Involvement of N4BP2L1, PLEKHA4, and BEGAIN genes in breast cancer and muscle cell development.

Patients with breast cancer show altered expression of genes within the pectoralis major skeletal muscle cells of the breast. Through analyses of The Cancer Genome Atlas (TCGA)-breast cancer (BRCA), we identified three previously uncharacterized putative novel tumor suppressor genes expressed in normal muscle cells, whose expression was downregulated in breast tumors. We found that NEDD4 binding protein 2-like 1 (N4BP2L1), pleckstrin homology domain-containing family A member 4 (PLEKHA4), and brain-enriched guanylate kinase-associated protein (BEGAIN) that are normally highly expressed in breast myoepithelial cells and smooth muscle cells were significantly downregulated in breast tumor tissues of a cohort of 50 patients with this cancer. Our data revealed that the low expression of PLEKHA4 in patients with menopause below 50 years correlated with a higher risk of breast cancer. Moreover, we identified N4BP2L1 and BEGAIN as potential biomarkers of HER2-positive breast cancer. Furthermore, low BEGAIN expression in breast cancer patients with blood fat, heart problems, and diabetes correlated with a higher risk of this cancer. In addition, protein and RNA expression analysis of TCGA-BRCA revealed N4BP2L1 as a promising diagnostic protein biomarker in breast cancer. In addition, the in silico data of scRNA-seq showed high expression of these genes in several cell types of normal breast tissue, including breast myoepithelial cells and smooth muscle cells. Thus, our results suggest their possible tumor-suppressive function in breast cancer and muscle development.

Bridging tissue repair and epithelial carcinogenesis: epigenetic memory and field cancerization.

The epigenome coordinates spatial-temporal specific gene expression during development and in adulthood, for the maintenance of homeostasis and upon tissue repair. The upheaval of the epigenetic landscape is a key event in the onset of many pathologies including tumours, where epigenetic changes cooperate with genetic aberrations to establish the neoplastic phenotype and to drive cell plasticity during its evolution. DNA methylation, histone modifiers and readers or other chromatin components are indeed often altered in cancers, such as carcinomas that develop in epithelia. Lining the surfaces and the cavities of our body and acting as a barrier from the environment, epithelia are frequently subjected to acute or chronic tissue damages, such as mechanical injuries or inflammatory episodes. These events can activate plasticity mechanisms, with a deep impact on cells' epigenome. Despite being very effective, tissue repair mechanisms are closely associated with tumour onset. Here we review the similarities between tissue repair and carcinogenesis, with a special focus on the epigenetic mechanisms activated by cells during repair and opted by carcinoma cells in multiple epithelia. Moreover, we discuss the recent findings on inflammatory and wound memory in epithelia and describe the epigenetic modifications that characterise them. Finally, as wound memory in epithelial cells promotes carcinogenesis, we highlight how it represents an early step for the establishment of field cancerization.

3plex enables deep computational investigation of triplex forming lncRNAs.

Long non-coding RNAs (lncRNAs) regulate gene expression through different molecular mechanisms, including DNA binding via the formation of RNA:DNA:DNA triple helices (TPXs). Despite the increasing amount of experimental evidence, TPXs investigation remains challenging. Here we present 3plex, a software able to predict TPX interactions in silico. Given an RNA sequence and a set of DNA sequences, 3plex integrates 1) Hoogsteen pairing rules that describe the biochemical interactions between RNA and DNA nucleotides, 2) RNA secondary structure prediction and 3) determination of the TPX thermal stability derived from a collection of TPX experimental evidences. We systematically collected and uniformly re-analysed published experimental lncRNA binding sites on human and mouse genomes. We used these data to evaluate 3plex performance and showed that its specific features allow a reliable identification of TPX interactions. We compared 3plex with the other available software and obtained comparable or even better accuracy at a fraction of the computation time. Interestingly, by inspecting collected data with 3plex we found that TPXs tend to be shorter and more degenerated than previously expected and that the majority of analysed lncRNAs can directly bind to the genome by TPX formation. Those results suggest that an important fraction of lncRNAs can exert its biological function through this mechanism. The software is available at https://github.com/molinerisLab/3plex.

