatic sensor, in which the sensing of inactivity depends on the presence and activation of G-protein-coupled receptors with different activation thresholds. In this model, the activation of the higher-threshold receptor suppresses the detection of inactivity, while the activation of the lower-threshold receptor promotes the detection of inactivity. The proposed model helps to explain a growing body of experimental data relating synaptic inactivity to production of homeostatic plasticity effectors such as tumor necrosis factor alpha. Although we consider a specific case study of metabotropic glutamate receptors on astrocytes, the model conclusions are likely to be applicable to any cells expressing receptors that activate the relevant G protein units.

neuroscience↗

bioRxiv2018

Analysing progress of SDG 6 in India: Past, Present, and Future

Human endeavors to meet social and economic water needs at national scale might cause negative environmental manifestations and water stress from local to global scale. So, appropriation of Sustainable Development Goals requires a comprehensive monitoring and knowledge base of the water resource availability, utilization and access. Hence, scientific research progression has a significant role to facilitate the implementation of sustainable development goals through assessment and policy implementation from global to local scales. India holds a key position among developing economies with a complex interconnected web of a fast-growing population, coupled with biophysical stress, social deprivation and economic inequality related to water and sanitation. This study addresses some of these challenges related to monitoring and implementation of the targets of the United Nations Sustainable Development Goal 6 in India. Acknowledging the contribution of society and economy in sustainability paradigm, here we have chosen 28 indicators (clustered into eleven dimensions) under two major groups, concerning biophysical and social development aspects of water and sanitation. We have shown declining level of per capita biophysical water resource and slow to rapidly developing social indicators related to Sustainable Development Goal 6 in India. From past trends, we have calculated probable scenario of biophysical consumption of India up to 2050, which shows at least 1.3 times increase. This cumulative assessment framework contributes a tool to prioritize water resource appropriation, management response and policy implementations to national level sustainability of water and sanitation in India. We also advocate the necessity of restraining threats both at source and consumption process levels in order to ensure national water security for both human and biodiversity, keeping in mind the societal and economic development scenario.

ecology↗

bioRxiv2017

Physiological Preparation Of Hair Cells From The Sacculus Of The American Bullfrog (Rana catesbeiana)

SHORT ABSTRACTThe American bullfrogs sacculus permits direct examination of hair-cell physiology. Here we describe the dissection and preparation of the bullfrogs sacculus for biophysical studies. We show representative experiments from these hair cells, including the calculation of a bundles force-displacement relation and measurement of its spontaneous motion.\n\nLONG ABSTRACTThe study of hearing and balance rests upon insights drawn from biophysical studies of model systems. One such model, the sacculus of the American bullfrog, has become a mainstay of auditory and vestibular research. Studies of this organ have revealed how sensory cells--hair cells--can actively detect signals from the environment. Because of these studies, we now better understand the mechanical gating and localization of a hair cells transduction channels, calciums role in mechanical adaptation, and the identity of hair-cell currents. This highly accessible organ continues to provide insight into the workings of hair cells.\n\nHere we describe the preparation of the bullfrogs sacculus for biophysical studies on its hair cells. We include the complete dissection procedure and provide specific protocols for the preparation of the sacculus in specific contexts. We additionally include representative results using this preparation, including the calculation of a hair bundles force-displacement relation and measurement of a bundles spontaneous motion.

biophysics↗

bioRxiv2015

Synergy of AMPA and NMDA receptor currents in dopaminergic neurons: a modeling study

Dopaminergic (DA) neurons display two modes of firing: low-frequency tonic and high-frequency bursts. The high frequency firing within the bursts is attributed to NMDA, but not AMPA receptor activation. In our models of the DA neuron, both biophysical and abstract, the NMDA receptor current can significantly increase their firing frequency, whereas the AMPA receptor current is not able to evoke high-frequency activity and usually suppresses firing. However, both currents are produced by glutamate receptors and, consequently, are often co-activated. Here we consider combined influence of AMPA and NMDA synaptic input in the models of the DA neuron. Different types of neuronal activity (resting state, low frequency, or high frequency firing) are observed depending on the conductance of the AMPAR and NMDAR currents. In two models, biophysical and reduced, we show that the firing frequency increases more effectively if both receptors are co-activated for certain parameter values. In particular, in the more quantitative biophysical model, the maximal frequency is 40% greater than that with NMDAR alone. The dynamical mechanism of such frequency growth is explained in the framework of phase space evolution using the reduced model. In short, both the AMPAR and NMDAR currents flatten the voltage nullcline, providing the frequency increase, whereas only NMDA prevents complete unfolding of the nullcline, providing robust firing. Thus, we confirm a major role of the NMDAR in generating high-frequency firing and conclude that AMPAR activation further significantly increases the frequency.

Neuroscience↗

bioRxiv2017

Engineering Human CNS Morphogenesis: Controlled Induction of Singular Neural Rosette Emergence

Human pluripotent stem cell (hPSC)-derived neural organoids have revolutionized in vitro modelling of human neurological disorders. Cell-intrinsic morphogenesis processes displayed within these tissues could serve as the basis for ex vivo manufacture of brain and spinal cord tissues with biomimetic anatomy and physiology. However, we must first understand how to control their emergent properties starting at the genesis of neural organoid formation, i.e. emergence of polarized neuroepithelium. In vivo, all CNS tissues develop from a singular neuroepithelial tube. Yet, current protocols yield organoids with multiple neuroepithelial rings, a.k.a. neural rosettes, each acting as independent centers of morphogenesis and thereby impeding coordinate tissue development. We discovered that the morphology of hPSC-derived neural tissues is a critical biophysical parameter for inducing singular neural rosette emergence. Tissue morphology screens conducted using micropatterned array substrates and an automated image analysis determined that circular morphologies of 200-250 and 150m diameter are optimal for inducing singular neural rosette emergence within 80-85% forebrain and 73.5% spinal tissues, respectively. The discrepancy in optimal circular morphology for Pax6+/N-cadherin+ neuroepithelial forebrain versus spinal tissues was due to previously unknown differences in ROCK-mediated cell contractility. The singular neuroepithelium induced within geometrically confined tissues persisted as the tissues morphed from a 2-D monolayer to multilayered 3-D hemispherical aggregate. Upon confinement release using clickable micropatterned substrates, the tissue displayed radial outgrowth with maintenance of a singular neuroepithelium and peripheral neuronal differentiation. Thus, we have quantitatively defined a pertinent biophysical parameter for effectively inducing a singular neuroepithelium emergence within morphing hPSC-derived neural tissues.\n\nSignificance StatementHuman pluripotent stem cell (hPSC)-derived neural organoids display emergent properties that, if harnessed, could serve as the basis for ex vivo manufacture of brain and spinal cord tissues with biomimetic macroscale anatomy and physiology. Their chaotic terminal structure arises from uncontrolled morphogenesis at their genesis, resulting in spontaneous induction of multiple neuroepithelial morphogenesis centers,a.k.a. neural rosettes. Here, we determined that neural tissue morphology is a pertinent biophysical parameter for controlling subsequent morphogenesis, and identified discrete circular tissue morphologies as optimal and effective at inducing singular neural rosette emergence within forebrain and spinal neural tissues. Thus, we developed an approach to reproducibly control the initial stage of hPSC-derived neural tissue morphogenesis enabling their manufacture with a biomimetic nascent CNS anatomy.

bioengineering↗