Programmed and self-organized flow of information during morphogenesis.

How the shape of embryos and organs emerges during development is a fundamental question that has fascinated scientists for centuries. Tissue dynamics arise from a small set of cell behaviours, including shape changes, cell contact remodelling, cell migration, cell division and cell extrusion. These behaviours require control over cell mechanics, namely active stresses associated with protrusive, contractile and adhesive forces, and hydrostatic pressure, as well as material properties of cells that dictate how cells respond to active stresses. In this Review, we address how cell mechanics and the associated cell behaviours are robustly organized in space and time during tissue morphogenesis. We first outline how not only gene expression and the resulting biochemical cues, but also mechanics and geometry act as sources of morphogenetic information to ultimately define the time and length scales of the cell behaviours driving morphogenesis. Next, we present two idealized modes of how this information flows - how it is read out and translated into a biological effect - during morphogenesis. The first, akin to a programme, follows deterministic rules and is hierarchical. The second follows the principles of self-organization, which rests on statistical rules characterizing the system's composition and configuration, local interactions and feedback. We discuss the contribution of these two modes to the mechanisms of four very general classes of tissue deformation, namely tissue folding and invagination, tissue flow and extension, tissue hollowing and, finally, tissue branching. Overall, we suggest a conceptual framework for understanding morphogenetic information that encapsulates genetics and biochemistry as well as mechanics and geometry as information modules, and the interplay of deterministic and self-organized mechanisms of their deployment, thereby diverging considerably from the traditional notion that shape is fully encoded and determined by genes.

A framework for understanding the functions of biomolecular condensates across scales.

Biomolecular condensates are found throughout eukaryotic cells, including in the nucleus, in the cytoplasm and on membranes. They are also implicated in a wide range of cellular functions, organizing molecules that act in processes ranging from RNA metabolism to signalling to gene regulation. Early work in the field focused on identifying condensates and understanding how their physical properties and regulation arise from molecular constituents. Recent years have brought a focus on understanding condensate functions. Studies have revealed functions that span different length scales: from molecular (modulating the rates of chemical reactions) to mesoscale (organizing large structures within cells) to cellular (facilitating localization of cellular materials and homeostatic responses). In this Roadmap, we discuss representative examples of biochemical and cellular functions of biomolecular condensates from the recent literature and organize these functions into a series of non-exclusive classes across the different length scales. We conclude with a discussion of areas of current interest and challenges in the field, and thoughts about how progress may be made to further our understanding of the widespread roles of condensates in cell biology.

Biomolecular condensates: organizers of cellular biochemistry.

Biomolecular condensates are micron-scale compartments in eukaryotic cells that lack surrounding membranes but function to concentrate proteins and nucleic acids. These condensates are involved in diverse processes, including RNA metabolism, ribosome biogenesis, the DNA damage response and signal transduction. Recent studies have shown that liquid-liquid phase separation driven by multivalent macromolecular interactions is an important organizing principle for biomolecular condensates. With this physical framework, it is now possible to explain how the assembly, composition, physical properties and biochemical and cellular functions of these important structures are regulated.

Single-molecule approaches embrace molecular cohorts.

Enormous mechanistic insight has been gained by studying the behavior of single molecules. The same approaches used to study proteins in isolation are now being leveraged to examine the changes in functional behavior that emerge when single molecules have company.

Grow now, pay later: When should a bacterium go into debt?

Microbes grow in a wide variety of environments and must balance growth and stress resistance. Despite the prevalence of such trade-offs, understanding of their role in nonsteady environments is limited. In this study, we introduce a mathematical model of "growth debt," where microbes grow rapidly initially, paying later with slower growth or heightened mortality. We first compare our model to a classical chemostat experiment, validating our proposed dynamics and quantifying Escherichia coli's stress resistance dynamics. Extending the chemostat theory to include serial-dilution cultures, we derive phase diagrams for the persistence of "debtor" microbes. We find that debtors cannot coexist with nondebtors if "payment" is increased mortality but can coexist if it lowers enzyme affinity. Surprisingly, weak noise considerably extends the persistence of resistance elements, pertinent for antibiotic resistance management. Our microbial debt theory, broadly applicable across many environments, bridges the gap between chemostat and serial dilution systems.

