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.

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.

The free energy landscape of small-world networks of cells.

The properties of organs, tissues, organoids, and other systems of cells, are influenced by the spatial localization and distribution of their elements. Here, we used networks to describe distributions of cells on a surface where the small-world coefficient (SW) of the networks was varied between SW~1 (random uniform distributions) and SW~10 (clustered distributions). The small-world coefficient is a topological measure of graphs: networks with SW>1 are topologically biased to transmit information. For each system configuration, we then determined the total energy U as the sum of the energies that describe cell-cell interactions - approximated by a harmonic potential. The graph of energy (U) across the configuration space of the networks (SW) is the energy landscape: it indicates which configuration a system of cells will likely assume over time. We found that, depending on the model parameters, the energy landscapes of 2D distributions of cells may be of different types: from type I to type IV. Type I and type II systems have high probability to evolve into random distributions. Type III and type IV systems have a higher probability to form clustered architectures. A great many of simulations indicated that cultures of cells with high initial density and limited sensing range could evolve into clustered configurations with enhanced topological characteristics. Moreover, the strongest the binding between cells, the greater the likelihood that they will assume configurations characterized by finite values of SW. Results of the work are relevant for those working the field of tissue engineering, regenerative medicine, the formation of in-vitro-models, the analysis of neuro-degenerative diseases.

The regulatory effect of growth differentiation factor 11 on different cells.

Growth differentiation factor 11 (GDF11) is one of the important factors in the pathophysiological process of animals. It is widely expressed in many tissues and organs of animals, showing its wide biological activity and potential application value. Previous research has demonstrated that GDF11 has a therapeutic effect on various diseases, such as anti-myocardial aging and anti-tumor. This has not only sparked intense interest and enthusiasm among academics but also spurred some for-profit businesses to attempt to develop GDF11 as a medication for regenerative medicine or anti-aging application. Currently, Sotatercept, a GDF11 antibody drug, is in the marketing application stage, and HS-235 and rGDF11 are in the preclinical research stage. Therefore, we believe that figuring out which cells GDF11 acts on and its current problems should be an important issue in the scientific and commercial communities. Only through extensive, comprehensive research and discussion can we better understand the role and potential of GDF11, while avoiding unnecessary risks and misinformation. In this review, we aimed to summarize the role of GDF11 in different cells and its current controversies and challenges, providing an important reference for us to deeply understand the function of GDF11 and formulate more effective treatment strategies in the future.

Discrimination of Multidrug Resistance in Cancer Cells Achieved Using Single-Cell Analysis.

The biophysical signatures of single cells, such as multidrug resistance (MDR), may easily change during their various disease states. Therefore, there is an ever-growing need for advanced methods to study and analyze the response of cancer cells to therapeutic intervention. To determine the cancer cells and responses to various cancer therapies, from a cell mortality perspective, we report a label-free and real-time method to monitor the in situ responses of ovarian cancer cells using a single-cell bioanalyzer (SCB). The SCB instrument was used to detect different ovarian cancer cells, such as NCI/ADR-RES cells, which are multidrug resistant (MDR), and non-MDR OVCAR-8 cells. The discrimination of ovarian cells has been achieved at the single-cell level by measuring drug accumulation quantitatively in real time, in which the accumulation is high in non-MDR single cells without drug efflux but is low in MDR single cells which are not efflux-free. The SCB was constructed as an inverted microscope for optical imaging and fluorescent measurement of a single cell that was retained in a microfluidic chip. The single ovarian cancer cell retained in the chip offered sufficient fluorescent signals for the SCB to measure the accumulation of daunorubicin (DNR) in the single cell in the absence of cyclosporine A (CsA). The same cell allows us to detect the enhanced drug accumulation due to MDR modulation in the presence of CsA, which is the MDR inhibitor. The measurement of drug accumulation in a cell was achieved after it was captured in the chip for one hour, with the correction of background interference. The detection of accumulation enhancement due to MDR modulation by CsA was determined in terms of either the accumulation rate or enhanced concentration of DNR in the single cell (same cell, p < 0.01). It showed that with the effectiveness of efflux blocking by CsA, the intracellular DNR concentration in a single cell increased by threefold against its same cell control. This single-cell bioanalyzer instrument has the ability to discriminate MDR in different ovarian cells due to drug efflux in them by eliminating the interference of background fluorescence and by using the same cell control.

A histone deacetylase 3 and mitochondrial complex I axis regulates toxic formaldehyde production.

Cells produce considerable genotoxic formaldehyde from an unknown source. We carry out a genome-wide CRISPR-Cas9 genetic screen in metabolically engineered HAP1 cells that are auxotrophic for formaldehyde to find this cellular source. We identify histone deacetylase 3 (HDAC3) as a regulator of cellular formaldehyde production. HDAC3 regulation requires deacetylase activity, and a secondary genetic screen identifies several components of mitochondrial complex I as mediators of this regulation. Metabolic profiling indicates that this unexpected mitochondrial requirement for formaldehyde detoxification is separate from energy generation. HDAC3 and complex I therefore control the abundance of a ubiquitous genotoxic metabolite.

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.

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.

Direct observation of motor protein stepping in living cells using MINFLUX.

Dynamic measurements of molecular machines can provide invaluable insights into their mechanism, but these measurements have been challenging in living cells. Here, we developed live-cell tracking of single fluorophores with nanometer spatial and millisecond temporal resolution in two and three dimensions using the recently introduced super-resolution technique MINFLUX. Using this approach, we resolved the precise stepping motion of the motor protein kinesin-1 as it walked on microtubules in living cells. Nanoscopic tracking of motors walking on the microtubules of fixed cells also enabled us to resolve the architecture of the microtubule cytoskeleton with protofilament resolution.

