Photosynthesis and other factors affecting the establishment and maintenance of cnidarian-dinoflagellate symbiosis

Coral growth depends on the partnership between the animal hosts and their intracellular, photosynthetic dinoflagellate symbionts. In this study, we used the sea anemone Aiptasia, a laboratory model for coral biology, to investigate the poorly understood mechanisms that mediate symbiosis establishment and maintenance. We found that initial colonization of both adult polyps and larvae by a compatible algal strain was more effective when the algae were able to photosynthesize and that the long-term maintenance of the symbiosis also depended on photosynthesis. In the dark, algal cells were taken up into host gastrodermal cells and not rapidly expelled, but they seemed unable to reproduce and thus were gradually lost. When we used confocal microscopy to examine the interaction of larvae with two algal strains that cannot establish stable symbioses with Aiptasia, it appeared that both pre- and post-phagocytosis mechanisms were involved. With one strain, algae entered the gastric cavity but appeared to be completely excluded from the gastrodermal cells. With the other strain, small numbers of algae entered the gastrodermal cells but appeared unable to proliferate there and were slowly lost upon further incubation. We also asked if the exclusion of either incompatible strain could result simply from their cells' being too large for the host cells to accommodate. However, the size distributions of the compatible and incompatible strains overlapped extensively. Moreover, examination of macerates confirmed earlier reports that individual gastrodermal cells could expand to accommodate multiple algal cells. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

Structural insights into the unexpected agonism of tetracyclic antidepressants at serotonin receptors 5-HT1eR and 5-HT1FR

Serotonin [5-hydroxytryptamine (5-HT)] acts via 13 different receptors in humans. Of these receptor subtypes, all but 5-HT1eR have confirmed roles in native tissue and are validated drug targets. Despite 5-HT1eR's therapeutic potential and plausible druggability, the mechanisms of its activation remain elusive. To illuminate 5-HT1eR's pharmacology in relation to the highly homologous 5-HT1FR, we screened a library of aminergic receptor ligands at both receptors and observe 5-HT1eR/5-HT1FR agonism by multicyclic drugs described as pan-antagonists at 5-HT receptors. Potent agonism by tetracyclic antidepressants mianserin, setiptiline, and mirtazapine suggests a mechanism for their clinically observed antimigraine properties. Using cryo-EM and mutagenesis studies, we uncover and characterize unique agonist-like binding poses of mianserin and setiptiline at 5-HT1eR distinct from similar drug scaffolds in inactive-state 5-HTR structures. Together with computational studies, our data suggest that these binding poses alongside receptor-specific allosteric coupling in 5-HT1eR and 5-HT1FR contribute to the agonist activity of these antidepressants.

Dispersive nonreciprocity between a qubit and a cavity

The dispersive interaction between a qubit and a cavity is ubiquitous in circuit and cavity quantum electrodynamics. It describes the frequency shift of one quantum mode in response to excitations in the other and, in closed systems, is necessarily bidirectional, i.e., reciprocal. Here, we present an experimental study of a nonreciprocal dispersive-type interaction between a transmon qubit and a superconducting cavity, arising from a common coupling to dissipative intermediary modes with broken time reversal symmetry. We characterize the qubit-cavity dynamics, including asymmetric frequency pulls and photon shot noise dephasing, under varying degrees of nonreciprocity by tuning the magnetic field bias of a ferrite component in situ. We introduce a general master equation model for nonreciprocal interactions in the dispersive regime, providing a compact description of the observed qubit-cavity dynamics agnostic to the intermediary system. Our result provides an example of quantum nonreciprocal phenomena beyond the typical paradigms of non-Hermitian Hamiltonians and cascaded systems.

Bounds on the Ultrasensitivity of Biochemical Reaction Cascades

The ultrasensitivity of a dose response function can be quantifiably defined using the generalized Hill coefficient of the function. We examined an upper bound for the Hill coefficient of the composition of two functions, namely the product of their individual Hill coefficients. We proved that this upper bound holds for compositions of Hill functions, and that there are instances of counterexamples that exist for more general sigmoidal functions. Additionally, we tested computationally other types of sigmoidal functions, such as the logistic and inverse trigonometric functions, and we provided computational evidence that in these cases the inequality also holds. We show that in large generality there is a limit to how ultrasensitive the composition of two functions can be, which has applications to understanding signaling cascades in biochemical reactions.

Isometric Immersions and the Waving of Flags

In this article we propose a novel geometric model to study the motion of a physical flag. In our approach, a flag is viewed as an isometric immersion from the square with values in R 3 satisfying certain boundary conditions at the flag pole. Under additional regularity constraints we show that the space of all such flags carries the structure of an infinite dimensional manifold and can be viewed as a submanifold of the space of all immersions. In the second part of the article we equip the space of isometric immersions with its natural kinetic energy and derive the corresponding equations of motion. This approach can be viewed in a spirit similar to Arnold's geometric picture for the motion of an incompressible fluid.

A geometrical model of cell fate specification in the mouse blastocyst

The lineage decision that generates the epiblast and primitive endoderm from the inner cell mass (ICM) is a paradigm for cell fate specification. Recent mathematics has formalized Waddington's landscape metaphor and proven that lineage decisions in detailed gene network models must conform to a small list of low-dimensional stereotypic changes called bifurcations. The most plausible bifurcation for the ICM is the so-called heteroclinic flip that we define and elaborate here. Our re-analysis of recent data suggests that there is sufficient cell movement in the ICM so the FGF signal, which drives the lineage decision, can be treated as spatially uniform. We thus extend the bifurcation model for a single cell to the entire ICM by means of a self-consistently defined time-dependent FGF signal. This model is consistent with available data and we propose additional dynamic experiments to test it further. This demonstrates that simplified, quantitative and intuitively transparent descriptions are possible when attention is shifted from specific genes to lineages. The flip bifurcation is a very plausible model for any situation where the embryo needs control over the relative proportions of two fates by a morphogen feedback.

