Cellular identity at the single-cell level

One model fits all: Combining inference and simulation of gene regulatory networks

The rise of single-cell data highlights the need for a nondeterministic view of gene expression, while offering new opportunities regarding gene regulatory network inference. We recently introduced two strategies that specifically exploit time-course data, where single-cell profiling is performed after a stimulus: HARISSA, a mechanistic network model with a highly efficient simulation procedure, and CARDAMOM, a scalable inference method seen as model calibration. Here, we combine the two approaches and show that the same model driven by transcriptional bursting can be used simultaneously as an inference tool, to reconstruct biologically relevant networks, and as a simulation tool, to generate realistic transcriptional profiles emerging from gene interactions. We verify that CARDAMOM quantitatively reconstructs causal links when the data is simulated from HARISSA, and demonstrate its performance on experimental data collected on in vitro differentiating mouse embryonic stem cells. Overall, this integrated strategy largely overcomes the limitations of disconnected inference and simulation.

Reduction of a stochastic model of gene expression: Lagrangian dynamics gives access to basins of attraction as cell types and metastabilty

Differentiation is the process whereby a cell acquires a specific phenotype, by differential gene expression as a function of time. This is thought to result from the dynamical functioning of an underlying Gene Regulatory Network (GRN). The precise path from the stochastic GRN behavior to the resulting cell state is still an open question. In this work we propose to reduce a stochastic model of gene expression, where a cell is represented by a vector in a continuous space of gene expression, to a discrete coarse-grained model on a limited number of cell types. We develop analytical results and numerical tools to perform this reduction for a specific model characterizing the evolution of a cell by a system of piecewise deterministic Markov processes (PDMP). Solving a spectral problem, we find the explicit variational form of the rate function associated to a large deviations principle, for any number of genes. The resulting Lagrangian dynamics allows us to define a deterministic limit of which the basins of attraction can be identified to cellular types. In this context the quasipotential, describing the transitions between these basins in the weak noise limit, can be defined as the unique solution of an Hamilton-Jacobi equation under a particular constraint. We develop a numerical method for approximating the coarse-grained model parameters, and show its accuracy for a symmetric toggle-switch network. We deduce from the reduced model an approximation of the stationary distribution of the PDMP system, which appears as a Beta mixture. Altogether those results establish a rigorous frame for connecting GRN behavior to the resulting cellular behavior, including the calculation of the probability of jumps between cell types.

Cis-Regulatory Logic Produces Gene-Expression Noise Describing Phenotypic Heterogeneity in Bacteria

Gene transcriptional process is random. It occurs in bursts and follows single-molecular kinetics. Intermittent bursts are measured based on their frequency and size. They influence temporal fluctuations in the abundance of total mRNA and proteins by generating distinct transcriptional variations referred to as “noise”. Noisy expression induces uncertainty because the association between transcriptional variation and the extent of gene expression fluctuation is ambiguous. The promoter architecture and remote interference of different cis-regulatory elements are the crucial determinants of noise, which is reflected in phenotypic heterogeneity. An alternative perspective considers that cellular parameters dictating genome-wide transcriptional kinetics follow a universal pattern. Research on noise and systematic perturbations of promoter sequences reinforces that both gene-specific and genome-wide regulation occur across species ranging from bacteria and yeast to animal cells. Thus, deciphering gene-expression noise is essential across different genomics applications. Amidst the mounting conflict, it is imperative to reconsider the scope, progression, and rational construction of diversified viewpoints underlying the origin of the noise. Here, we have established an indication connecting noise, gene expression variations, and bacterial phenotypic variability. This review will enhance the understanding of gene-expression noise in various scientific contexts and applications.

