Dynamic models of human development and concepts of the individual.

Stem cells can be coaxed to self-organize into dynamic models of human development and early embryo formation. Despite their scientific promise, might widespread use of these technologies alter people's beliefs about what it means to be a human individual? Attention to some important philosophical distinctions may help navigate our thinking.

A simple rule for predicting function of microbial communities.

Microbial communities perform many important functions, such as carbon sequestration, decomposition, pathogen resistance, etc., but quantitatively predicting functions of new communities remains a major challenge. In this issue of Cell, Diaz-Colunga et al. report a new simple statistical regularity that enables such predictions.

Machine learning interpretable models of cell mechanics from protein images.

Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. Currently, no systematic strategy exists to infer large-scale physical properties of a cell from its molecular components. This is an obstacle to understanding processes such as cell adhesion and migration. Here, we develop a data-driven modeling pipeline to learn the mechanical behavior of adherent cells. We first train neural networks to predict cellular forces from images of cytoskeletal proteins. Strikingly, experimental images of a single focal adhesion (FA) protein, such as zyxin, are sufficient to predict forces and can generalize to unseen biological regimes. Using this observation, we develop two approaches-one constrained by physics and the other agnostic-to construct data-driven continuum models of cellular forces. Both reveal how cellular forces are encoded by two distinct length scales. Beyond adherent cell mechanics, our work serves as a case study for integrating neural networks into predictive models for cell biology.

Toward developing human organs via embryo models and chimeras.

Developing functional organs from stem cells remains a challenging goal in regenerative medicine. Existing methodologies, such as tissue engineering, bioprinting, and organoids, only offer partial solutions. This perspective focuses on two promising approaches emerging for engineering human organs from stem cells: stem cell-based embryo models and interspecies organogenesis. Both approaches exploit the premise of guiding stem cells to mimic natural development. We begin by summarizing what is known about early human development as a blueprint for recapitulating organogenesis in both embryo models and interspecies chimeras. The latest advances in both fields are discussed before highlighting the technological and knowledge gaps to be addressed before the goal of developing human organs could be achieved using the two approaches. We conclude by discussing challenges facing embryo modeling and interspecies organogenesis and outlining future prospects for advancing both fields toward the generation of human tissues and organs for basic research and translational applications.

Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective.

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

A developmental constraint model of cancer cell states and tumor heterogeneity.

Cancer is a disease that stems from a fundamental liability inherent to multicellular life forms in which an individual cell is capable of reneging on the interests of the collective organism. Although cancer is commonly described as an evolutionary process, a less appreciated aspect of tumorigenesis may be the constraints imposed by the organism's developmental programs. Recent work from single-cell transcriptomic analyses across a range of cancer types has revealed the recurrence, plasticity, and co-option of distinct cellular states among cancer cell populations. Here, we note that across diverse cancer types, the observed cell states are proximate within the developmental hierarchy of the cell of origin. We thus posit a model by which cancer cell states are directly constrained by the organism's "developmental map." According to this model, a population of cancer cells traverses the developmental map, thereby generating a heterogeneous set of states whose interactions underpin emergent tumor behavior.

Human organoids: New strategies and methods for analyzing human development and disease.

For decades, insight into fundamental principles of human biology and disease has been obtained primarily by experiments in animal models. While this has allowed researchers to understand many human biological processes in great detail, some developmental and disease mechanisms have proven difficult to study due to inherent species differences. The advent of organoid technology more than 10 years ago has established laboratory-grown organ tissues as an additional model system to recapitulate human-specific aspects of biology. The use of human 3D organoids, as well as other advances in single-cell technologies, has revealed unprecedented insights into human biology and disease mechanisms, especially those that distinguish humans from other species. This review highlights novel advances in organoid biology with a focus on how organoid technology has generated a better understanding of human-specific processes in development and disease.

Cell maturation: Hallmarks, triggers, and manipulation.

How cells become specialized, or "mature," is important for cell and developmental biology. While maturity is usually deemed a terminal fate, it may be more helpful to consider maturation not as a switch but as a dynamic continuum of adaptive phenotypic states set by genetic and environment programing. The hallmarks of maturity comprise changes in anatomy (form, gene circuitry, and interconnectivity) and physiology (function, rhythms, and proliferation) that confer adaptive behavior. We discuss efforts to harness their chemical (nutrients, oxygen, and growth factors) and physical (mechanical, spatial, and electrical) triggers in vitro and in vivo and how maturation strategies may support disease research and regenerative medicine.