Single-cell RNA-seq of the rare virosphere reveals the native hosts of giant viruses in the marine environment

Giant viruses (phylum Nucleocytoviricota) are globally distributed in aquatic ecosystems. They play fundamental roles as evolutionary drivers of eukaryotic plankton and regulators of global biogeochemical cycles. However, we lack knowledge about their native hosts, hindering our understanding of their life cycle and ecological importance. In the present study, we applied a single-cell RNA sequencing (scRNA-seq) approach to samples collected during an induced algal bloom, which enabled pairing active giant viruses with their native protist hosts. We detected hundreds of single cells from multiple host lineages infected by diverse giant viruses. These host cells included members of the algal groups Chrysophycae and Prymnesiophycae, as well as heterotrophic flagellates in the class Katablepharidaceae. Katablepharids were infected with a rare Imitervirales-07 giant virus lineage expressing a large repertoire of cell-fate regulation genes. Analysis of the temporal dynamics of these host-virus interactions revealed an important role for the Imitervirales-07 in controlling the population size of the host Katablepharid population. Our results demonstrate that scRNA-seq can be used to identify previously undescribed host-virus interactions and study their ecological importance and impact.

An abundant bacterial phylum with nitrite-oxidizing potential in oligotrophic marine sediments

Nitrite-oxidizing bacteria (NOB) are important nitrifiers whose activity regulates the availability of nitrite and dictates the magnitude of nitrogen loss in ecosystems. In oxic marine sediments, ammonia-oxidizing archaea (AOA) and NOB together catalyze the oxidation of ammonium to nitrate, but the abundance ratios of AOA to canonical NOB in some cores are significantly higher than the theoretical ratio range predicted from physiological traits of AOA and NOB characterized under realistic ocean conditions, indicating that some NOBs are yet to be discovered. Here we report a bacterial phylum Candidatus Nitrosediminicolota, members of which are more abundant than canonical NOBs and are widespread across global oligotrophic sediments. Ca. Nitrosediminicolota members have the functional potential to oxidize nitrite, in addition to other accessory functions such as urea hydrolysis and thiosulfate reduction. While one recovered species (Ca. Nitrosediminicola aerophilus) is generally confined within the oxic zone, another (Ca. Nitrosediminicola anaerotolerans) additionally appears in anoxic sediments. Counting Ca. Nitrosediminicolota as a nitrite-oxidizer helps to resolve the apparent abundance imbalance between AOA and NOB in oxic marine sediments, and thus its activity may exert controls on the nitrite budget.

Fibration symmetries and cluster synchronization in the Caenorhabditis elegans connectome

Capturing how the Caenorhabditis elegans connectome structure gives rise to its neuron functionality remains unclear. It is through fiber symmetries found in its neuronal connectivity that synchronization of a group of neurons can be determined. To understand these we investigate graph symmetries and search for such in the symmetrized versions of the forward and backward locomotive sub-networks of the Caenorhabditi elegans worm neuron network. The use of ordinarily differential equations simulations admissible to these graphs are used to validate the predictions of these fiber symmetries and are compared to the more restrictive orbit symmetries. Additionally fibration symmetries are used to decompose these graphs into their fundamental building blocks which reveal units formed by nested loops or multilayered fibers. It is found that fiber symmetries of the connectome can accurately predict neuronal synchronization even under not idealized connectivity as long as the dynamics are within stable regimes of simulations.

Quantum simulation of the bosonic Kitaev chain

Superconducting quantum circuits are a natural platform for quantum simulations of a wide variety of important lattice models describing topological phenomena, spanning condensed matter and high-energy physics. One such model is the bosonic analog of the well-known fermionic Kitaev chain, a 1D tight-binding model with both nearest-neighbor hopping and pairing terms. Despite being fully Hermitian, the bosonic Kitaev chain exhibits a number of striking features associated with non-Hermitian systems, including chiral transport and a dramatic sensitivity to boundary conditions known as the non-Hermitian skin effect. Here, using a multimode superconducting parametric cavity, we implement the bosonic Kitaev chain in synthetic dimensions. The lattice sites are mapped to frequency modes of the cavity, and the in situ tunable complex hopping and pairing terms are created by parametric pumping at the mode-difference and mode-sum frequencies, respectively. We experimentally demonstrate important precursors of nontrivial topology and the non-Hermitian skin effect in the bosonic Kitaev chain, including chiral transport, quadrature wavefunction localization, and sensitivity to boundary conditions. Our experiment is an important first step towards exploring genuine many-body non-Hermitian quantum dynamics.

PMF-GRN: a variational inference approach to single-cell gene regulatory network inference using probabilistic matrix factorization

Inferring gene regulatory networks (GRNs) from single-cell data is challenging due to heuristic limitations. Existing methods also lack estimates of uncertainty. Here we present Probabilistic Matrix Factorization for Gene Regulatory Network Inference (PMF-GRN). Using single-cell expression data, PMF-GRN infers latent factors capturing transcription factor activity and regulatory relationships. Using variational inference allows hyperparameter search for principled model selection and direct comparison to other generative models. We extensively test and benchmark our method using real single-cell datasets and synthetic data. We show that PMF-GRN infers GRNs more accurately than current state-of-the-art single-cell GRN inference methods, offering well-calibrated uncertainty estimates.

Peptide Mimics of the Cysteine-Rich Regions of HapX and SreA Bind a [2Fe-2S] Cluster In Vitro

HapX and SreA are transcription factors that regulate the response of the fungus Aspergillus fumigatus to the availability of iron. During iron starvation, HapX represses genes involved in iron consuming pathways and upon a shift to iron excess, HapX activates these same genes. SreA blocks the expression of genes needed for iron uptake during periods of iron availability. Both proteins possess cysteine-rich regions (CRR) that are hypothesized to be necessary for the sensing of iron levels. However, the contribution of each of these domains to the function of the protein has remained unclear. Here, the ability of peptide analogs of each CRR is determined to bind an iron-sulfur cluster in vitro. UV-vis and resonance Raman (RR) spectroscopies reveal that each CRR is capable of coordinating a [2Fe-2S] cluster with comparable affinities. The iron-sulfur cluster coordinated to the CRR-B domain of HapX displays particularly high stability. The data are consistent with HapX and SreA mediating responses to cellular iron levels through the direct coordination of [2Fe-2S] clusters. The high stability of the CRR-B peptide may also find use as a starting point for the development of new green catalysts.

