Enhancer-promoter interactions are reconfigured through the formation of long-range multiway hubs as mouse ES cells exit pluripotency.

Enhancers bind transcription factors, chromatin regulators, and non-coding transcripts to modulate the expression of target genes. Here, we report 3D genome structures of single mouse ES cells as they are induced to exit pluripotency and transition through a formative stage prior to undergoing neuroectodermal differentiation. We find that there is a remarkable reorganization of 3D genome structure where inter-chromosomal intermingling increases dramatically in the formative state. This intermingling is associated with the formation of a large number of multiway hubs that bring together enhancers and promoters with similar chromatin states from typically 5-8 distant chromosomal sites that are often separated by many Mb from each other. In the formative state, genes important for pluripotency exit establish contacts with emerging enhancers within these multiway hubs, suggesting that the structural changes we have observed may play an important role in modulating transcription and establishing new cell identities.

Fluctuations in p53 Signaling Allow Escape from Cell-Cycle Arrest.

Biological signals need to be robust and filter small fluctuations yet maintain sensitivity to signals across a wide range of magnitudes. Here, we studied how fluctuations in DNA damage signaling relate to maintenance of long-term cell-cycle arrest. Using live-cell imaging, we quantified division profiles of individual human cells in the course of 1 week after irradiation. We found a subset of cells that initially establish cell-cycle arrest and then sporadically escape and divide. Using fluorescent reporters and mathematical modeling, we determined that fluctuations in the oscillatory pattern of the tumor suppressor p53 trigger a sharp switch between p21 and CDK2, leading to escape from arrest. Transient perturbation of p53 stability mimicked the noise in individual cells and was sufficient to trigger escape from arrest. Our results show that the self-reinforcing circuitry that mediates cell-cycle transitions can translate small fluctuations in p53 signaling into large phenotypic changes.

Single Live Cell Monitoring of Protein Turnover Reveals Intercellular Variability and Cell-Cycle Dependence of Degradation Rates.

Cells need to reliably control their proteome composition to maintain homeostasis and regulate growth. How protein synthesis and degradation interplay to control protein expression levels remains unclear. Here, we combined a tandem fluorescent timer and pulse-chase protein labeling to disentangle how protein synthesis and degradation control protein homeostasis in single live mouse embryonic stem cells. We discovered substantial cell-cycle dependence in protein synthesis rates and stabilization of a large number of proteins around cytokinesis. Protein degradation rates were highly variable between cells, co-varied within individual cells for different proteins, and were positively correlated with synthesis rates. This suggests variability in proteasome activity as an important source of global extrinsic noise in gene expression. Our approach paves the way toward understanding the complex interplay of synthesis and degradation processes in determining protein levels of individual mammalian cells.

Automated and reproducible cell identification in mass cytometry using neural networks.

The principal use of mass cytometry is to identify distinct cell types and changes in their composition, phenotype and function in different samples and conditions. Combining data from different studies has the potential to increase the power of these discoveries in diverse fields such as immunology, oncology and infection. However, current tools are lacking in scalable, reproducible and automated methods to integrate and study data sets from mass cytometry that often use heterogenous approaches to study similar samples. To address these limitations, we present two novel developments: (1) a pre-trained cell identification model named Immunopred that allows automated identification of immune cells without user-defined prior knowledge of expected cell types and (2) a fully automated cytometry meta-analysis pipeline built around Immunopred. We evaluated this pipeline on six COVID-19 study data sets comprising 270 unique samples and uncovered novel significant phenotypic changes in the wider immune landscape of COVID-19 that were not identified when each study was analyzed individually. Applied widely, our approach will support the discovery of novel findings in research areas where cytometry data sets are available for integration.

High-Precision Single-Cell microRNA Therapy by a Functional Nanopipette with Sensitive Photoelectrochemical Feedback.

