Gene regulation networks related to neural differentiation of hESC

Insights into the ubiquitin-proteasome system of human embryonic stem cells

Human embryonic stem cells (hESCs) exhibit high levels of proteasome activity, an intrinsic characteristic required for their self-renewal, pluripotency and differentiation. However, the mechanisms by which enhanced proteasome activity maintains hESC identity are only partially understood. Besides its essential role for the ability of hESCs to suppress misfolded protein aggregation, we hypothesize that enhanced proteasome activity could also be important to degrade endogenous regulatory factors. Since E3 ubiquitin ligases are responsible for substrate selection, we first define which E3 enzymes are increased in hESCs compared with their differentiated counterparts. Among them, we find HECT-domain E3 ligases such as HERC2 and UBE3A as well as several RING-domain E3s, including UBR7 and RNF181. Systematic characterization of their interactome suggests a link with hESC identity. Moreover, loss of distinct up-regulated E3s triggers significant changes at the transcriptome and proteome level of hESCs. However, these alterations do not dysregulate pluripotency markers and differentiation ability. On the contrary, global proteasome inhibition impairs diverse processes required for hESC identity, including protein synthesis, rRNA maturation, telomere maintenance and glycolytic metabolism. Thus, our data indicate that high proteasome activity is coupled with other determinant biological processes of hESC identity.

Investigating evolutionary perspective of carcinogenesis with single-cell transcriptome analysis

We developed phase-switch microfluidic devices for molecular profiling of a large number of single cells. Whole genome microarrays and RNA-sequencing are commonly used to determine the expression levels of genes in cell lysates (a physical mix of millions of cells) for inferring gene functions. However, cellular heterogeneity becomes an inherent noise in the measurement of gene expression. The unique molecular characteristics of individual cells, as well as the temporal and quantitative information of gene expression in cells, are lost when averaged among all cells in cell lysates. Our single-cell technology overcomes this limitation and enables us to obtain a large number of single-cell transcriptomes from a population of cells. A collection of single-cell molecular profiles allows us to study carcinogenesis from an evolutionary perspective by treating cancer as a diverse population of cells with abnormal molecular characteristics. Because a cancer cell population contains cells at various stages of development toward drug resistance, clustering similar single-cell molecular profiles could reveal how drug-resistant sub-clones evolve during cancer treatment. Here, we discuss how single-cell transcriptome analysis technology could enable the study of carcinogenesis from an evolutionary perspective and the development of drug-resistance in leukemia. The single-cell transcriptome analysis reported here could have a direct and significant impact on current cancer treatments and future personalized cancer therapies.

Increase developmental plasticity of human keratinocytes with gene suppression

Recent evidence indicates that p53 suppression increased the efficiency of induced pluripotent stem cell (iPSC) generation. This occurred even with the enforced expression of as few as two canonical transcription factors, Oct4 and Sox2. In this study, primary human keratinocytes were successfully induced into a stage of plasticity by transient inactivation of p53, without enforced expression of any of the transcription factors previously used in iPSC generation. These cells were later redifferentiated into neural lineages. The gene suppression plastic cells were morphologically indistinguishable from human ES cells. Gene suppression plastic cells were alkaline phosphatase-positive, had normal karyotypes, and expressed p53. Together with the accumulating evidence of similarities and overlapping mechanisms between iPSC generation and cancer formation, this finding sheds light on the emerging picture of p53 sitting at the crossroads between two intricate cellular potentials: stem cell vs. cancer cell generation. This finding further supports the crucial role played by p53 in cellular reprogramming and suggests an alternative method to switch the lineage identity of human cells. This reported method offers the potential for directed lineage switching with the goal of generating autologous cell populations for novel clinical applications for neurodegenerative diseases.

Developmental engineering: a new paradigm for the design and manufacturing of cell-based products. Part II: from genes to networks: tissue engineering from the viewpoint of systems biology and network science

The field of tissue engineering is moving toward a new concept of "in vitro biomimetics of in vivo tissue development." In Part I of this series, we proposed a theoretical framework integrating the concepts of developmental biology with those of process design to provide the rules for the design of biomimetic processes. We named this methodology "developmental engineering" to emphasize that it is not the tissue but the process of in vitro tissue development that has to be engineered. To formulate the process design rules in a rigorous way that will allow a computational design, we should refer to mathematical methods to model the biological process taking place in vitro. Tissue functions cannot be attributed to individual molecules but rather to complex interactions between the numerous components of a cell and interactions between cells in a tissue that form a network. For tissue engineering to advance to the level of a technologically driven discipline amenable to well-established principles of process engineering, a scientifically rigorous formulation is needed of the general design rules so that the behavior of networks of genes, proteins, or cells that govern the unfolding of developmental processes could be related to the design parameters. Now that sufficient experimental data exist to construct plausible mathematical models of many biological control circuits, explicit hypotheses can be evaluated using computational approaches to facilitate process design. Recent progress in systems biology has shown that the empirical concepts of developmental biology that we used in Part I to extract the rules of biomimetic process design can be expressed in rigorous mathematical terms. This allows the accurate characterization of manufacturing processes in tissue engineering as well as the properties of the artificial tissues themselves. In addition, network science has recently shown that the behavior of biological networks strongly depends on their topology and has developed the necessary concepts and methods to describe it, allowing therefore a deeper understanding of the behavior of networks during biomimetic processes. These advances thus open the door to a transition for tissue engineering from a substantially empirical endeavor to a technology-based discipline comparable to other branches of engineering.

Temporal analysis of neural differentiation using quantitative proteomics

The ability to derive neural progenitors, differentiated neurons and glial cells from human embryonic stem cells (hESCs) with high efficiency holds promise for a number of clinical applications. However, investigating the temporal events is crucial for defining the underlying mechanisms that drive this process of differentiation along different lineages. We carried out quantitative proteomic profiling using a multiplexed approach capable of analyzing eight different samples simultaneously to monitor the temporal dynamics of protein abundance as human embryonic stem cells differentiate into motor neurons or astrocytes. With this approach, a catalog of approximately 1200 proteins along with their relative quantitative expression patterns was generated. The differential expression of the large majority of these proteins has not previously been reported or studied in the context of neural differentiation. As expected, two of the widely used markers of pluripotency, alkaline phosphatase (ALPL) and LIN28, were found to be downregulated during differentiation, while S-100 and tenascin C were upregulated in astrocytes. Neurofilament 3 protein, doublecortin and CAM kinase-like 1 and nestin proteins were upregulated during motor neuron differentiation. We identified a number of proteins whose expression was largely confined to specific cell types, embryonic stem cells, embryoid bodies and differentiating motor neurons. For example, glycogen phosphorylase (PYGL) and fatty acid binding protein 5 (FABP5) were enriched in ESCs, while beta spectrin (SPTBN5) was highly expressed in embryoid bodies. Karyopherin, heat shock 27 kDa protein 1 and cellular retinoic acid binding protein 2 (CRABP2) were upregulated in differentiating motor neurons but were downregulated in mature motor neurons. We validated some of the novel markers of the differentiation process using immunoblotting and immunocytochemical labeling. To our knowledge, this is the first large-scale temporal proteomic profiling of human stem cell differentiation into neural cell types highlighting proteins with limited or undefined roles in neural fate.