High-Fidelity RNA Copying via 2',3'-Cyclic Phosphate Ligation

Templated ligation offers an efficient approach to replicate long strands in an RNA world. The 2',3'-cyclic phosphate (>P) is a prebiotically available activation that also forms during RNA hydrolysis. Using gel electrophoresis and high-performance liquid chromatography, we found that the templated ligation of RNA with >P proceeds in simple low-salt aqueous solutions with 1 mM MgCl2 under alkaline pH ranging from 9 to 11 and temperatures from -20 to 25 °C. No additional catalysts were required. In contrast to previous reports, we found an increase in the number of canonical linkages to 50%. The reaction proceeds in a sequence-specific manner, with an experimentally determined ligation fidelity of 82% at the 3' end and 91% at the 5' end of the ligation site. With splinted oligomers, five ligations created a 96-mer strand, demonstrating a pathway for the ribozyme assembly. Due to the low salt requirements, the ligation conditions will be compatible with strand separation. Templated ligation mediated by 2',3'-cyclic phosphate in alkaline conditions therefore offers a performant replication and elongation reaction for RNA on early Earth.

Effects of parental age and polymer composition on short tandem repeat de novo mutation rates

Short tandem repeats (STRs) are hotspots of genomic variability in the human germline because of their high mutation rates, which have long been attributed largely to polymerase slippage during DNA replication. This model suggests that STR mutation rates should scale linearly with a father's age, as progenitor cells continually divide after puberty. In contrast, it suggests that STR mutation rates should not scale with a mother's age at her child's conception, since oocytes spend a mother's reproductive years arrested in meiosis II and undergo a fixed number of cell divisions that are independent of the age at ovulation. Yet, mirroring recent findings, we find that STR mutation rates covary with paternal and maternal age, implying that some STR mutations are caused by DNA damage in quiescent cells rather than polymerase slippage in replicating progenitor cells. These results echo the recent finding that DNA damage in oocytes is a significant source of de novo single nucleotide variants and corroborate evidence of STR expansion in postmitotic cells. However, we find that the maternal age effect is not confined to known hotspots of oocyte mutagenesis, nor are postzygotic mutations likely to contribute significantly. STR nucleotide composition demonstrates divergent effects on de novo mutation (DNM) rates between sexes. Unlike the paternal lineage, maternally derived DNMs at A/T STRs display a significantly greater association with maternal age than DNMs at G/C-containing STRs. These observations may suggest the mechanism and developmental timing of certain STR mutations and contradict prior attribution of replication slippage as the primary mechanism of STR mutagenesis.

Microbial Diversity and Open Questions about the Deep Tree of Life

In this perspective, we explore the transformative impact and inherent limitations of metagenomics and single-cell genomics on our understanding of microbial diversity and their integration into the Tree of Life. We delve into the key challenges associated with incorporating new microbial lineages into the Tree of Life through advanced phylogenomic approaches. Additionally, we shed light on enduring debates surrounding various aspects of the microbial Tree of Life, focusing on recent advances in some of its deepest nodes, such as the roots of bacteria, archaea, and eukaryotes. We also bring forth current limitations in genome recovery and phylogenomic methodology, as well as new avenues of research to uncover additional key microbial lineages and resolve the shape of the Tree of Life.

Passive frequency comb generation at radiofrequency for ranging applications

Optical frequency combs, featuring evenly spaced spectral lines, have been extensively studied and applied to metrology, signal processing, and sensing. Recently, frequency comb generation has been also extended to MHz frequencies by harnessing nonlinearities in microelectromechanical membranes. However, the generation of frequency combs at radio frequencies (RF) has been less explored, together with their potential application in wireless technologies. In this work, we demonstrate an RF system able to wirelessly and passively generate frequency combs. This circuit, which we name quasi-harmonic tag (qHT), offers a battery-free solution for far-field ranging of unmanned vehicles (UVs) in GPS-denied settings, and it enables a strong immunity to multipath interference, providing better accuracy than other RF approaches to far-field ranging. Here, we discuss the principle of operation, design, implementation, and performance of qHTs used to remotely measure the azimuthal distance of a UV flying in an uncontrolled electromagnetic environment. We show that qHTs can wirelessly generate frequency combs with μWatt-levels of incident power by leveraging the nonlinear interaction between an RF parametric oscillator and a high quality factor piezoelectric microacoustic resonator. Our technique for frequency comb generation opens new avenues for a wide range of RF applications beyond ranging, including timing, computing and sensing.

Enhanced branched-chain amino acid metabolism improves age-related reproduction in C. elegans

Reproductive ageing is one of the earliest human ageing phenotypes, and mitochondrial dysfunction has been linked to oocyte quality decline; however, it is not known which mitochondrial metabolic processes are critical for oocyte quality maintenance with age. To understand how mitochondrial processes contribute to Caenorhabditis elegans oocyte quality, we characterized the mitochondrial proteomes of young and aged wild-type and long-reproductive daf-2 mutants. Here we show that the mitochondrial proteomic profiles of young wild-type and daf-2 worms are similar and share upregulation of branched-chain amino acid (BCAA) metabolism pathway enzymes. Reduction of the BCAA catabolism enzyme BCAT-1 shortens reproduction, elevates mitochondrial reactive oxygen species levels, and shifts mitochondrial localization. Moreover, bcat-1 knockdown decreases oocyte quality in daf-2 worms and reduces reproductive capability, indicating the role of this pathway in the maintenance of oocyte quality with age. Notably, oocyte quality deterioration can be delayed, and reproduction can be extended in wild-type animals both by bcat-1 overexpression and by supplementing with vitamin B1, a cofactor needed for BCAA metabolism.

Square beams for optimal tiling in transmission electron microscopy

Imaging large fields of view at a high magnification requires tiling. Transmission electron microscopes typically have round beam profiles; therefore, tiling across a large area is either imperfect or results in uneven exposures, a problem for dose-sensitive samples. Here, we introduce a square electron beam that can easily be retrofitted in existing microscopes, and demonstrate its application, showing that it can tile nearly perfectly and deliver cryo-electron microscopy imaging with a resolution comparable to conventional set-ups.