This work proposes the concept of single-cell microRNA (miR) therapy and proof-of-concept by engineering a nanopipette for high-precision miR-21-targeted therapy in a single HeLa cell with sensitive photoelectrochemical (PEC) feedback. Targeting the representative oncogenic miR-21, the as-functionalized nanopipette permits direct intracellular drug administration with precisely controllable dosages, and the corresponding therapeutic effects can be sensitively transduced by a PEC sensing interface that selectively responds to the indicator level of cytosolic caspase-3. The experimental results reveal that injection of ca. 4.4 × 10-20 mol miR-21 inhibitor, i.e., 26488 copies, can cause the obvious therapeutic action in the targeted cell. This work features a solution to obtain the accurate knowledge of how a certain miR-drug with specific dosages treats the cells and thus provides an insight into futuristic high-precision clinical miR therapy using personalized medicine, provided that the prerequisite single-cell experiments are courses of personalized customization.

Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel.

Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited in proteomic depth, throughput, and robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated and complete dimethyl labeling of bulk or single-cell samples, without losing proteomic depth. Lys-N digestion enables five-plex quantification at MS1 and MS2 level. Because the multiplexed channels are quantitatively isolated from each other, mDIA accommodates a reference channel that does not interfere with the target channels. Our algorithm RefQuant takes advantage of this and confidently quantifies twice as many proteins per single cell compared to our previous work (Brunner et al, PMID 35226415), while our workflow currently allows routine analysis of 80 single cells per day. Finally, we combined mDIA with spatial proteomics to increase the throughput of Deep Visual Proteomics seven-fold for microdissection and four-fold for MS analysis. Applying this to primary cutaneous melanoma, we discovered proteomic signatures of cells within distinct tumor microenvironments, showcasing its potential for precision oncology.

SLAM-Drop-seq reveals mRNA kinetic rates throughout the cell cycle.

RNA abundance is tightly regulated in eukaryotic cells by modulating the kinetic rates of RNA production, processing, and degradation. To date, little is known about time­dependent kinetic rates during dynamic processes. Here, we present SLAM­Drop­seq, a method that combines RNA metabolic labeling and alkylation of modified nucleotides in methanol­fixed cells with droplet­based sequencing to detect newly synthesized and preexisting mRNAs in single cells. As a first application, we sequenced 7280 HEK293 cells and calculated gene­specific kinetic rates during the cell cycle using the novel package Eskrate. Of the 377 robust­cycling genes that we identified, only a minor fraction is regulated solely by either dynamic transcription or degradation (6 and 4%, respectively). By contrast, the vast majority (89%) exhibit dynamically regulated transcription and degradation rates during the cell cycle. Our study thus shows that temporally regulated mRNA degradation is fundamental for the correct expression of a majority of cycling genes. SLAM­Drop­seq, combined with Eskrate, is a powerful approach to understanding the underlying mRNA kinetics of single­cell gene expression dynamics in continuous biological processes.

Single-cell response to Wnt signaling activation reveals uncoupling of Wnt target gene expression.

Wnt signaling drives nuclear translocation of ß-catenin and its subsequent association with the DNA-bound TCF/LEF transcription factors, which dictate target gene specificity by recognizing Wnt responsive elements across the genome. ß-Catenin target genes are therefore thought to be collectively activated upon Wnt pathway stimulation. However, this appears in contrast with the non-overlapping patterns of Wnt target gene expression in several contexts, including early mammalian embryogenesis. Here we followed Wnt target gene expression in human embryonic stem cells after Wnt pathway stimulation at a single-cell resolution. Cells changed gene expression program over time consistent with three key developmental events: i) loss of pluripotency, ii) induction of Wnt target genes, and iii) mesoderm specification. Contrary to our expectation, not all cells displayed equal amplitude of Wnt target gene activation; rather, they distributed in a continuum from strong to weak responders when ranked based on the expression of the target AXIN2. Moreover, high AXIN2 did not always correspond to elevated expression of other Wnt targets, which were activated in different proportions in individual cells. The uncoupling of Wnt target gene expression was also identified in single cell transcriptomics profiling of other Wnt-responding cell types, including HEK293T, murine developing forelimbs, and human colorectal cancer. Our finding underlines the necessity to identify additional mechanisms that explain the heterogeneity of the Wnt/ß-catenin-mediated transcriptional outputs in single cells.

Applying single-cell highly multiplexed secretome proteomics to characterize immunotherapeutic products and predict clinical responses.

