What is cancer metabolism?

The uptake and metabolism of nutrients support fundamental cellular process from bioenergetics to biomass production and cell fate regulation. While many studies of cell metabolism focus on cancer cells, the principles of metabolism elucidated in cancer cells apply to a wide range of mammalian cells. The goal of this review is to discuss how the field of cancer metabolism provides a framework for revealing principles of cell metabolism and for dissecting the metabolic networks that allow cells to meet their specific demands. Understanding context-specific metabolic preferences and liabilities will unlock new approaches to target cancer cells to improve patient care.

Fundamental behaviors emerge from simulations of a living minimal cell.

We present a whole-cell fully dynamical kinetic model (WCM) of JCVI-syn3A, a minimal cell with a reduced genome of 493 genes that has retained few regulatory proteins or small RNAs. Cryo-electron tomograms provide the cell geometry and ribosome distributions. Time-dependent behaviors of concentrations and reaction fluxes from stochastic-deterministic simulations over a cell cycle reveal how the cell balances demands of its metabolism, genetic information processes, and growth, and offer insight into the principles of life for this minimal cell. The energy economy of each process including active transport of amino acids, nucleosides, and ions is analyzed. WCM reveals how emergent imbalances lead to slowdowns in the rates of transcription and translation. Integration of experimental data is critical in building a kinetic model from which emerges a genome-wide distribution of mRNA half-lives, multiple DNA replication events that can be compared to qPCR results, and the experimentally observed doubling behavior.

Atoms to Phenotypes: Molecular Design Principles of Cellular Energy Metabolism.

We report a 100-million atom-scale model of an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium, that reveals the cascade of energy conversion steps culminating in the generation of ATP from sunlight. Molecular dynamics simulations of this vesicle elucidate how the integral membrane complexes influence local curvature to tune photoexcitation of pigments. Brownian dynamics of small molecules within the chromatophore probe the mechanisms of directional charge transport under various pH and salinity conditions. Reproducing phenotypic properties from atomistic details, a kinetic model evinces that low-light adaptations of the bacterium emerge as a spontaneous outcome of optimizing the balance between the chromatophore's structural integrity and robust energy conversion. Parallels are drawn with the more universal mitochondrial bioenergetic machinery, from whence molecular-scale insights into the mechanism of cellular aging are inferred. Together, our integrative method and spectroscopic experiments pave the way to first-principles modeling of whole living cells.

TOR, the Gateway to Cellular Metabolism, Cell Growth, and Disease.

Michael N. Hall is this year's recipient of the Lasker Basic Medical Research Award for the identification of the target of rapamycin, TOR. TOR is a master regulator of the cell's growth and metabolic state, and its dysregulation contributes to a variety of diseases, including diabetes, obesity, neurodegenerative disorders, aging, and cancer, making the TOR pathway an attractive therapeutic target.

Design and Analysis of Single-Cell Sequencing Experiments.

Recent advances in single-cell sequencing hold great potential for exploring biological systems with unprecedented resolution. Sequencing the genome of individual cells can reveal somatic mutations and allows the investigation of clonal dynamics. Single-cell transcriptome sequencing can elucidate the cell type composition of a sample. However, single-cell sequencing comes with major technical challenges and yields complex data output. In this Primer, we provide an overview of available methods and discuss experimental design and single-cell data analysis. We hope that these guidelines will enable a growing number of researchers to leverage the power of single-cell sequencing.

Cell-type-directed design of synthetic enhancers.

Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes1. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Here we show that deep learning models2-6, can be used to efficiently design synthetic, cell-type-specific enhancers, starting from random sequences, and that this optimization process allows detailed tracing of enhancer features at single-nucleotide resolution. We evaluate the function of fully synthetic enhancers to specifically target Kenyon cells or glial cells in the fruit fly brain using transgenic animals. We further exploit enhancer design to create 'dual-code' enhancers that target two cell types and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the state space searches towards local optima, we characterize enhancer codes through the strength, combination and arrangement of transcription factor activator and transcription factor repressor motifs. Finally, we apply the same strategies to successfully design human enhancers, which adhere to enhancer rules similar to those of Drosophila enhancers. Enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.

Bridging structural and cell biology with cryo-electron microscopy.

Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.

Sex differences orchestrated by androgens at single-cell resolution.

Sex differences in mammalian complex traits are prevalent and are intimately associated with androgens1-7. However, a molecular and cellular profile of sex differences and their modulation by androgens is still lacking. Here we constructed a high-dimensional single-cell transcriptomic atlas comprising over 2.3 million cells from 17 tissues in Mus musculus and explored the effects of sex and androgens on the molecular programs and cellular populations. In particular, we found that sex-biased immune gene expression and immune cell populations, such as group 2 innate lymphoid cells, were modulated by androgens. Integration with the UK Biobank dataset revealed potential cellular targets and risk gene enrichment in antigen presentation for sex-biased diseases. This study lays the groundwork for understanding the sex differences orchestrated by androgens and provides important evidence for targeting the androgen pathway as a broad therapeutic strategy for sex-biased diseases.