Coevolution of reproducers and replicators at the origin of life and the conditions for the origin of genomes.

There are two fundamentally distinct but inextricably linked types of biological evolutionary units, reproducers and replicators. Reproducers are cells and organelles that reproduce via various forms of division and maintain the physical continuity of compartments and their content. Replicators are genetic elements (GE), including genomes of cellular organisms and various autonomous elements, that both cooperate with reproducers and rely on the latter for replication. All known cells and organisms comprise a union between replicators and reproducers. We explore a model in which cells emerged via symbiosis between primordial "metabolic" reproducers (protocells) which evolved, on short time scales, via a primitive form of selection and random drift, and mutualist replicators. Mathematical modeling identifies the conditions, under which GE-carrying protocells can outcompete GE-less ones, taking into account that, from the earliest stages of evolution, replicators split into mutualists and parasites. Analysis of the model shows that, for the GE-containing protocells to win the competition and to be fixed in evolution, it is essential that the birth-death process of the GE is coordinated with the rate of protocell division. At the early stages of evolution, random, high-variance cell division is advantageous compared with symmetrical division because the former provides for the emergence of protocells containing only mutualists, preventing takeover by parasites. These findings illuminate the likely order of key events on the evolutionary route from protocells to cells that involved the origin of genomes, symmetrical cell division, and antiparasite defense systems.

Electron transport chains as a window into the earliest stages of evolution.

The origin and early evolution of life is generally studied under two different paradigms: bottom up and top down. Prebiotic chemistry and early Earth geochemistry allow researchers to explore possible origin of life scenarios. But for these "bottom-up" approaches, even successful experiments only amount to a proof of principle. On the other hand, "top-down" research on early evolutionary history is able to provide a historical account about ancient organisms, but is unable to investigate stages that occurred during and just after the origin of life. Here, we consider ancient electron transport chains (ETCs) as a potential bridge between early evolutionary history and a protocellular stage that preceded it. Current phylogenetic evidence suggests that ancestors of several extant ETC components were present at least as late as the last universal common ancestor of life. In addition, recent experiments have shown that some aspects of modern ETCs can be replicated by minerals, protocells, or organic cofactors in the absence of biological proteins. Here, we discuss the diversity of ETCs and other forms of chemiosmotic energy conservation, describe current work on the early evolution of membrane bioenergetics, and advocate for several lines of research to enhance this understanding by pairing top-down and bottom-up approaches.

Chemoproteomic mapping of the glycolytic targetome in cancer cells.

Hyperactivated glycolysis is a metabolic hallmark of most cancer cells. Although sporadic information has revealed that glycolytic metabolites possess nonmetabolic functions as signaling molecules, how these metabolites interact with and functionally regulate their binding targets remains largely elusive. Here, we introduce a target-responsive accessibility profiling (TRAP) approach that measures changes in ligand binding-induced accessibility for target identification by globally labeling reactive proteinaceous lysines. With TRAP, we mapped 913 responsive target candidates and 2,487 interactions for 10 major glycolytic metabolites in a model cancer cell line. The wide targetome depicted by TRAP unveils diverse regulatory modalities of glycolytic metabolites, and these modalities involve direct perturbation of enzymes in carbohydrate metabolism, intervention of an orphan transcriptional protein's activity and modulation of targetome-level acetylation. These results further our knowledge of how glycolysis orchestrates signaling pathways in cancer cells to support their survival, and inspire exploitation of the glycolytic targetome for cancer therapy.

Scaling laws in enzyme function reveal a new kind of biochemical universality.