Tissue memory relies on stem cell priming in distal undamaged areas.

Epithelial cells that participated in wound repair elicit a more efficient response to future injuries, which is believed to be locally restricted. Here we show that cell adaptation resulting from a localized tissue damage has a wide spatial impact at a scale not previously appreciated. We demonstrate that a specific stem cell population, distant from the original injury, originates long-lasting wound memory progenitors residing in their own niche. Notably, these distal memory cells have not taken part in the first healing but become intrinsically pre-activated through priming. This cell state, maintained at the chromatin and transcriptional level, leads to an enhanced wound repair that is partially recapitulated through epigenetic perturbation. Importantly wound memory has long-term harmful consequences, exacerbating tumourigenesis. Overall, we show that sub-organ-scale adaptation to injury relies on spatially organized memory-dedicated progenitors, characterized by an actionable cell state that establishes an epigenetic field cancerization and predisposes to tumour onset.

DNMT3B supports meso-endoderm differentiation from mouse embryonic stem cells.

The correct establishment of DNA methylation patterns during mouse early development is essential for cell fate specification. However, the molecular targets as well as the mechanisms that determine the specificity of the de novo methylation machinery during differentiation are not completely elucidated. Here we show that the DNMT3B-dependent DNA methylation of key developmental regulatory regions at epiblast-like cells (EpiLCs) provides an epigenetic priming that ensures flawless commitment at later stages. Using in vitro stem cell differentiation and loss of function experiments combined with high-throughput genome-wide bisulfite-, bulk-, and single cell RNA-sequencing we dissected the specific role of DNMT3B in cell fate. We identify DNMT3B-dependent regulatory elements on the genome which, in Dnmt3b knockout (3BKO), impair the differentiation into meso-endodermal (ME) progenitors and redirect EpiLCs towards the neuro-ectodermal lineages. Moreover, ectopic expression of DNMT3B in 3BKO re-establishes the DNA methylation of the master regulator Sox2 super-enhancer, downmodulates its expression, and restores the expression of ME markers. Taken together, our data reveal that DNMT3B-dependent methylation at the epiblast stage is essential for the priming of the meso-endodermal lineages and provide functional characterization of the de novo DNMTs during EpiLCs lineage determination.

Single-Cell Sequencing for Everybody.

Over the past 7 years, single-cell sequencing has become very popular. For this reason, many laboratories of different biological disciplines that span from neurobiology to developmental biology from immunology to tumor biology have been approaching this technique. For someone new to this field that wants to investigate heterogeneity in what appears to be a single-cell population, the choice of the best protocol can be difficult, due to the high abundance of available protocols, instruments, and options. For this reason, here we describe the Smart-seq2 protocol for full-length mRNA sequencing of single cell. This protocol can be easily optimized in every molecular biology laboratory provided with standard laboratory equipment. The protocol is suitable for many different cell types, and the cost per cell is relatively small, allowing a good balance between costs and transcript coverage.

Flow Cytometry for Beginners: Hints and Tips for Approaching the Very First Single-Cell Technique.

While many single-cell proteomics techniques have been rapidly developed over the past decade, flow cytometry still remains the pillar of single-cell protein analysis, as it allows to rapidly analyze and characterize protein expression in millions of cells.In this chapter, we will describe the main steps to prepare and acquire samples for flow cytometry, with particular focus on the setup of the right controls that are instrumental in analyzing and interpreting the results.

The Lysine Methylase SMYD3 Modulates Mesendodermal Commitment during Development.

SMYD3 (SET and MYND domain containing protein 3) is a methylase over-expressed in cancer cells and involved in oncogenesis. While several studies uncovered key functions for SMYD3 in cancer models, the SMYD3 role in physiological conditions has not been fully elucidated yet. Here, we dissect the role of SMYD3 at early stages of development, employing mouse embryonic stem cells (ESCs) and zebrafish as model systems. We report that SMYD3 depletion promotes the induction of the mesodermal pattern during in vitro differentiation of ESCs and is linked to an upregulation of cardiovascular lineage markers at later stages. In vivo, smyd3 knockdown in zebrafish favors the upregulation of mesendodermal markers during zebrafish gastrulation. Overall, our study reveals that SMYD3 modulates levels of mesendodermal markers, both in development and in embryonic stem cell differentiation.

