Cell-Surface Marker Signature for Enrichment of Ventricular Cardiomyocytes Derived from Human Embryonic Stem Cells.

To facilitate understanding of human cardiomyocyte (CM) subtype specification, and the study of ventricular CM biology in particular, we developed a broadly applicable strategy for enrichment of ventricular cardiomyocytes (VCMs) derived from human embryonic stem cells (hESCs). A bacterial artificial chromosome transgenic H9 hESC line in which GFP expression was driven by the human ventricular-specific myosin light chain 2 (MYL2) promoter was generated, and screened to identify cell-surface markers specific for MYL2-GFP-expressing VCMs. A CD77+/CD200- cell-surface signature facilitated isolation of >97% cardiac troponin I-positive cells from H9 hESC differentiation cultures, with 65% expressing MYL2-GFP. This study provides a tool for VCM enrichment when using some, but not all, human pluripotent stem cell lines. Tools generated in this study can be utilized toward understanding CM subtype specification, and enriching for VCMs for therapeutic applications.

Cell-surface marker signatures for the isolation of neural stem cells, glia and neurons derived from human pluripotent stem cells.

BACKGROUND: Neural induction of human pluripotent stem cells often yields heterogeneous cell populations that can hamper quantitative and comparative analyses. There is a need for improved differentiation and enrichment procedures that generate highly pure populations of neural stem cells (NSC), glia and neurons. One way to address this problem is to identify cell-surface signatures that enable the isolation of these cell types from heterogeneous cell populations by fluorescence activated cell sorting (FACS). METHODOLOGY/PRINCIPAL FINDINGS: We performed an unbiased FACS- and image-based immunophenotyping analysis using 190 antibodies to cell surface markers on naïve human embryonic stem cells (hESC) and cell derivatives from neural differentiation cultures. From this analysis we identified prospective cell surface signatures for the isolation of NSC, glia and neurons. We isolated a population of NSC that was CD184(+)/CD271(-)/CD44(-)/CD24(+) from neural induction cultures of hESC and human induced pluripotent stem cells (hiPSC). Sorted NSC could be propagated for many passages and could differentiate to mixed cultures of neurons and glia in vitro and in vivo. A population of neurons that was CD184(-)/CD44(-)/CD15(LOW)/CD24(+) and a population of glia that was CD184(+)/CD44(+) were subsequently purified from cultures of differentiating NSC. Purified neurons were viable, expressed mature and subtype-specific neuronal markers, and could fire action potentials. Purified glia were mitotic and could mature to GFAP-expressing astrocytes in vitro and in vivo. CONCLUSIONS/SIGNIFICANCE: These findings illustrate the utility of immunophenotyping screens for the identification of cell surface signatures of neural cells derived from human pluripotent stem cells. These signatures can be used for isolating highly pure populations of viable NSC, glia and neurons by FACS. The methods described here will enable downstream studies that require consistent and defined neural cell populations.

The ROCK inhibitor Y-27632 improves recovery of human embryonic stem cells after fluorescence-activated cell sorting with multiple cell surface markers.

BACKGROUND: Due to the inherent sensitivity of human embryonic stem cells (hESCs) to manipulations, the recovery and survival of hESCs after fluorescence-activated cell sorting (FACS) can be low. Additionally, a well characterized and robust methodology for performing FACS on hESCs using multiple-cell surface markers has not been described. The p160-Rho-associated coiled kinase (ROCK) inhibitor, Y-27632, previously has been identified as enhancing survival of hESCs upon single-cell dissociation, as well as enhancing recovery from cryopreservation. Here we examined the application of Y-27632 to hESCs after FACS to improve survival in both feeder-dependent and feeder-independent growth conditions. METHODOLOGY/PRINCIPAL FINDINGS: HESCs were sorted using markers for SSEA-3, TRA-1-81, and SSEA-1. Cells were plated after sorting for 24 hours in either the presence or the absence of Y-27632. In both feeder-dependent and feeder-independent conditions, cell survival was greater when Y-27632 was applied to the hESCs after sort. Specifically, treatment of cells with Y-27632 improved post-sort recovery up to four fold. To determine the long-term effects of sorting with and without the application of Y-27632, hESCs were further analyzed. Specifically, hESCs sorted with and without the addition of Y-27632 retained normal morphology, expressed hESC-specific markers as measured by immunocytochemistry and flow cytometry, and maintained a stable karyotype. In addition, the hESCs could differentiate into three germ layers in vitro and in vivo in both feeder-dependent and feeder-independent growth conditions. CONCLUSIONS/SIGNIFICANCE: The application of Y-27632 to hESCs after cell sorting improves cell recovery with no observed effect on pluripotency, and enables the consistent recovery of hESCs by FACS using multiple surface markers. This improved methodology for cell sorting of hESCs will aid many applications such as removal of hESCs from secondary cell types, identification and isolation of stem cell subpopulations, and generation of single cell clones. Finally, these results demonstrate an additional application of ROCK inhibition to hESC research.