Genetically and phenotypically identical immune cell populations can be highly heterogenous in terms of their immune functions and protein secretion profiles. The microfluidic chip-based single-cell highly multiplexed secretome proteomics enables characterization of cellular heterogeneity of immune responses at different cellular and molecular layers. Increasing evidence has demonstrated that polyfunctional T cells that simultaneously produce 2+ proteins per cell at the single-cell level are key effector cells that contribute to the development of potent and durable cellular immunity against pathogens and cancers. The functional proteomic technology offers a wide spectrum of cellular function assessment and can uniquely define highly polyfunctional cell subsets with cytokine signatures from live individual cells. This high-dimensional single-cell analysis provides deep dissection into functional heterogeneity and helps identify predictive biomarkers and potential correlates that are crucial for immunotherapeutic product design optimization and personalized immunotherapy development to achieve better clinical outcomes.

Advances and applications of single-cell omics technologies in plant research.

Single-cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high-dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single-cell omics, especially single-cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well-executed benchmarking studies to highlight advances made through the application of single-cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single-cell sequencing with revolutionary perspectives in plant biology.

Molecular-defined clonal evolution in patients with classical myeloproliferative neoplasms.

Classical myeloproliferative neoplasms (MPNs) are characterized by distinct clinical phenotypes. The discovery of driver mutations in JAK2, CALR and MPL genes provided new insights into their pathogenesis. Next-generation sequencing (NGS) identified additional somatic mutations, most frequently in epigenetic modulator genes. In this study, a cohort of 95 MPN patients was genetically characterized using targeted NGS. Clonal hierarchies of detected mutations were subsequently analysed using colony forming progenitor assays derived from single cells to study mutation acquisition. Further, the hierarchy of mutations within distinct cell lineages was evaluated. NGS revealed mutations in three epigenetic modulator genes (TET2, DNMT3A, ASXL1) as most common co-mutations to the classical driver mutations. JAK2V617F as well as DNMT3A and TET2 mutations were detected as primary events in disease formation and most cases presented with a linear mutation pattern. Mutations appear mostly in the myeloid lineages but can also appear in lymphoid subpopulations. In one case with a double mutant MPL gene, mutations exclusively appeared in the monocyte lineage. Overall, this study confirms the mutational heterogeneity of classical MPNs and highlights the role of JAK2V617F and epigenetic modifier genes as early events in hematologic disease formation.

Differentiating single cervical cells by mitochondrial fluorescence imaging and deep learning-based label-free light scattering with multi-modal static cytometry.

Cervical cancer is a high-risk disease that threatens women's health globally. In this study, we developed the multi-modal static cytometry that adopted different features to classify the typical human cervical epithelial cells (H8) and cervical cancer cells (HeLa). With the light-sheet static cytometry, we obtain brightfield (BF) images, fluorescence (FL) images and two-dimensional (2D) light scattering (LS) patterns of single cervical cells. Three feature extraction methods are used to extract multi-modal features based on different data characteristics. Analysis and classification of morphological and textural features demonstrate the potential of intracellular mitochondria in cervical cancer cell classification. The deep learning method is used to automatically extract deep features of label-free LS patterns, and an accuracy of 76.16% for the classification of the above two kinds of cervical cells is obtained, which is higher than the other two single modes (BF and FL). Our multi-modal static cytometry uses a variety of feature extraction and analysis methods to provide the mitochondria as promising internal biomarkers for cervical cancer diagnosis, and to show the promise of label-free, automatic classification of early cervical cancer with deep learning-based 2D light scattering.

Coordination of MAPK and p53 dynamics in the cellular responses to DNA damage and oxidative stress.