Meta-Research: Understudied genes are lost in a leaky pipeline between genome-wide assays and reporting of results

Present-day publications on human genes primarily feature genes that already appeared in many publications prior to completion of the Human Genome Project in 2003. These patterns persist despite the subsequent adoption of high-throughput technologies, which routinely identify novel genes associated with biological processes and disease. Although several hypotheses for bias in the selection of genes as research targets have been proposed, their explanatory powers have not yet been compared. Our analysis suggests that understudied genes are systematically abandoned in favor of better-studied genes between the completion of -omics experiments and the reporting of results. Understudied genes remain abandoned by studies that cite these -omics experiments. Conversely, we find that publications on understudied genes may even accrue a greater number of citations. Among 45 biological and experimental factors previously proposed to affect which genes are being studied, we find that 33 are significantly associated with the choice of hit genes presented in titles and abstracts of -omics studies. To promote the investigation of understudied genes, we condense our insights into a tool, find my understudied genes (FMUG), that allows scientists to engage with potential bias during the selection of hits. We demonstrate the utility of FMUG through the identification of genes that remain understudied in vertebrate aging. FMUG is developed in Flutter and is available for download at fmug.amaral.northwestern.edu as a MacOS/Windows app.

More than a photoreceptor: aureochromes are intrinsic to the diatom light-regulated transcriptional network

This article comments on:

Im SH, Lepetit B, Mosesso N, Shrestha S, Weiss L, Nymark M, Roellig R, Wilhelm C, Isono E, Kroth PG. 2024. Identification of promoter targets by Aureochrome 1a in the diatom Phaeodactylum tricornutum. Journal of Experimental Botany 75, 1834–1851.

Effects of Electron-Withdrawing Strengths of the Substituents on the Properties of 4-(Carbazolyl-R-benzoyl)-5-CF3-1H-1,2,3-triazole Derivatives as Blue Emitters for Doping-Free Electroluminescence Devices

The synthesis of four 4-(carbazolyl-R-benzoyl)-5-CF3-1H-1,2,3-triazoles with extra groups ((3-methyl)-phenyl-, 4-fluorophenyl-, quinolinyl-, or (3-trifluoromethyl)-phenyl-) in the acceptor fragment has been reported. The effects of substituents with different electron-withdrawing strengths on the thermal, electrochemical, photophysical, and electroluminescence properties of the synthesized compounds are discussed. The results of X-ray analyses and density functional theory (DFT) calculations support unusual molecular packing and electronic properties. The compounds are capable of glass formation with glass transition temperatures ranging from 54-84 °C. Ionization potentials of the compounds are in the range of 5.98-6.22 eV and electron affinities range from 3.09 to 3.35 eV. Under ultraviolet excitation, the neat films of the compounds exhibit blue emission with photoluminescence quantum yields ranging from 18 to 27%. The films of selected compounds are used for the preparation of host-free light-emitting layers of organic light-emitting diodes with very simple device structures and an external quantum efficiency of 4.6%.

Dynamics of the charge transfer to solvent process in aqueous iodide

Charge-transfer-to-solvent states in aqueous halides are ideal systems for studying the electron-transfer dynamics to the solvent involving a complex interplay between electronic excitation and solvent polarization. Despite extensive experimental investigations, a full picture of the charge-transfer-to-solvent dynamics has remained elusive. Here, we visualise the intricate interplay between the dynamics of the electron and the solvent polarization occurring in this process. Through the combined use of ab initio molecular dynamics and machine learning methods, we investigate the structure, dynamics and free energy as the excited electron evolves through the charge-transfer-to-solvent process, which we characterize as a sequence of states denoted charge-transfer-to-solvent, contact-pair, solvent-separated, and hydrated electron states, depending on the distance between the iodine and the excited electron. Our assignment of the charge-transfer-to-solvent states is supported by the good agreement between calculated and measured vertical binding energies. Our results reveal the charge transfer process in terms of the underlying atomic processes and mechanisms.

Transient states during the annealing of mismatched and bulged oligonucleotides

Oligonucleotide hybridization is crucial in various biological, prebiotic and nanotechnological processes, including gene regulation, non-enzymatic primer extension and DNA nanodevice assembly. Although extensive research has focused on the thermodynamics and kinetics of nucleic acid hybridization, the behavior of complex mixtures and the outcome of competition for target binding remain less well understood. In this study, we investigate the impact of mismatches and bulges in a 12 bp DNA or RNA duplex on its association (kon) and dissociation (koff) kinetics. We find that such defects have relatively small effects on the association kinetics, while the dissociation kinetics vary in a position-dependent manner by up to 6 orders of magnitude. Building upon this observation, we explored a competition scenario involving multiple oligonucleotides, and observed a transient low specificity of probe hybridization to fully versus partially complementary targets in solution. We characterize these long-lived metastable states and their evolution toward equilibrium, and show that sufficiently long-lived mis-paired duplexes can serve as substrates for prebiotically relevant chemical copying reactions. Our results suggest that transient low accuracy states may spontaneously emerge within all complex nucleic acid systems comprising a large enough number of competing strands, with potential repercussions for gene regulation in the realm of modern biology and the prebiotic preservation of genetic information.

Can neural networks benefit from objectives that encourage iterative convergent computations? A case study of ResNets and object classification

Recent work has suggested that feedforward residual neural networks (ResNets) approximate iterative recurrent computations. Iterative computations are useful in many domains, so they might provide good solutions for neural networks to learn. However, principled methods for measuring and manipulating iterative convergence in neural networks remain lacking. Here we address this gap by 1) quantifying the degree to which ResNets learn iterative solutions and 2) introducing a regularization approach that encourages the learning of iterative solutions. Iterative methods are characterized by two properties: iteration and convergence. To quantify these properties, we define three indices of iterative convergence. Consistent with previous work, we show that, even though ResNets can express iterative solutions, they do not learn them when trained conventionally on computer-vision tasks. We then introduce regularizations to encourage iterative convergent computation and test whether this provides a useful inductive bias. To make the networks more iterative, we manipulate the degree of weight sharing across layers using soft gradient coupling. This new method provides a form of recurrence regularization and can interpolate smoothly between an ordinary ResNet and a "recurrent" ResNet (i.e., one that uses identical weights across layers and thus could be physically implemented with a recurrent network computing the successive stages iteratively across time). To make the networks more convergent we impose a Lipschitz constraint on the residual functions using spectral normalization. The three indices of iterative convergence reveal that the gradient coupling and the Lipschitz constraint succeed at making the networks iterative and convergent, respectively. To showcase the practicality of our approach, we study how iterative convergence impacts generalization on standard visual recognition tasks (MNIST, CIFAR-10, CIFAR-100) or challenging recognition tasks with partial occlusions (Digitclutter). We find that iterative convergent computation, in these tasks, does not provide a useful inductive bias for ResNets. Importantly, our approach may be useful for investigating other network architectures and tasks as well and we hope that our study provides a useful starting point for investigating the broader question of whether iterative convergence can help neural networks in their generalization.