Genomic structure predicts metabolite dynamics in microbial communities.

The metabolic activities of microbial communities play a defining role in the evolution and persistence of life on Earth, driving redox reactions that give rise to global biogeochemical cycles. Community metabolism emerges from a hierarchy of processes, including gene expression, ecological interactions, and environmental factors. In wild communities, gene content is correlated with environmental context, but predicting metabolite dynamics from genomes remains elusive. Here, we show, for the process of denitrification, that metabolite dynamics of a community are predictable from the genes each member of the community possesses. A simple linear regression reveals a sparse and generalizable mapping from gene content to metabolite dynamics for genomically diverse bacteria. A consumer-resource model correctly predicts community metabolite dynamics from single-strain phenotypes. Our results demonstrate that the conserved impacts of metabolic genes can predict community metabolite dynamics, enabling the prediction of metabolite dynamics from metagenomes, designing denitrifying communities, and discovering how genome evolution impacts metabolism.

Mapping transcriptomic vector fields of single cells.

Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses to enable accurate velocity estimations on a metabolically labeled human hematopoiesis scRNA-seq dataset. Furthermore, differential geometry analyses reveal mechanisms driving early megakaryocyte appearance and elucidate asymmetrical regulation within the PU.1-GATA1 circuit. Leveraging the least-action-path method, dynamo accurately predicts drivers of numerous hematopoietic transitions. Finally, in silico perturbations predict cell-fate diversions induced by gene perturbations. Dynamo, thus, represents an important step in advancing quantitative and predictive theories of cell-state transitions.

A segmentation clock patterns cellular differentiation in a bacterial biofilm.

Contrary to multicellular organisms that display segmentation during development, communities of unicellular organisms are believed to be devoid of such sophisticated patterning. Unexpectedly, we find that the gene expression underlying the nitrogen stress response of a developing Bacillus subtilis biofilm becomes organized into a ring-like pattern. Mathematical modeling and genetic probing of the underlying circuit indicate that this patterning is generated by a clock and wavefront mechanism, similar to that driving vertebrate somitogenesis. We experimentally validated this hypothesis by showing that predicted nutrient conditions can even lead to multiple concentric rings, resembling segments. We additionally confirmed that this patterning mechanism is driven by cell-autonomous oscillations. Importantly, we show that the clock and wavefront process also spatially patterns sporulation within the biofilm. Together, these findings reveal a biofilm segmentation clock that organizes cellular differentiation in space and time, thereby challenging the paradigm that such patterning mechanisms are exclusive to plant and animal development.

Cellular architecture of human brain metastases.

Brain metastasis (BrM) is the most common form of brain cancer, characterized by neurologic disability and an abysmal prognosis. Unfortunately, our understanding of the biology underlying human BrMs remains rudimentary. Here, we present an integrative analysis of >100,000 malignant and non-malignant cells from 15 human parenchymal BrMs, generated by single-cell transcriptomics, mass cytometry, and complemented with mouse model- and in silico approaches. We interrogated the composition of BrM niches, molecularly defined the blood-tumor interface, and revealed stromal immunosuppressive states enriched with infiltrated T cells and macrophages. Specific single-cell interrogation of metastatic tumor cells provides a framework of 8 functional cell programs that coexist or anticorrelate. Collectively, these programs delineate two functional BrM archetypes, one proliferative and the other inflammatory, that are evidently shaped through tumor-immune interactions. Our resource provides a foundation to understand the molecular basis of BrM in patients with tumor cell-intrinsic and host environmental traits.

Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches.

The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis.

The Mexican Tetra, Astyanax mexicanus, as a Model System in Cell and Developmental Biology.

Our understanding of cell and developmental biology has been greatly aided by a focus on a small number of model organisms. However, we are now in an era where techniques to investigate gene function can be applied across phyla, allowing scientists to explore the diversity and flexibility of developmental mechanisms and gain a deeper understanding of life. Researchers comparing the eyeless cave-adapted Mexican tetra, Astyanax mexicanus, with its river-dwelling counterpart are revealing how the development of the eyes, pigment, brain, cranium, blood, and digestive system evolves as animals adapt to new environments. Breakthroughs in our understanding of the genetic and developmental basis of regressive and constructive trait evolution have come from A. mexicanus research. They include understanding the types of mutations that alter traits, which cellular and developmental processes they affect, and how they lead to pleiotropy. We review recent progress in the field and highlight areas for future investigations that include evolution of sex differentiation, neural crest development, and metabolic regulation of embryogenesis.