Chemical Principles in Tissue Clearing and Staining Protocols for Whole-Body Cell Profiling.

Mammalian bodies have more than a billion cells per cubic centimeter, which makes whole-body cell (WBC) profiling of an organism one of the ultimate challenges in biology and medicine. Recent advances in tissue-clearing technology have enabled rapid and comprehensive cellular analyses in whole organs and in the whole body by a combination of state-of-the-art technologies of optical imaging and image informatics. In this review, we focus mainly on the chemical principles in currently available techniques for tissue clearing and staining to facilitate our understanding of their underlying mechanisms. Tissue clearing is usually conducted by the following steps: (a) fixation, (b) permeabilization, (c) decolorizing, and (d) refractive index (RI) matching. To phenotype individual cells after tissue clearing, it is important to visualize genetically encoded fluorescent reporters and/or to stain tissues with fluorescent dyes, fluorescent labeled antibodies, or nucleic acid probes. Although some technical challenges remain, the chemical principles in tissue clearing and staining for WBC profiling will enable various applications, such as identifying cellular circuits across multiple organs and measuring their dynamics in stochastic and proliferative cellular processes, for example, autoimmune and malignant neoplastic diseases.

Cell Competition: Mechanisms and Physiological Roles.

Cell-competitive interactions are widespread in nature and determine the outcome of a vast variety of biological processes. A particular class of competitive interactions takes place when alterations in intrinsic cellular properties are sensed nonautonomously by comparison between neighboring cells, resulting in the selective elimination of one cell population. This type of cell competition was first described four decades ago in developing epithelia of Drosophila. In the last 15 years, further molecular and cellular analyses have provided essential knowledge about the mechanisms, universality, and physiological relevance of cell competition. The two main phenomena triggering cell competition are alterations in cellular metabolic status and alterations in epithelial apico-basal polarity, while other reported pathways are less characterized. Cell competition plays essential roles in quality control, homeostasis, and repair of developing and adult tissues, and depending on the context, it may function as a tumor-suppressing or tumor-promoting mechanism.

Transcriptional Control of Developmental Cell Behaviors.

Tissue-specific transcription regulators emerged as key developmental control genes, which operate in the context of complex gene regulatory networks (GRNs) to coordinate progressive cell fate specification and tissue morphogenesis. We discuss how GRNs control the individual cell behaviors underlying complex morphogenetic events. Cell behaviors classically range from mesenchymal cell motility to cell shape changes in epithelial sheets. These behaviors emerge from the tissue-specific, multiscale integration of the local activities of universal and pleiotropic effectors, which underlie modular subcellular processes including cytoskeletal dynamics, cell-cell and cell-matrix adhesion, signaling, polarity, and vesicle trafficking. Extrinsic cues and intrinsic cell competence determine the subcellular spatiotemporal patterns of effector activities. GRNs influence most subcellular activities by controlling only a fraction of the effector-coding genes, which we argue is enriched in effectors involved in reading and processing the extrinsic cues to contextualize intrinsic subcellular processes and canalize developmental cell behaviors. The properties of the transcription-cell behavior interface have profound implications for evolution and disease.

Metabolic control of autophagy.

Macroautophagy (herein referred to as autophagy) is an evolutionarily conserved mechanism of adaptation to adverse microenvironmental conditions, including limited nutrient supplies. Several sensors interacting with the autophagic machinery have evolved to detect fluctuations in key metabolic parameters. The signal transduction cascades operating downstream of these sensors are highly interconnected to control a spatially and chronologically coordinated autophagic response that maintains the health and function of individual cells while preserving organismal homeostasis. Here, we discuss the physiological regulation of autophagy by metabolic circuitries, as well as alterations of such control in disease.

H3K4me3 breadth is linked to cell identity and transcriptional consistency.

Trimethylation of histone H3 at lysine 4 (H3K4me3) is a chromatin modification known to mark the transcription start sites of active genes. Here, we show that H3K4me3 domains that spread more broadly over genes in a given cell type preferentially mark genes that are essential for the identity and function of that cell type. Using the broadest H3K4me3 domains as a discovery tool in neural progenitor cells, we identify novel regulators of these cells. Machine learning models reveal that the broadest H3K4me3 domains represent a distinct entity, characterized by increased marks of elongation. The broadest H3K4me3 domains also have more paused polymerase at their promoters, suggesting a unique transcriptional output. Indeed, genes marked by the broadest H3K4me3 domains exhibit enhanced transcriptional consistency and [corrected] increased transcriptional levels, and perturbation of H3K4me3 breadth leads to changes in transcriptional consistency. Thus, H3K4me3 breadth contains information that could ensure transcriptional precision at key cell identity/function genes.

Single-cell phenotyping within transparent intact tissue through whole-body clearing.