A chemical approach to stem cell biology.

Small molecule libraries have been used successfully to probe several biological systems. Recent work has translated these successes across to the field of stem cell biology. Stem cells hold promise for both modeling of early development as well as having therapeutic potential. Enhanced understanding of the molecular mechanisms that control stem cell fates as well as an improved ability to manipulate cell populations are required. Known mechanistic chemical compounds have been used with stem cells to accomplish these two goals. More recently, through the utilization of high fitness libraries in phenotype-based screens, several small molecules that control self-renewal and differentiation in stem cells have been identified. These small molecules provide useful chemical tools for both basic research and practical applications.

Analysis of MVP and VPARP promoters indicates a role for chromatin remodeling in the regulation of MVP.

Multi-drug-resistant cancer cells frequently express elevated levels of ribonucleoprotein complexes termed vaults. The increased expression of vault proteins and their mRNAs has led to the suggestion that vaults may play a direct role in preventing drug toxicity. To further understand vault component up-regulation, the three proteins that comprise the vault, the major vault protein (MVP), vault poly(ADP-ribose) polymerase (VPARP), and telomerase-associated protein-1 (TEP1), were examined with respect to gene amplification and drug-induced chromatin remodeling. Gene amplification was not responsible for increased vault component levels in multi-drug-resistant cancer cell lines. The TATA-less murine MVP and human VPARP promoters were identified and functionally characterized. There was no significant activation of either the MVP or VPARP promoters in drug-resistant cell lines in comparison to their parental, drug-sensitive counterparts. Treatment of various cell lines with sodium butyrate, an inhibitor of histone deacetylase (HDAC), led to an increase in vault component protein levels. Furthermore, treatment with trichostatin A (TSA), a more specific inhibitor of HDAC, caused an increase in MVP protein, mRNA, and promoter activity. These results suggest that up-regulation of MVP in multi-drug resistance (MDR) may involve chromatin remodeling.

Identification of conserved vault RNA expression elements and a non-expressed mouse vault RNA gene.

Vault RNA (vRNA) genes have been cloned from several vertebrates including rat, mouse, and humans. Their copy numbers vary, as does the length of the encoded RNA. We have determined that the mouse genome contains two vRNA genes; one is expressed the other is a pseudogene. In vitro transcription of the rat vRNA gene by RNA polymerase III has previously been shown to be dependent on a combination of both external and internal promoter sequence elements. By comparing the upstream regions of the vertebrate vRNA genes, a 25 bp conserved sequence and a TATA box can be identified. Furthermore, the unique arrangement of the internal promoter boxes (one A and two B boxes) is conserved in the expressed human vRNA genes even though a new RNA polymerase III termination sequence has evolved between the two B boxes.

A simpler way of comparing the labelling densities of cellular compartments illustrated using data from VPARP and LAMP-1 immunogold labelling experiments.

Quantitative immunoelectron microscopy of gold label in intracellular compartments often involves calculating labelling densities (LDs). These are related to antigen concentrations and usually refer gold particle counts to the sizes of compartments on sections (for example, golds per microm(2) of organelle profile area or per microm of membrane trace length). Here, we show how LD values can be estimated more simply (without estimating areas or lengths) and also how observed and expected LD values can be used to calculate a relative labelling index (RLI) for each compartment and then test statistically for preferential (non-random) labelling. For random labelling, RLI=1. Compartment size is estimated stereologically by superimposing random test points (which hit organelle profiles in proportion to their area) or test lines (which intersect membrane traces in proportion to their length). By this means, the observed LD of a compartment (LD(obs)) can be expressed simply as golds per test point (organelles) or per intersection (membranes). Furthermore, the LD obtained by dividing total golds (on all compartments) by total points or intersections (on all compartments) is the value to be expected (LD(exp)) when compartments label randomly. For each compartment, RLI=LD(obs)/LD(exp). Statistical analysis is undertaken by comparing observed distributions of golds with predicted random distributions (calculated from point or intersection counts). A compartment is preferentially labelled if two criteria are met: (1) its RLI>1 (i.e. LD(obs) is greater than LD(exp)) and (2) its partial chi-squared value makes a substantial contribution to total chi-squared value. This approach provides a simple and efficient way of comparing LDs in different compartments. Its utility is illustrated using data from VPARP and LAMP-1 labelling experiments.