The Unreasonable Effectiveness of Reaction Diffusion in Vertebrate Skin Color Patterning.

In 1952, Alan Turing published the reaction-diffusion (RD) mathematical framework, laying the foundations of morphogenesis as a self-organized process emerging from physicochemical first principles. Regrettably, this approach has been widely doubted in the field of developmental biology. First, we summarize Turing's line of thoughts to alleviate the misconception that RD is an artificial mathematical construct. Second, we discuss why phenomenological RD models are particularly effective for understanding skin color patterning at the meso/macroscopic scales, without the need to parameterize the profusion of variables at lower scales. More specifically, we discuss how RD models (a) recapitulate the diversity of actual skin patterns, (b) capture the underlying dynamics of cellular interactions, (c) interact with tissue size and shape, (d) can lead to ordered sequential patterning, (e) generate cellular automaton dynamics in lizards and snakes, (f) predict actual patterns beyond their statistical features, and (g) are robust to model variations. Third, we discuss the utility of linear stability analysis and perform numerical simulations to demonstrate how deterministic RD emerges from the underlying chaotic microscopic agents.

Repair of DNA Double-Strand Breaks by the Nonhomologous End Joining Pathway.

DNA double-strand breaks pose a serious threat to genome stability. In vertebrates, these breaks are predominantly repaired by nonhomologous end joining (NHEJ), which pairs DNA ends in a multiprotein synaptic complex to promote their direct ligation. NHEJ is a highly versatile pathway that uses an array of processing enzymes to modify damaged DNA ends and enable their ligation. The mechanisms of end synapsis and end processing have important implications for genome stability. Rapid and stable synapsis is necessary to limit chromosome translocations that result from the mispairing of DNA ends. Furthermore, end processing must be tightly regulated to minimize mutations at the break site. Here, we review our current mechanistic understanding of vertebrate NHEJ, with a particular focus on end synapsis and processing.

Food allergy as a biological food quality control system.

Food is simultaneously a source of essential nutrients and a potential source of lethal toxins and pathogens. Consequently, multiple sensory mechanisms evolved to monitor the quality of food based on the presence and relative abundance of beneficial and harmful food substances. These include the olfactory, gustatory, and gut chemosensory systems. Here we argue that, in addition to these systems, allergic immunity plays a role in food quality control by mounting allergic defenses against food antigens associated with noxious substances. Exaggeration of these defenses can result in pathological food allergy.

Inflammatory adaptation in barrier tissues.

Surface epithelia provide a critical barrier to the outside world. Upon a barrier breach, resident epithelial and immune cells coordinate efforts to control infections and heal tissue damage. Inflammation can etch lasting marks within tissues, altering features such as scope and quality of future responses. By remembering inflammatory experiences, tissues are better equipped to quickly and robustly respond to barrier breaches. Alarmingly, in disease states, memory may fuel the inflammatory fire. Here, we review the cellular communication networks in barrier tissues and the integration between tissue-resident and recruited immune cells and tissue stem cells underlying tissue adaptation to environmental stress.

Organs-on-a-chip models for biological research.

We explore the utility of bioengineered human tissues-individually or connected into physiological units-for biological research. While much smaller and simpler than their native counterparts, these tissues are complex enough to approximate distinct tissue phenotypes: molecular, structural, and functional. Unlike organoids, which form spontaneously and recapitulate development, "organs-on-a-chip" are engineered to display some specific functions of whole organs. Looking back, we discuss the key developments of this emerging technology. Thinking forward, we focus on the challenges faced to fully establish, validate, and utilize the fidelity of these models for biological research.

Reading the chromatinized genome.

Eukaryotic DNA-binding proteins operate in the context of chromatin, where nucleosomes are the elementary building blocks. Nucleosomal DNA is wrapped around a histone core, thereby rendering a large fraction of the DNA surface inaccessible to DNA-binding proteins. Nevertheless, first responders in DNA repair and sequence-specific transcription factors bind DNA target sites obstructed by chromatin. While early studies examined protein binding to histone-free DNA, it is only now beginning to emerge how DNA sequences are interrogated on nucleosomes. These readout strategies range from the release of nucleosomal DNA from histones, to rotational/translation register shifts of the DNA motif, and nucleosome-specific DNA binding modes that differ from those observed on naked DNA. Since DNA motif engagement on nucleosomes strongly depends on position and orientation, we argue that motif location and nucleosome positioning co-determine protein access to DNA in transcription and DNA repair.