All life on Earth is unified by its use of a shared set of component chemical compounds and reactions, providing a detailed model for universal biochemistry. However, this notion of universality is specific to known biochemistry and does not allow quantitative predictions about examples not yet observed. Here, we introduce a more generalizable concept of biochemical universality that is more akin to the kind of universality found in physics. Using annotated genomic datasets including an ensemble of 11,955 metagenomes, 1,282 archaea, 11,759 bacteria, and 200 eukaryotic taxa, we show how enzyme functions form universality classes with common scaling behavior in their relative abundances across the datasets. We verify that these scaling laws are not explained by the presence of compounds, reactions, and enzyme functions shared across known examples of life. We demonstrate how these scaling laws can be used as a tool for inferring properties of ancient life by comparing their predictions with a consensus model for the last universal common ancestor (LUCA). We also illustrate how network analyses shed light on the functional principles underlying the observed scaling behaviors. Together, our results establish the existence of a new kind of biochemical universality, independent of the details of life on Earth's component chemistry, with implications for guiding our search for missing biochemical diversity on Earth or for biochemistries that might deviate from the exact chemical makeup of life as we know it, such as at the origins of life, in alien environments, or in the design of synthetic life.

Mapping the per-residue surface electrostatic potential of CAPRIN1 along its phase-separation trajectory.

Electrostatic interactions and charge balance are important for the formation of biomolecular condensates involving proteins and nucleic acids. However, a detailed, atomistic picture of the charge distribution around proteins during the phase-separation process is lacking. Here, we use solution NMR spectroscopy to measure residue-specific near-surface electrostatic potentials (ϕENS) of the positively charged carboxyl-terminal intrinsically disordered 103 residues of CAPRIN1, an RNA-binding protein localized to membraneless organelles playing an important role in messenger RNA (mRNA) storage and translation. Measured ϕENS values have been mapped along the adenosine triphosphate (ATP)-induced phase-separation trajectory. In the absence of ATP, ϕENS values for the mixed state of CAPRIN1 are positive and large and progressively decrease as ATP is added. This is coupled to increasing interchain interactions, particularly between aromatic-rich and arginine-rich regions of the protein. Upon phase separation, CAPRIN1 molecules in the condensed phase are neutral (ϕENS [Formula: see text] 0 mV), with ∼five molecules of ATP associated with each CAPRIN1 chain. Increasing the ATP concentration further inverts the CAPRIN1 electrostatic potential, so that molecules become negatively charged, especially in aromatic-rich regions, leading to re-entrance into a mixed phase. Our results collectively show that a subtle balance between electrostatic repulsion and interchain attractive interactions regulates CAPRIN1 phase separation and provides insight into how nucleotides, such as ATP, can induce formation of and subsequently dissolve protein condensates.

Maturation and Conformational Switching of a De Novo Designed Phase-Separating Polypeptide.

Cellular compartments formed by biomolecular condensation are widespread features of cell biology. These organelle-like assemblies compartmentalize macromolecules dynamically within the crowded intracellular environment. However, the intermolecular interactions that produce condensed droplets may also create arrested states and potentially pathological assemblies such as fibers, aggregates, and gels through droplet maturation. Protein liquid-liquid phase separation is a metastable process, so maturation may be an intrinsic property of phase-separating proteins, where nucleation of different phases or states arises in supersaturated condensates. Here, we describe the formation of both phase-separated droplets and proteinaceous fibers driven by a de novo designed polypeptide. We characterize the formation of supramolecular fibers in vitro and in bacterial cells. We show that client proteins can be targeted to the fibers in cells using a droplet-forming construct. Finally, we explore the interplay between phase separation and fiber formation of the de novo polypeptide, showing that the droplets mature with a post-translational switch to largely ß conformations, analogous to models of pathological phase separation.

MeganServer: facilitating interactive access to metagenomic data on a server.

MOTIVATION: Metagenomic projects often involve large numbers of large sequencing datasets (totaling hundreds of gigabytes of data). Thus, computational preprocessing and analysis are usually performed on a server. The results of such analyses are then usually explored interactively. One approach is to use MEGAN, an interactive program that allows analysis and comparison of metagenomic datasets. Previous releases have required that the user first download the computed data from the server, an increasingly time-consuming process. Here, we present MeganServer, a stand-alone program that serves MEGAN files to the web, using a RESTful API, facilitating interactive analysis in MEGAN, without requiring prior download of the data. We describe a number of different application scenarios. AVAILABILITY AND IMPLEMENTATION: MeganServer is provided as a stand-alone program tools/megan-server in the MEGAN software suite, available at https://software-ab.cs.uni-tuebingen.de/download/megan6. Source is available at: https://github.com/husonlab/megan-ce/tree/master/src/megan/ms. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.