A Prebiotic Precursor to Life's Phosphate Transfer System with an ATP Analog and Histidyl Peptide Organocatalysts

Biochemistry is dependent upon enzyme catalysts accelerating key reactions. At the origin of life, prebiotic chemistry must have incorporated catalytic reactions. While this would have yielded much needed amplification of certain reaction products, it would come at the possible cost of rapidly depleting the high energy molecules that acted as chemical fuels. Biochemistry solves this problem by combining kinetically stable and thermodynamically activated molecules (e.g., ATP) with enzyme catalysts. Here, we demonstrate a prebiotic phosphate transfer system involving an ATP analog (imidazole phosphate) and histidyl peptides, which function as organocatalytic enzyme analogs. We demonstrate that histidyl peptides catalyze phosphorylations via a phosphorylated histidyl intermediate. We integrate these histidyl-catalyzed phosphorylations into a complete prebiotic scenario whereby inorganic phosphate is incorporated into organic compounds though physicochemical wet-dry cycles. Our work demonstrates a plausible system for the catalyzed production of phosphorylated compounds on the early Earth and how organocatalytic peptides, as enzyme precursors, could have played an important role in this.

Alignment of density maps in Wasserstein distance

In this article, we propose an algorithm for aligning three-dimensional objects when represented as density maps, motivated by applications in cryogenic electron microscopy. The algorithm is based on minimizing the 1-Wasserstein distance between the density maps after a rigid transformation. The induced loss function enjoys a more benign landscape than its Euclidean counterpart and Bayesian optimization is employed for computation. Numerical experiments show improved accuracy and efficiency over existing algorithms on the alignment of real protein molecules. In the context of aligning heterogeneous pairs, we illustrate a potential need for new distance functions.

Neural criticality from effective latent variables

Observations of power laws in neural activity data have raised the intriguing notion that brains may operate in a critical state. One example of this critical state is 'avalanche criticality', which has been observed in various systems, including cultured neurons, zebrafish, rodent cortex, and human EEG. More recently, power laws were also observed in neural populations in the mouse under an activity coarse-graining procedure, and they were explained as a consequence of the neural activity being coupled to multiple latent dynamical variables. An intriguing possibility is that avalanche criticality emerges due to a similar mechanism. Here, we determine the conditions under which latent dynamical variables give rise to avalanche criticality. We find that populations coupled to multiple latent variables produce critical behavior across a broader parameter range than those coupled to a single, quasi-static latent variable, but in both cases, avalanche criticality is observed without fine-tuning of model parameters. We identify two regimes of avalanches, both critical but differing in the amount of information carried about the latent variable. Our results suggest that avalanche criticality arises in neural systems in which activity is effectively modeled as a population driven by a few dynamical variables and these variables can be inferred from the population activity.

The eukaryotic-like characteristics of small GTPase, roadblock and TRAPPC3 proteins from Asgard archaea

Membrane-enclosed organelles are defining features of eukaryotes in distinguishing these organisms from prokaryotes. Specification of distinct membranes is critical to assemble and maintain discrete compartments. Small GTPases and their regulators are the signaling molecules that drive membrane-modifying machineries to the desired location. These signaling molecules include Rab and Rag GTPases, roadblock and longin domain proteins, and TRAPPC3-like proteins. Here, we take a structural approach to assess the relatedness of these eukaryotic-like proteins in Asgard archaea, the closest known prokaryotic relatives to eukaryotes. We find that the Asgard archaea GTPase core domains closely resemble eukaryotic Rabs and Rags. Asgard archaea roadblock, longin and TRAPPC3 domain-containing proteins form dimers similar to those found in the eukaryotic TRAPP and Ragulator complexes. We conclude that the emergence of these protein architectures predated eukaryogenesis, however further adaptations occurred in proto-eukaryotes to allow these proteins to regulate distinct internal membranes.

New estimates indicate that males are not larger than females in most mammal species

Sexual size dimorphism has motivated a large body of research on mammalian mating strategies and sexual selection. Despite some contrary evidence, the narrative that larger males are the norm in mammals-upheld since Darwin's Descent of Man-still dominates today, supported by meta-analyses that use coarse measures of dimorphism and taxonomically-biased sampling. With newly-available datasets and primary sources reporting sex-segregated means and variances in adult body mass, we estimate statistically-determined rates of sexual size dimorphism in mammals, sampling taxa by their species richness at the family level. Our analyses of wild, non-provisioned populations representing >400 species indicate that although males tend to be larger than females when dimorphism occurs, males are not larger in most mammal species, suggesting a need to revisit other assumptions in sexual selection research.

Interactions between circuit architecture and plasticity in a closed-loop cerebellar system

Determining the sites and directions of plasticity underlying changes in neural activity and behavior is critical for understanding mechanisms of learning. Identifying such plasticity from neural recording data can be challenging due to feedback pathways that impede reasoning about cause and effect. We studied interactions between feedback, neural activity, and plasticity in the context of a closed-loop motor learning task for which there is disagreement about the loci and directions of plasticity: vestibulo-ocular reflex learning. We constructed a set of circuit models that differed in the strength of their recurrent feedback, from no feedback to very strong feedback. Despite these differences, each model successfully fit a large set of neural and behavioral data. However, the patterns of plasticity predicted by the models fundamentally differed, with the direction of plasticity at a key site changing from depression to potentiation as feedback strength increased. Guided by our analysis, we suggest how such models can be experimentally disambiguated. Our results address a long-standing debate regarding cerebellum-dependent motor learning, suggesting a reconciliation in which learning-related changes in the strength of synaptic inputs to Purkinje cells are compatible with seemingly oppositely directed changes in Purkinje cell spiking activity. More broadly, these results demonstrate how changes in neural activity over learning can appear to contradict the sign of the underlying plasticity when either internal feedback or feedback through the environment is present.

Disentangling top-down drivers of mortality underlying diel population dynamics of Prochlorococcus in the North Pacific Subtropical Gyre

Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. We find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics.