In response to different cellular stresses, the transcription factor p53 undergoes different dynamics. p53 dynamics, in turn, control cell fate. However, distinct stresses can generate the same p53 dynamics but different cell fate outcomes, suggesting integration of dynamic information from other pathways is important for cell fate regulation. To determine how MAPK activities affect p53-mediated responses to DNA breaks and oxidative stress, we simultaneously tracked p53 and either ERK, JNK, or p38 activities in single cells. While p53 dynamics were comparable between the stresses, cell fate outcomes were distinct. Combining MAPK dynamics with p53 dynamics was important for distinguishing between the stresses and for generating temporal ordering of cell fate pathways. Furthermore, cross-talk between MAPKs and p53 controlled the balance between proliferation and cell death. These findings provide insight into how cells integrate signaling pathways with distinct temporal patterns of activity to encode stress specificity and drive different cell fate decisions.

Increasing resolution in stress neurobiology: from single cells to complex group behaviors.

Stress can have severe psychological and physiological consequences. Thus, inappropriate regulation of the stress response is linked to the etiology of mood and anxiety disorders. The generation and implementation of preclinical animal models represent valuable tools to explore and characterize the mechanisms underlying the pathophysiology of stress-related psychiatric disorders and the development of novel pharmacological strategies. In this commentary, we discuss the strengths and limitations of state-of-the-art molecular and computational advances employed in stress neurobiology research, with a focus on the ever-increasing spatiotemporal resolution in cell biology and behavioral science. Finally, we share our perspective on future directions in the fields of preclinical and human stress research.

Striking heterogeneity of somatic L1 retrotransposition in single normal and cancerous gastrointestinal cells.

Somatic LINE-1 (L1) retrotransposition has been detected in early embryos, adult brains, and the gastrointestinal (GI) tract, and many cancers, including epithelial GI tumors. We previously found numerous somatic L1 insertions in paired normal and GI cancerous tissues. Here, using a modified method of single-cell analysis for somatic L1 insertions, we studied adenocarcinomas of colon, pancreas, and stomach, and found a variable number of somatic L1 insertions in tumors of the same type from patient to patient. We detected no somatic L1 insertions in single cells of 5 of 10 tumors studied. In three tumors, aneuploid cells were detected by FACS. In one pancreatic tumor, there were many more L1 insertions in aneuploid than in euploid tumor cells. In one gastric cancer, both aneuploid and euploid cells contained large numbers of likely clonal insertions. However, in a second gastric cancer with aneuploid cells, no somatic L1 insertions were found. We suggest that when the cellular environment is favorable to retrotransposition, aneuploidy predisposes tumor cells to L1 insertions, and retrotransposition may occur at the transition from euploidy to aneuploidy. Seventeen percent of insertions were also present in normal cells, similar to findings in genomic DNA from normal tissues of GI tumor patients. We provide evidence that: 1) The number of L1 insertions in tumors of the same type is highly variable, 2) most somatic L1 insertions in GI cancer tissues are absent from normal tissues, and 3) under certain conditions, somatic L1 retrotransposition exhibits a propensity for occurring in aneuploid cells.

The Bladder Tumor Microenvironment Components That Modulate the Tumor and Impact Therapy.

The tumor microenvironment (TME) is complex and involves many different cell types that seemingly work together in helping cancer cells evade immune monitoring and survive therapy. The advent of single-cell sequencing has greatly increased our knowledge of the cell types present in the tumor microenvironment and their role in the developing cancer. This, coupled with clinical data showing that cancer development and the response to therapy may be influenced by drugs that indirectly influence the tumor environment, highlights the need to better understand how the cells present in the TME work together. This review looks at the different cell types (cancer cells, cancer stem cells, endothelial cells, pericytes, adipose cells, cancer-associated fibroblasts, and neuronal cells) in the bladder tumor microenvironment. Their impact on immune activation and on shaping the microenvironment are discussed as well as the effects of hypertensive drugs and anesthetics on bladder cancer.

Impact of Sample Preparation Methods on Single-Cell X-ray Microscopy and Light Elemental Analysis Evaluated by Combined Low Energy X-ray Fluorescence, STXM and AFM.