Hair follicle stem cell progeny heal blisters while pausing skin development.

Injury in adult tissue generally reactivates developmental programs to foster regeneration, but it is not known whether this paradigm applies to growing tissue. Here, by employing blisters, we show that epidermal wounds heal at the expense of skin development. The regenerated epidermis suppresses the expression of tissue morphogenesis genes accompanied by delayed hair follicle (HF) growth. Lineage tracing experiments, cell proliferation dynamics, and mathematical modeling reveal that the progeny of HF junctional zone stem cells, which undergo a morphological transformation, repair the blisters while not promoting HF development. In contrast, the contribution of interfollicular stem cell progeny to blister healing is small. These findings demonstrate that HF development can be sacrificed for the sake of epidermal wound regeneration. Our study elucidates the key cellular mechanism of wound healing in skin blistering diseases.

Mapping Rora expression in resting and activated CD4+ T cells.

The transcription factor Rora has been shown to be important for the development of ILC2 and the regulation of ILC3, macrophages and Treg cells. Here we investigate the role of Rora across CD4+ T cells in general, but with an emphasis on Th2 cells, both in vitro as well as in the context of several in vivo type 2 infection models. We dissect the function of Rora using overexpression and a CD4-conditional Rora-knockout mouse, as well as a RORA-reporter mouse. We establish the importance of Rora in CD4+ T cells for controlling lung inflammation induced by Nippostrongylus brasiliensis infection, and have measured the effect on downstream genes using RNA-seq. Using a systematic stimulation screen of CD4+ T cells, coupled with RNA-seq, we identify upstream regulators of Rora, most importantly IL-33 and CCL7. Our data suggest that Rora is a negative regulator of the immune system, possibly through several downstream pathways, and is under control of the local microenvironment.

Long Noncoding RNAs in Human Stemness and Differentiation.

There is increasing evidence that long noncoding RNAs (lncRNAs) are among the main regulatory factors of stem cell maintenance and differentiation. They act through various mechanisms and interactions with proteins, DNA, and RNA. This heterogeneity in function increases the capabilities of the lncRNome toolkit but also makes it difficult to predict the function of novel lncRNAs or even rely on biological information produced in animal models. As lncRNAs are species- and tissue-specific, the recent technical advances in self-renewal and differentiation of human embryonic stem cells (ESCs) make these cells the ideal system to identify key regulatory lncRNAs and study their molecular functions. Here we provide an overview of the functional versatility of lncRNA mechanistic heterogeneity in regulating pluripotency maintenance and human differentiation.

Gene expression variability across cells and species shapes innate immunity.

As the first line of defence against pathogens, cells mount an innate immune response, which varies widely from cell to cell. The response must be potent but carefully controlled to avoid self-damage. How these constraints have shaped the evolution of innate immunity remains poorly understood. Here we characterize the innate immune response's transcriptional divergence between species and variability in expression among cells. Using bulk and single-cell transcriptomics in fibroblasts and mononuclear phagocytes from different species, challenged with immune stimuli, we map the architecture of the innate immune response. Transcriptionally diverging genes, including those that encode cytokines and chemokines, vary across cells and have distinct promoter structures. Conversely, genes that are involved in the regulation of this response, such as those that encode transcription factors and kinases, are conserved between species and display low cell-to-cell variability in expression. We suggest that this expression pattern, which is observed across species and conditions, has evolved as a mechanism for fine-tuned regulation to achieve an effective but balanced response.

Locked and Loaded: Inflammation Training Prepares Skin Epithelial Stem Cells for Trauma.

Memory of a trauma and how to cope with it is useful for acting rapidly in the event of a second traumatic incident. Recently, Naik et al. (2017) reported in Nature that skin epithelial stem cells have this ability by maintaining long-term chromatin features acquired during the first assault.

Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation.