Understanding the structure-function relationships at cellular, circuit, and organ-wide scale requires 3D anatomical and phenotypical maps, currently unavailable for many organs across species. At the root of this knowledge gap is the absence of a method that enables whole-organ imaging. Herein, we present techniques for tissue clearing in which whole organs and bodies are rendered macromolecule-permeable and optically transparent, thereby exposing their cellular structure with intact connectivity. We describe PACT (passive clarity technique), a protocol for passive tissue clearing and immunostaining of intact organs; RIMS (refractive index matching solution), a mounting media for imaging thick tissue; and PARS (perfusion-assisted agent release in situ), a method for whole-body clearing and immunolabeling. We show that in rodents PACT, RIMS, and PARS are compatible with endogenous-fluorescence, immunohistochemistry, RNA single-molecule FISH, long-term storage, and microscopy with cellular and subcellular resolution. These methods are applicable for high-resolution, high-content mapping and phenotyping of normal and pathological elements within intact organs and bodies.

Integrating biological redesign: where synthetic biology came from and where it needs to go.

Synthetic biology seeks to extend approaches from engineering and computation to redesign of biology, with goals such as generating new chemicals, improving human health, and addressing environmental issues. Early on, several guiding principles of synthetic biology were articulated, including design according to specification, separation of design from fabrication, use of standardized biological parts and organisms, and abstraction. We review the utility of these principles over the past decade in light of the field's accomplishments in building complex systems based on microbial transcription and metabolism and describe the progress in mammalian cell engineering.

A DNA methylation atlas of normal human cell types.

DNA methylation is a fundamental epigenetic mark that governs gene expression and chromatin organization, thus providing a window into cellular identity and developmental processes1. Current datasets typically include only a fraction of methylation sites and are often based either on cell lines that underwent massive changes in culture or on tissues containing unspecified mixtures of cells2-5. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing, allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell type are more than 99.5% identical, demonstrating the robustness of cell identity programmes to environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny and identifies methylation patterns retained since embryonic development. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hypermethylated loci are rare and are enriched for CpG islands, Polycomb targets and CTCF binding sites, suggesting a new role in shaping cell-type-specific chromatin looping. The atlas provides an essential resource for study of gene regulation and disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.

Ångström-resolution fluorescence microscopy.

Fluorescence microscopy, with its molecular specificity, is one of the major characterization methods used in the life sciences to understand complex biological systems. Super-resolution approaches1-6 can achieve resolution in cells in the range of 15 to 20 nm, but interactions between individual biomolecules occur at length scales below 10 nm and characterization of intramolecular structure requires Ångström resolution. State-of-the-art super-resolution implementations7-14 have demonstrated spatial resolutions down to 5 nm and localization precisions of 1 nm under certain in vitro conditions. However, such resolutions do not directly translate to experiments in cells, and Ångström resolution has not been demonstrated to date. Here we introdue a DNA-barcoding method, resolution enhancement by sequential imaging (RESI), that improves the resolution of fluorescence microscopy down to the Ångström scale using off-the-shelf fluorescence microscopy hardware and reagents. By sequentially imaging sparse target subsets at moderate spatial resolutions of >15 nm, we demonstrate that single-protein resolution can be achieved for biomolecules in whole intact cells. Furthermore, we experimentally resolve the DNA backbone distance of single bases in DNA origami with Ångström resolution. We use our method in a proof-of-principle demonstration to map the molecular arrangement of the immunotherapy target CD20 in situ in untreated and drug-treated cells, which opens possibilities for assessing the molecular mechanisms of targeted immunotherapy. These observations demonstrate that, by enabling intramolecular imaging under ambient conditions in whole intact cells, RESI closes the gap between super-resolution microscopy and structural biology studies and thus delivers information key to understanding complex biological systems.

Extracting insight from noisy cellular networks.

Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched.

Encoding and decoding cellular information through signaling dynamics.

A growing number of studies are revealing that cells can send and receive information by controlling the temporal behavior (dynamics) of their signaling molecules. In this Review, we discuss what is known about the dynamics of various signaling networks and their role in controlling cellular responses. We identify general principles that are emerging in the field, focusing specifically on how the identity and quantity of a stimulus is encoded in temporal patterns, how signaling dynamics influence cellular outcomes, and how specific dynamical patterns are both shaped and interpreted by the structure of molecular networks. We conclude by discussing potential functional roles for transmitting cellular information through the dynamics of signaling molecules and possible applications for the treatment of disease.

Using optogenetics to interrogate the dynamic control of signal transmission by the Ras/Erk module.

The complex, interconnected architecture of cell-signaling networks makes it challenging to disentangle how cells process extracellular information to make decisions. We have developed an optogenetic approach to selectively activate isolated intracellular signaling nodes with light and use this method to follow the flow of information from the signaling protein Ras. By measuring dose and frequency responses in single cells, we characterize the precision, timing, and efficiency with which signals are transmitted from Ras to Erk. Moreover, we elucidate how a single pathway can specify distinct physiological outcomes: by combining distinct temporal patterns of stimulation with proteomic profiling, we identify signaling programs that differentially respond to Ras dynamics, including a paracrine circuit that activates STAT3 only after persistent (>1 hr) Ras activation. Optogenetic stimulation provides a powerful tool for analyzing the intrinsic transmission properties of pathway modules and identifying how they dynamically encode distinct outcomes.