Improvement of Disease Resistance in Livestock: Application of Immunogenomics and CRISPR/Cas9 Technology

Disease occurrence adversely affects livestock production and animal welfare, and have an impact on both human health and public perception of food-animals production. Combined efforts from farmers, animal scientists, and veterinarians have been continuing to explore the effective disease control approaches for the production of safe animal-originated food. Implementing the immunogenomics, along with genome editing technology, has been considering as the key approach for safe food-animal production through the improvement of the host genetic resistance. Next-generation sequencing, as a cutting-edge technique, enables the production of high throughput transcriptomic and genomic profiles resulted from host-pathogen interactions. Immunogenomics combine the transcriptomic and genomic data that links to host resistance to disease, and predict the potential candidate genes and their genomic locations. Genome editing, which involves insertion, deletion, or modification of one or more genes in the DNA sequence, is advancing rapidly and may be poised to become a commercial reality faster than it has thought. The clustered regulatory interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) [CRISPR/Cas9] system has recently emerged as a powerful tool for genome editing in agricultural food production including livestock disease management. CRISPR/Cas9 mediated insertion of NRAMP1 gene for producing tuberculosis resistant cattle, and deletion of CD163 gene for producing porcine reproductive and respiratory syndrome (PRRS) resistant pigs are two groundbreaking applications of genome editing in livestock. In this review, we have highlighted the technological advances of livestock immunogenomics and the principles and scopes of application of CRISPR/Cas9-mediated targeted genome editing in animal breeding for disease resistance.

The Application of Single-Cell RNA Sequencing in Studies of Autoimmune Diseases: a Comprehensive Review

Complex composition is one of the most important features of the immune system, involving many types of organs, tissues, cells, and molecules that perform immune functions. The normal function of each component of the immune system is the guarantee for maintaining the relatively stable immune function of the body. When the self-immune tolerance mechanism of the body is unregulated or destroyed, the immune system reacts to autoantigens, resulting in damage to self-tissues and organs or an immunopathological state with abnormal functions. Autoimmune diseases are diverse, and their pathogenesis is complicated. Various immune cells and their interactions play significant roles in the occurrence and development of diseases. The solution to heterogeneity of immune cells is the basic science and translational understanding of how genes and the environment interact to induce disease so that we can develop personalized medicine, a goal that has to this point eluded scientists. Single-cell RNA sequencing (scRNA-Seq) refers to a new technique allowing high-throughput sequencing analysis of the whole transcriptome to reveal the gene expression status of individual cells. It has emerged as an indispensable tool in the field of life science research, and can help identify the complex mechanism of cell heterogeneity, discover new cell subsets, and help uncover the molecular mechanisms of pathogenesis, the evolution of disorders, and drug resistance. This information can provide us with new strategies for diagnosis and prognostic evaluation, as well as monitoring treatment responses. In this review, we summarize the crucial experimental procedures used for single-cell RNA sequencing, and the current applications of this technique to study autoimmune diseases are described in detail. This technique will be widely used in more in-depth studies of autoimmune diseases and will contribute to the diagnosis and therapies of these disorders.

Comparison of neural stem/progenitor cells from adult Gecko japonicus and mouse spinal cords

The properties and number of neural stem cells (NSCs) in neural tissue are important issues for the regenerative capacity of the spinal cord in different organisms or developmental stages. In this study, we investigated the self-renewal and differentiation potential of NSCs from adult spinal cords of adult geckos (Gecko japonicus) and mice. The sphere forming ratio of mouse NSCs was higher than that of gecko NSCs, and the sphere forming time of mouse NSCs was shorter as well. In addition, serum-induced differentiation of NSCs gave rise to more β-tubulin III (TUBB3)-positive progeny in geckos, whereas NSCs gave rise to more glial fibrillary acidic protein (GFAP)-positive cells in mice. We further conducted single sphere RNA-seq for both gecko and mouse NSCs, and transcriptome data revealed that purified NSC populations form either geckos or mice are heterogeneous and stay at various differentiated stages even with similar appearance. Mouse NSCs expressed more glial markers and gecko NSCs expressed more neuronal markers, which is consistent with cell fate determination of mouse and gecko NSCs in differentiation assays.