Cytidine deaminases APOBEC3C and APOBEC3D promote DNA replication stress resistance in pancreatic cancer cells

Gemcitabine is a potent inhibitor of DNA replication and is a mainstay therapeutic for diverse cancers, particularly pancreatic ductal adenocarcinoma (PDAC). However, most tumors remain refractory to gemcitabine therapies. Here, to define the cancer cell response to gemcitabine, we performed genome-scale CRISPR-Cas9 chemical-genetic screens in PDAC cells and found selective loss of cell fitness upon disruption of the cytidine deaminases APOBEC3C and APOBEC3D. Following gemcitabine treatment, APOBEC3C and APOBEC3D promote DNA replication stress resistance and cell survival by deaminating cytidines in the nuclear genome to ensure DNA replication fork restart and repair in PDAC cells. We provide evidence that the chemical-genetic interaction between APOBEC3C or APOBEC3D and gemcitabine is absent in nontransformed cells but is recapitulated across different PDAC cell lines, in PDAC organoids and in PDAC xenografts. Thus, we uncover roles for APOBEC3C and APOBEC3D in DNA replication stress resistance and offer plausible targets for improving gemcitabine-based therapies for PDAC.

Filament formation drives catalysis by glutaminase enzymes important in cancer progression

The glutaminase enzymes GAC and GLS2 catalyze the hydrolysis of glutamine to glutamate, satisfying the 'glutamine addiction' of cancer cells. They are the targets of anti-cancer drugs; however, their mechanisms of activation and catalytic activity have been unclear. Here we demonstrate that the ability of GAC and GLS2 to form filaments is directly coupled to their catalytic activity and present their cryo-EM structures which provide a view of the conformational states essential for catalysis. Filament formation guides an 'activation loop' to assume a specific conformation that works together with a 'lid' to close over the active site and position glutamine for nucleophilic attack by an essential serine. Our findings highlight how ankyrin repeats on GLS2 regulate enzymatic activity, while allosteric activators stabilize, and clinically relevant inhibitors block, filament formation that enables glutaminases to catalyze glutaminolysis and support cancer progression.

Extending the Usefulness of the Brief Observation of Social Communication Change (BOSCC): Validating the Phrase Speech and Young Fluent Version

The current study investigated the utility of the Brief Observation of Social Communication Change-Phrase Speech Young Fluent (BOSCC-PSYF) as an outcome measure of treatment response by analyzing the measure's psychometric properties and initial validity. The BOSCC coding scheme was applied to 345 administrations from 160 participants diagnosed with autism. Participants included individuals of any age with phrase speech, or individuals under the age of 8 years with complex sentences. All were receiving behavioral intervention throughout the study. Test-retest and inter-rater reliability were good for the Early Communication and Social Reciprocity/Language domains, and fair for the Restricted and Repetitive Behavior domain. Significant changes occurred over time in the Early Communication and Social Reciprocity/Language domains, and Core Total scores. The BOSCC-PSYF may provide a low-cost, flexible, and user-friendly outcome measure that reliably measures changes in broad social communicative behaviors in a short period of time.

The function of the feeding groove of 'typical excavate' flagellates

Phagotrophic flagellates are the main consumers of bacteria and picophytoplankton. Despite their ecological significance in the 'microbial loop', many of their predation mechanisms remain unclear. 'Typical excavates' bear a ventral groove, where prey is captured for ingestion. The consequences of feeding through a 'semi-rigid' furrow on the prey size range have not been explored. An unidentified moving element called 'the wave' that sweeps along the bottom of the groove toward the site of phagocytosis has been observed in a few species; its function is unclear. We investigated the presence, behavior, and function of the wave in four species from the three excavate clades (Discoba, Metamonada, and Malawimonadida) and found it present in all studied cases, suggesting the potential homology of this feature across all three groups. The wave displayed a species-specific behavior and was crucial for phagocytosis. The morphology of the feeding groove had an upper-prey size limit for successful prey captures, but smaller particles were not constrained. Additionally, the ingestion efficiencies were species dependent. By jointly studying these feeding traits, we speculate on adaptations to differences in food availability to better understand their ecological functions.

Ubiquitous filter feeders shape open ocean microbial community structure and function

The mechanism of mortality plays a large role in how microorganisms in the open ocean contribute to global energy and nutrient cycling. Salps are ubiquitous pelagic tunicates that are a well-known mortality source for large phototrophic microorganisms in coastal and high-latitude systems, but their impact on the immense populations of smaller prokaryotes in the tropical and subtropical open ocean gyres is not well quantified. We used robustly quantitative techniques to measure salp clearance and enrichment of specific microbial functional groups in the North Pacific Subtropical Gyre, one of the largest ecosystems on Earth. We discovered that salps are a previously unknown predator of the globally abundant nitrogen fixer Crocosphaera; thus, salps restrain new nitrogen delivery to the marine ecosystem. We show that the ocean's two numerically dominant cells, Prochlorococcus and SAR11, are not consumed by salps, which offers a new explanation for the dominance of small cells in open ocean systems. We also identified a double bonus for Prochlorococcus, wherein it not only escapes salp predation but the salps also remove one of its major mixotrophic predators, the prymnesiophyte Chrysochromulina. When we modeled the interaction between salp mesh and particles, we found that cell size alone could not account for these prey selection patterns. Instead, the results suggest that alternative mechanisms, such as surface property, shape, nutritional quality, or even prey behavior, determine which microbial cells are consumed by salps. Together, these results identify salps as a major factor in shaping the structure, function, and ecology of open ocean microbial communities.

Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts

Protein-protein interactions (PPIs) drive cellular processes and responses to environmental cues, reflecting the cellular state. Here we develop Tapioca, an ensemble machine learning framework for studying global PPIs in dynamic contexts. Tapioca predicts de novo interactions by integrating mass spectrometry interactome data from thermal/ion denaturation or cofractionation workflows with protein properties and tissue-specific functional networks. Focusing on the thermal proximity coaggregation method, we improved the experimental workflow. Finely tuned thermal denaturation afforded increased throughput, while cell lysis optimization enhanced protein detection from different subcellular compartments. The Tapioca workflow was next leveraged to investigate viral infection dynamics. Temporal PPIs were characterized during the reactivation from latency of the oncogenic Kaposi's sarcoma-associated herpesvirus. Together with functional assays, NUCKS was identified as a proviral hub protein, and a broader role was uncovered by integrating PPI networks from alpha- and betaherpesvirus infections. Altogether, Tapioca provides a web-accessible platform for predicting PPIs in dynamic contexts.