BACKGROUND: Although X-ray fluorescence microscopy is becoming a widely used technique for single-cell analysis, sample preparation for this microscopy remains one of the main challenges in obtaining optimal conditions for the measurements in the X-ray regime. The information available to researchers on sample treatment is inadequate and unclear, sometimes leading to wasted time and jeopardizing the experiment's success. Many cell fixation methods have been described, but none of them have been systematically tested and declared the most suitable for synchrotron X-ray microscopy. METHODS: The HEC-1-A endometrial cells, human spermatozoa, and human embryonic kidney (HEK-293) cells were fixed with organic solvents and cross-linking methods: 70% ethanol, 3.7%, and 2% paraformaldehyde; in addition, HEK-293 cells were subjected to methanol/ C3H6O treatment and cryofixation. Fixation methods were compared by coupling low-energy X-ray fluorescence with scanning transmission X-ray microscopy and atomic force microscopy. RESULTS: Organic solvents lead to greater dehydration of cells, which has the most significant effect on the distribution and depletion of diffusion elements. Paraformaldehyde provides robust and reproducible data. Finally, the cryofixed cells provide the best morphology and element content results. CONCLUSION: Although cryofixation seems to be the most appropriate method as it allows for keeping cells closer to physiological conditions, it has some technical limitations. Paraformaldehyde, when used at the average concentration of 3.7%, is also an excellent alternative for X-ray microscopy.

Electrochemical Single-Cell Protein Therapeutics Using a Double-Barrel Nanopipette.

Single-cell protein therapeutics is expected to promote our in-depth understanding of how a specific protein with a therapeutic dosage treats the cell without population averaging. However, it has not yet been tackled by current single-cell nanotools. We address this challenge by the use of a double-barrel nanopipette, in which one lumen was used for electroosmotic cytosolic protein delivery and the other was customized for ionic evaluation of the consequence. Upon injection of protein DJ-1 through the delivery lumen, upregulation of the antioxidant protein could protect neural PC-12 cells against oxidative stress from phorbol myristate acetate exposure, as deduced by targeting of the cytosolic hydrogen peroxide by the detecting lumen. The nanotool developed in this study for single-cell protein therapeutics provides a perspective for future single-cell therapeutics involving different therapeutic modalities, such as peptides, enzymes and nucleic acids.

Neuro-mesodermal progenitors (NMPs): a comparative study between pluripotent stem cells and embryo-derived populations.

The mammalian embryo's caudal lateral epiblast (CLE) harbours bipotent progenitors, called neural mesodermal progenitors (NMPs), that contribute to the spinal cord and the paraxial mesoderm throughout axial elongation. Here, we performed a single cell analysis of different in vitro NMP populations produced either from embryonic stem cells (ESCs) or epiblast stem cells (EpiSCs) and compared them with E8.25 CLE mouse embryos. In our analysis of this region, our findings challenge the notion that NMPs can be defined by the exclusive co-expression of Sox2 and T at mRNA level. We analyse the in vitro NMP-like populations using a purpose-built support vector machine (SVM) based on the embryo CLE and use it as a classification model to compare the in vivo and in vitro populations. Our results show that NMP differentiation from ESCs leads to heterogeneous progenitor populations with few NMP-like cells, as defined by the SVM algorithm, whereas starting with EpiSCs yields a high proportion of cells with the embryo NMP signature. We find that the population from which the Epi-NMPs are derived in culture contains a node-like population, which suggests that this population probably maintains the expression of T in vitro and thereby a source of NMPs. In conclusion, differentiation of EpiSCs into NMPs reproduces events in vivo and suggests a sequence of events for the emergence of the NMP population.

Inkjet-Patterned Microdroplets as Individual Microenvironments for Adherent Single Cell Culture.

Adhesion of single cells is the foundation of manifold cellular behaviors and life processes. However, investigating the function of a specific cell is still challenging due to deficiency of adhesion or interference from surrounding cells. Herein, an open microfluidic system is reported for culturing adherent single cells, implemented by a micrometer-scale droplet matrix on an inkjet-printed polylysine template. The target cells are isolated from any cell from other droplets, and their adhesion strength is determined to be comparable to conventional petri dishes via an in-situ investigation with a microfluidic extractor. On this proposed platform, isolated single cells are observed to display an entirely distinct spreading behavior featuring total absence of elongation, indicating drastic cell behavior change from their "singleness." This system has high versatility and compatibility for various assaying methods, assuring a promising potential in detailed single cell behavior and cell heterogeneity studies.