The epicenter of chromosomal fragility of Fra14A2, the mouse ortholog of human FRA3B common fragile site, is largely attached to the nuclear matrix in lymphocytes but not in other cell types that do not express such a fragility

Common fragile sites (CFSs) correspond to chromosomal regions susceptible to present breaks, discontinuities or constrictions in metaphase chromosomes from cells subjected to replication stress. They are considered as genomic regions intrinsically difficult to replicate and they are evolutionary conserved at least in mammals. However, the recent discovery that CFSs are cell-type specific indicates that DNA sequence by itself cannot account for CFS instability. Nevertheless, the large gene FHIT that includes FRA3B, the most highly expressed CFS in human lymphocytes, is commonly deleted in a variety of tumors suggesting a tumor suppressor role for its product. Here, we report that the epicenter of fragility of Fra14A2/Fhit, the mouse ortholog of human FRA3B/FHIT that like its human counterpart is the most highly expressed CFS in mouse lymphocytes, is largely attached to the nuclear matrix compartment in naive B lymphocytes but not in primary hepatocytes or cortical neurons that do not express such a CFS. Our results suggest a structural explanation for the difficult-to-replicate nature of such a region and so for its common fragility in lymphocytes, that is independent of the possible tumor suppressor role of the gene harboring such CFS.

Recent advances in single-cell analysis by mass spectrometry

Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail.

Technical Advances in Single-Cell RNA Sequencing and Applications in Normal and Malignant Hematopoiesis

Single-cell RNA sequencing (scRNA-seq) has been tremendously developed in the past decade owing to overcoming challenges associated with isolation of massive quantities of single cells. Previously, cell heterogeneity and low quantities of available biological material posed significant difficulties to scRNA-seq. Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of normal and malignant hematopoietic cells; this heterogeneity has often been ignored in omics studies. The application of scRNA-seq has profoundly changed our comprehension of many biological phenomena, including organ development and carcinogenesis. Hematopoiesis, is actually a maturation process for more than ten distinct blood and immune cells, and is thought to be critically involved in hematological homeostasis and in sustaining the physiological functions. However, aberrant hematopoiesis directly leads to hematological malignancy, and a deeper understanding of malignant hematopoiesis will provide deeper insights into diagnosis and prognosis for patients with hematological malignancies. Here, we aim to review the recent technical progress and future prospects for scRNA-seq, as applied in physiological and malignant hematopoiesis, in efforts to further understand the hematopoietic hierarchy and to illuminate personalized therapy and precision medicine approaches used in the clinical treatment of hematological malignancies.

Application of Single Cell Sequencing in Cancer

Cancer is a heterogenetic disease at both the level of clinical manifestation and the level of the genome. Single-cell sequencing provides an unprecedented means of characterizing the intra-tumor heterogeneity and detecting and analyzing the genomes of cancer cells. These data will help to reconstruct the understanding of the evolutionary lineage of cancer cells. In the future, single-cell technology is believed to be a useful tool in diagnostic and prognostic application in oncology. The application of single cell technology in clinics will make it possible to detect cancer non-invasively at early stages and to develop precision medicine. In this chapter, we review the research and application status of the single cell technology in cancer.

Next-generation molecular diagnosis: single-cell sequencing from bench to bedside

Single-cell sequencing (SCS) is a fast-growing, exciting field in genomic medicine. It enables the high-resolution study of cellular heterogeneity, and reveals the molecular basis of complicated systems, which facilitates the identification of new biomarkers for diagnosis and for targeting therapies. It also directly promotes the next generation of genomic medicine because of its ultra-high resolution and sensitivity that allows for the non-invasive and early detection of abnormalities, such as aneuploidy, chromosomal translocation, and single-gene disorders. This review provides an overview of the current progress and prospects for the diagnostic applications of SCS, specifically in pre-implantation genetic diagnosis/screening, non-invasive prenatal diagnosis, and analysis of circulating tumor cells. These analyses will accelerate the early and precise control of germline- or somatic-mutation-based diseases, particularly single-gene disorders, chromosome abnormalities, and cancers.

Single cell sequencing: a distinct new field

Single cell sequencing (SCS) has become a new approach to study biological heterogeneity. The advancement in technologies for single cell isolation, amplification of genome/transcriptome and next-generation sequencing enables SCS to reveal the inherent properties of a single cell from the large scale of the genome, transcriptome or epigenome at high resolution. Recently, SCS has been widely applied in various clinical and research fields, such as cancer biology and oncology, immunology, microbiology, neurobiology and prenatal diagnosis. In this review, we will discuss the development of SCS methods and focus on the latest clinical and research applications of SCS.