BACKGROUND: Differentiation of lymphocytes is frequently accompanied by cell cycle changes, interplay that is of central importance for immunity but is still incompletely understood. Here, we interrogate and quantitatively model how proliferation is linked to differentiation in CD4+ T cells. RESULTS: We perform ex vivo single-cell RNA-sequencing of CD4+ T cells during a mouse model of infection that elicits a type 2 immune response and infer that the differentiated, cytokine-producing cells cycle faster than early activated precursor cells. To dissect this phenomenon quantitatively, we determine expression profiles across consecutive generations of differentiated and undifferentiated cells during Th2 polarization in vitro. We predict three discrete cell states, which we verify by single-cell quantitative PCR. Based on these three states, we extract rates of death, division and differentiation with a branching state Markov model to describe the cell population dynamics. From this multi-scale modelling, we infer a significant acceleration in proliferation from the intermediate activated cell state to the mature cytokine-secreting effector state. We confirm this acceleration both by live imaging of single Th2 cells and in an ex vivo Th1 malaria model by single-cell RNA-sequencing. CONCLUSION: The link between cytokine secretion and proliferation rate holds both in Th1 and Th2 cells in vivo and in vitro, indicating that this is likely a general phenomenon in adaptive immunity.

T cell fate and clonality inference from single-cell transcriptomes.

We developed TraCeR, a computational method to reconstruct full-length, paired T cell receptor (TCR) sequences from T lymphocyte single-cell RNA sequence data. TraCeR links T cell specificity with functional response by revealing clonal relationships between cells alongside their transcriptional profiles. We found that T cell clonotypes in a mouse Salmonella infection model span early activated CD4(+) T cells as well as mature effector and memory cells.

Single-cell technologies are revolutionizing the approach to rare cells.

In the last lustrum single-cell techniques such as single-cell quantitative PCR, RNA and DNA sequencing, and the state-of-the-art cytometry by time of flight (CyTOF) mass cytometer have allowed a detailed analysis of the sub-composition of different organs from the bone marrow hematopoietic compartment to the brain. These fine-grained analyses have highlighted the great heterogeneity within each cell compartment revealing previously unknown subpopulations of cells. In this review, we analyze how this fast technological evolution has improved our understanding of the biological processes with a particular focus on rare cells of the immune system.

Single-cell technologies to study the immune system.

The immune system is composed of a variety of cells that act in a coordinated fashion to protect the organism against a multitude of different pathogens. The great variability of existing pathogens corresponds to a similar high heterogeneity of the immune cells. The study of individual immune cells, the fundamental unit of immunity, has recently transformed from a qualitative microscopic imaging to a nearly complete quantitative transcriptomic analysis. This shift has been driven by the rapid development of multiple single-cell technologies. These new advances are expected to boost the detection of less frequent cell types and transient or intermediate cell states. They will highlight the individuality of each single cell and greatly expand the resolution of current available classifications and differentiation trajectories. In this review we discuss the recent advancement and application of single-cell technologies, their limitations and future applications to study the immune system.

Computational assignment of cell-cycle stage from single-cell transcriptome data.

The transcriptome of single cells can reveal important information about cellular states and heterogeneity within populations of cells. Recently, single-cell RNA-sequencing has facilitated expression profiling of large numbers of single cells in parallel. To fully exploit these data, it is critical that suitable computational approaches are developed. One key challenge, especially pertinent when considering dividing populations of cells, is to understand the cell-cycle stage of each captured cell. Here we describe and compare five established supervised machine learning methods and a custom-built predictor for allocating cells to their cell-cycle stage on the basis of their transcriptome. In particular, we assess the impact of different normalisation strategies and the usage of prior knowledge on the predictive power of the classifiers. We tested the methods on previously published datasets and found that a PCA-based approach and the custom predictor performed best. Moreover, our analysis shows that the performance depends strongly on normalisation and the usage of prior knowledge. Only by leveraging prior knowledge in form of cell-cycle annotated genes and by preprocessing the data using a rank-based normalisation, is it possible to robustly capture the transcriptional cell-cycle signature across different cell types, organisms and experimental protocols.