Network expansion of genetic associations defines a pleiotropy map of human cell biology.

Interacting proteins tend to have similar functions, influencing the same organismal traits. Interaction networks can be used to expand the list of candidate trait-associated genes from genome-wide association studies. Here, we performed network-based expansion of trait-associated genes for 1,002 human traits showing that this recovers known disease genes or drug targets. The similarity of network expansion scores identifies groups of traits likely to share an underlying genetic and biological process. We identified 73 pleiotropic gene modules linked to multiple traits, enriched in genes involved in processes such as protein ubiquitination and RNA processing. In contrast to gene deletion studies, pleiotropy as defined here captures specifically multicellular-related processes. We show examples of modules linked to human diseases enriched in genes with known pathogenic variants that can be used to map targets of approved drugs for repurposing. Finally, we illustrate the use of network expansion scores to study genes at inflammatory bowel disease genome-wide association study loci, and implicate inflammatory bowel disease-relevant genes with strong functional and genetic support.

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.

The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans.

Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. Using multiple tissues from a single donor enabled identification of the clonal distribution of T cells between tissues, identification of the tissue-specific mutation rate in B cells, and analysis of the cell cycle state and proliferative potential of shared cell types across tissues. Cell type-specific RNA splicing was discovered and analyzed across tissues within an individual.

PCGA: a comprehensive web server for phenotype-cell-gene association analysis.

Most complex disease-associated loci mapped by genome-wide association studies (GWAS) are located in non-coding regions. It remains elusive which genes the associated loci regulate and in which tissues/cell types the regulation occurs. Here, we present PCGA (https://pmglab.top/pcga), a comprehensive web server for jointly estimating both associated tissues/cell types and susceptibility genes for complex phenotypes by GWAS summary statistics. The web server is built on our published method, DESE, which represents an effective method to mutually estimate driver tissues and genes by integrating GWAS summary statistics and transcriptome data. By collecting and processing extensive bulk and single-cell RNA sequencing datasets, PCGA has included expression profiles of 54 human tissues, 2,214 human cell types and 4,384 mouse cell types, which provide the basis for estimating associated tissues/cell types and genes for complex phenotypes. We develop a framework to sequentially estimate associated tissues and cell types of a complex phenotype according to their hierarchical relationships we curated. Meanwhile, we construct a phenotype-cell-gene association landscape by estimating the associated tissues/cell types and genes of 1,871 public GWASs. The association landscape is generally consistent with biological knowledge and can be searched and browsed at the PCGA website.

Electrogenetics: Bridging synthetic biology and electronics to remotely control the behavior of mammalian designer cells.

Electrogenetics, the combination of electronics and genetics, is an emerging field of mammalian synthetic biology in which electrostimulation is used to remotely program user-designed genetic elements within designer cells to generate desired outputs. Here, we describe recent advances in electro-induced therapeutic gene expression and therapeutic protein secretion in engineered mammalian cells. We also review available tools and strategies to engineer electro-sensitive therapeutic designer cells that are able to sense electrical pulses and produce appropriate clinically relevant outputs in response. We highlight current limitations facing mammalian electrogenetics and suggest potential future directions for research.

Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data.

Mapping cell types across a tissue is a central concern of spatial biology, but cell type abundance is difficult to extract from spatial gene expression data. We introduce SpatialDecon, an algorithm for quantifying cell populations defined by single cell sequencing within the regions of spatial gene expression studies. SpatialDecon incorporates several advancements in gene expression deconvolution. We propose an algorithm harnessing log-normal regression and modelling background, outperforming classical least-squares methods. We compile cell profile matrices for 75 tissue types. We identify genes whose minimal expression by cancer cells makes them suitable for immune deconvolution in tumors. Using lung tumors, we create a dataset for benchmarking deconvolution methods against marker proteins. SpatialDecon is a simple and flexible tool for mapping cell types in spatial gene expression studies. It obtains cell abundance estimates that are spatially resolved, granular, and paired with highly multiplexed gene expression data.

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.

SOX9+ enthesis cells are associated with spinal ankylosis in ankylosing spondylitis.

OBJECTIVE: Although cartilage degeneration and invasion of the subchondral bone plate in entheseal lesion has been considered to consequently lead bony ankylosis in ankylosing spondylitis (AS), no evident mechanisms are known. DESIGN: To identify histopathological and physiological changes in enthesitis-related ankylosis in AS, we performed molecular characterization of transcription factors and surface markers, and transcriptome analysis with human tissues. Entheseal tissue containing subchondral bone was obtained from the facet joints of 9 patients with AS and 10 disease controls, and assessed by using differential staining techniques. Enthesis cells were isolated, characterized, stimulated with TNF and/or IL-17A, and analysed by cell-based experimental tools. RESULTS: We found diffusely distributed granular tissue and cartilage in the subchondral bone in AS. Co-expression of SOX9, a specific transcription factor in cartilage, and matrix metalloproteinase 13 (MMP13) was found in the granular tissues within the subchondral bone from AS patients. Intriguingly, SOX9 expression was significantly higher in AS enthesis cells than controls and correlated with TNFR1 and IL-17RA expressions, which is important for high reactivity to TNF and IL-17A cytokines. Co-stimulation by TNF and IL-17A resulted in accelerated mineralization/calcification features, and increased OCN expression in AS enthesis cells. Furthermore, SOX9 overexpression in enthesis leads to promoting mineralization feature by TNF and IL-17A stimuli. Finally, OCN expression is elevated in the destructive enthesis of advanced AS. CONCLUSION: These findings provide insight into the links between inflammation and the mineralization of entheseal tissue as the initiation of spinal ankylosis, emphasizing the importance of SOX9+ enthesis cells.