A novel RNF125 variant associated with Tenorio syndrome alters ubiquitin chain binding

A key signalling pathway required for clearance of viruses from host cells relies on the receptor protein, retinoic acid-inducible gene I (RIG-I). The activity of RIG-I is tightly controlled, and once bound to viral dsRNA, addition of lysine 63-linked ubiquitin chains activates signalling. Meanwhile, the addition of lysine 48-linked ubiquitin chains to RIG-I is required to terminate signalling when the infection has been resolved. Really interesting new gene (RING) finger protein 125 (RNF125) is the E3 ligase responsible for addition of the ubiquitin chains that terminate signalling, with disruption of its function associated with Tenorio syndrome. Here we describe a novel RNF125 gene variant in an individual with clinical symptoms including intellectual disability, macrocephaly and congenital heart disease, consistent with Tenorio syndrome. The newly identified Tenorio syndrome-associated variant [(NM_017831.4):c.670G>C p.Glu224Gln] is the first to be found in the ubiquitin interaction motif (UIM) of RNF125. While the E3 ligase activity of this RNF125 variant is retained, it has an impaired ability to interact with lysine 63-linked ubiquitin chains. The function of the UIM in RNF125 is uncertain; however, this study suggests that the UIM binds lysine 63-linked ubiquitin chains, and that this interaction is required for the normal function of RNF125.

Temperature and CO2 interactively drive shifts in the compositional and functional structure of peatland protist communities

Microbes affect the global carbon cycle that influences climate change and are in turn influenced by environmental change. Here, we use data from a long-term whole-ecosystem warming experiment at a boreal peatland to answer how temperature and CO2 jointly influence communities of abundant, diverse, yet poorly understood, non-fungi microbial Eukaryotes (protists). These microbes influence ecosystem function directly through photosynthesis and respiration, and indirectly, through predation on decomposers (bacteria and fungi). Using a combination of high-throughput fluid imaging and 18S amplicon sequencing, we report large climate-induced, community-wide shifts in the community functional composition of these microbes (size, shape, and metabolism) that could alter overall function in peatlands. Importantly, we demonstrate a taxonomic convergence but a functional divergence in response to warming and elevated CO2 with most environmental responses being contingent on organismal size: warming effects on functional composition are reversed by elevated CO2 and amplified in larger microbes but not smaller ones. These findings show how the interactive effects of warming and rising CO2 levels could alter the structure and function of peatland microbial food webs-a fragile ecosystem that stores upwards of 25% of all terrestrial carbon and is increasingly threatened by human exploitation.

Natural soda lakes provide compatible conditions for RNA and membrane function that could have enabled the origin of life

The origin of life likely occurred within environments that concentrated cellular precursors and enabled their co-assembly into cells. Soda lakes (those dominated by Na+ ions and carbonate species) can concentrate precursors of RNA and membranes, such as phosphate, cyanide, and fatty acids. Subsequent assembly of RNA and membranes into cells is a long-standing problem because RNA function requires divalent cations, e.g. Mg2+, but Mg2+ disrupts fatty acid membranes. The low solubility of Mg-containing carbonates limits soda lakes to moderate Mg2+ concentrations (∼1 mM), so we investigated whether both RNAs and membranes function within these lakes. We collected water from Last Chance Lake and Goodenough Lake in Canada. Because we sampled after seasonal evaporation, the lake water contained ∼1 M Na+ and ∼1 mM Mg2+ near pH 10. In the laboratory, nonenzymatic, RNA-templated polymerization of 2-aminoimidazole-activated ribonucleotides occurred at comparable rates in lake water and standard laboratory conditions (50 mM MgCl2, pH 8). Additionally, we found that a ligase ribozyme that uses oligonucleotide substrates activated with 2-aminoimidazole was active in lake water after adjusting pH from ∼10 to 9. We also observed that decanoic acid and decanol assembled into vesicles in a dilute solution that resembled lake water after seasonal rains, and that those vesicles retained encapsulated solutes despite salt-induced flocculation when the external solution was replaced with dry-season lake water. By identifying compatible conditions for nonenzymatic and ribozyme-catalyzed RNA assembly, and for encapsulation by membranes, our results suggest that soda lakes could have enabled cellular life to emerge on Earth, and perhaps elsewhere.

Parameter identifiability and model selection for partial differential equation models of cell invasion

When employing mechanistic models to study biological phenomena, practical parameter identifiability is important for making accurate predictions across wide ranges of unseen scenarios, as well as for understanding the underlying mechanisms. In this work, we use a profile-likelihood approach to investigate parameter identifiability for four extensions of the Fisher-Kolmogorov-Petrovsky-Piskunov (Fisher-KPP) model, given experimental data from a cell invasion assay. We show that more complicated models tend to be less identifiable, with parameter estimates being more sensitive to subtle differences in experimental procedures, and that they require more data to be practically identifiable. As a result, we suggest that parameter identifiability should be considered alongside goodness-of-fit and model complexity as criteria for model selection.

Dynamic and selective engrams emerge with memory consolidation

Episodic memories are encoded by experience-activated neuronal ensembles that remain necessary and sufficient for recall. However, the temporal evolution of memory engrams after initial encoding is unclear. In this study, we employed computational and experimental approaches to examine how the neural composition and selectivity of engrams change with memory consolidation. Our spiking neural network model yielded testable predictions: memories transition from unselective to selective as neurons drop out of and drop into engrams; inhibitory activity during recall is essential for memory selectivity; and inhibitory synaptic plasticity during memory consolidation is critical for engrams to become selective. Using activity-dependent labeling, longitudinal calcium imaging and a combination of optogenetic and chemogenetic manipulations in mouse dentate gyrus, we conducted contextual fear conditioning experiments that supported our model's predictions. Our results reveal that memory engrams are dynamic and that changes in engram composition mediated by inhibitory plasticity are crucial for the emergence of memory selectivity.

When do stereotypes undermine indirect reciprocity?

Social reputations provide a powerful mechanism to stimulate human cooperation, but observing individual reputations can be cognitively costly. To ease this burden, people may rely on proxies such as stereotypes, or generalized reputations assigned to groups. Such stereotypes are less accurate than individual reputations, and so they could disrupt the positive feedback between altruistic behavior and social standing, undermining cooperation. How do stereotypes impact cooperation by indirect reciprocity? We develop a theoretical model of group-structured populations in which individuals are assigned either individual reputations based on their own actions or stereotyped reputations based on their groups' behavior. We find that using stereotypes can produce either more or less cooperation than using individual reputations, depending on how widely reputations are shared. Deleterious outcomes can arise when individuals adapt their propensity to stereotype. Stereotyping behavior can spread and can be difficult to displace, even when it compromises collective cooperation and even though it makes a population vulnerable to invasion by defectors. We discuss the implications of our results for the prevalence of stereotyping and for reputation-based cooperation in structured populations.

Bayesian inference of relative fitness on high-throughput pooled competition assays

The tracking of lineage frequencies via DNA barcode sequencing enables the quantification of microbial fitness. However, experimental noise coming from biotic and abiotic sources complicates the computation of a reliable inference. We present a Bayesian pipeline to infer relative microbial fitness from high-throughput lineage tracking assays. Our model accounts for multiple sources of noise and propagates uncertainties throughout all parameters in a systematic way. Furthermore, using modern variational inference methods based on automatic differentiation, we are able to scale the inference to a large number of unique barcodes. We extend this core model to analyze multi-environment assays, replicate experiments, and barcodes linked to genotypes. On simulations, our method recovers known parameters within posterior credible intervals. This work provides a generalizable Bayesian framework to analyze lineage tracking experiments. The accompanying open-source software library enables the adoption of principled statistical methods in experimental evolution.

EphB1 controls long-range cortical axon guidance through a cell non-autonomous role in GABAergic cells

EphB1 is required for proper guidance of cortical axon projections during brain development, but how EphB1 regulates this process remains unclear. We show here that EphB1 conditional knockout (cKO) in GABAergic cells (Vgat-Cre), but not in cortical excitatory neurons (Emx1-Cre), reproduced the cortical axon guidance defects observed in global EphB1 KO mice. Interestingly, in EphB1 cKOVgat mice, the misguided axon bundles contained co-mingled striatal GABAergic and somatosensory cortical glutamatergic axons. In wild-type mice, somatosensory axons also co-fasciculated with striatal axons, notably in the globus pallidus, suggesting that a subset of glutamatergic cortical axons normally follows long-range GABAergic axons to reach their targets. Surprisingly, the ectopic axons in EphB1 KO mice were juxtaposed to major blood vessels. However, conditional loss of EphB1 in endothelial cells (Tie2-Cre) did not produce the axon guidance defects, suggesting that EphB1 in GABAergic neurons normally promotes avoidance of these ectopic axons from the developing brain vasculature. Together, our data reveal a new role for EphB1 in GABAergic neurons to influence proper cortical glutamatergic axon guidance during brain development.

Endotaxis: A neuromorphic algorithm for mapping, goal-learning, navigation, and patrolling

An animal entering a new environment typically faces three challenges: explore the space for resources, memorize their locations, and navigate towards those targets as needed. Here we propose a neural algorithm that can solve all these problems and operates reliably in diverse and complex environments. At its core, the mechanism makes use of a behavioral module common to all motile animals, namely the ability to follow an odor to its source. We show how the brain can learn to generate internal "virtual odors" that guide the animal to any location of interest. This endotaxis algorithm can be implemented with a simple 3-layer neural circuit using only biologically realistic structures and learning rules. Several neural components of this scheme are found in brains from insects to humans. Nature may have evolved a general mechanism for search and navigation on the ancient backbone of chemotaxis.

Structural models of genome-wide covariance identify multiple common dimensions in autism

Common genetic variation has been associated with multiple phenotypic features in Autism Spectrum Disorder (ASD). However, our knowledge of shared genetic factor structures contributing to this highly heterogeneous phenotypic spectrum is limited. Here, we developed and implemented a structural equation modelling framework to directly model genomic covariance across core and non-core ASD phenotypes, studying autistic individuals of European descent with a case-only design. We identified three independent genetic factors most strongly linked to language performance, behaviour and developmental motor delay, respectively, studying an autism community sample (N = 5331). The three-factorial structure was largely confirmed in independent ASD-simplex families (N = 1946), although we uncovered, in addition, simplex-specific genetic overlap between behaviour and language phenotypes. Multivariate models across cohorts revealed novel associations, including links between language and early mastering of self-feeding. Thus, the common genetic architecture in ASD is multi-dimensional with overarching genetic factors contributing, in combination with ascertainment-specific patterns, to phenotypic heterogeneity.

Optimization Algorithms for Multi-species Spherical Spin Glasses

This paper develops approximate message passing algorithms to optimize multi-species spherical spin glasses. We first show how to efficiently achieve the algorithmic threshold energy identified in our companion work (Huang and Sellke in arXiv preprint, 2023. arXiv:2303.12172), thus confirming that the Lipschitz hardness result proved therein is tight. Next we give two generalized algorithms which produce multiple outputs and show all of them are approximate critical points. Namely, in an r-species model we construct 2 r approximate critical points when the external field is stronger than a "topological trivialization" phase boundary, and exponentially many such points in the complementary regime. We also compute the local behavior of the Hamiltonian around each. These extensions are relevant for another companion work (Huang and Sellke in arXiv preprint, 2023. arXiv:2308.09677) on topological trivialization of the landscape.

Spatial-temporal order-disorder transition in angiogenic NOTCH signaling controls cell fate specification

Angiogenesis is a morphogenic process resulting in the formation of new blood vessels from pre-existing ones, usually in hypoxic micro-environments. The initial steps of angiogenesis depend on robust differentiation of oligopotent endothelial cells into the Tip and Stalk phenotypic cell fates, controlled by NOTCH-dependent cell-cell communication. The dynamics of spatial patterning of this cell fate specification are only partially understood. Here, by combining a controlled experimental angiogenesis model with mathematical and computational analyses, we find that the regular spatial Tip-Stalk cell patterning can undergo an order-disorder transition at a relatively high input level of a pro-angiogenic factor VEGF. The resulting differentiation is robust but temporally unstable for most cells, with only a subset of presumptive Tip cells leading sprout extensions. We further find that sprouts form in a manner maximizing their mutual distance, consistent with a Turing-like model that may depend on local enrichment and depletion of fibronectin. Together, our data suggest that NOTCH signaling mediates a robust way of cell differentiation enabling but not instructing subsequent steps in angiogenic morphogenesis, which may require additional cues and self-organization mechanisms. This analysis can assist in further understanding of cell plasticity underlying angiogenesis and other complex morphogenic processes.