Bringing Blood Stem Cell Phenotype, Genotype, and Function Closer Together

Imperfect purity, subtypes, and retrospective functional assays compromise efforts to define the molecular identity of hematopoietic stem cells (HSCs). In this issue of Cell Stem Cell, Wilson et al. (2015) use a single-cell-based bioinformatics-experimental strategy to extract a consensus molecular signature from heterogeneous HSC pools. Their data and strategy provide a powerful resource for stem cell characterization

Sensitivity Analysis of Intracellular Signaling Pathway Kinetics Predicts Targets for Stem Cell Fate Control

Directing stem cell fate requires knowledge of how signaling networks integrate temporally and spatially segregated stimuli. We developed and validated a computational model of signal transducer and activator of transcription-3 (Stat3) pathway kinetics, a signaling network involved in embryonic stem cell (ESC) self-renewal. Our analysis identified novel pathway responses; for example, overexpression of the receptor glycoprotein-130 results in reduced pathway activation and increased ESC differentiation. We used a systematic in silico screen to identify novel targets and protein interactions involved in Stat3 activation. Our analysis demonstrates that signaling activation and desensitization (the inability to respond to ligand restimulation) is regulated by balancing the activation state of a distributed set of parameters including nuclear export of Stat3, nuclear phosphatase activity, inhibition by suppressor of cytokine signaling, and receptor trafficking. This knowledge was used to devise a temporally modulated ligand delivery strategy that maximizes signaling activation and leads to enhanced ESC self-renewal

Geometric control of cardiomyogenic induction in human pluripotent stem cells

Although it has been observed that aggregate size affects cardiac development, an incomplete understanding of the cellular mechanisms underlying human pluripotent stem cell-derived cardiomyogenesis has limited the development of robust defined-condition cardiac cell generation protocols. Our objective was thus to elucidate cellular and molecular mechanisms underlying the endogenous control of human embryonic stem cell (hESC) cardiac tissue development, and to test the hypothesis that hESC aggregate size influences extraembryonic endoderm (ExE) commitment and cardiac inductive properties. hESC aggregates were generated with 100, 1000, or 4000 cells per aggregate using microwells. The frequency of endoderm marker (FoxA2 and GATA6)-expressing cells decreased with increasing aggregate size during early differentiation. Cardiogenesis was maximized in aggregates initiated from 1000 cells, with frequencies of 0.49±0.06 cells exhibiting a cardiac progenitor phenotype (KDRlow/C-KITneg) on day 5 and 0.24±0.06 expressing cardiac Troponin T on day 16. A direct relationship between ExE and cardiac differentiation efficiency was established by forming aggregates with varying ratios of SOX7 (a transcription factor required for ExE development) overexpressing or knockdown hESCs to unmanipulated hESCs. We demonstrate, in a defined, serum-free cardiac induction system, that robust and efficient cardiac differentiation is a function of endogenous ExE cell concentration, a parameter that can be directly modulated by controlling hESC aggregate size. © 2011 Mary Ann Liebert, Inc

Dynamic interaction networks in a hierarchically organized tissue

We have integrated gene expression profiling with database and literature mining, mechanistic modeling, and cell culture experiments to identify intercellular and intracellular networks regulating blood stem cell self-renewal.Blood stem cell fate in vitro is regulated non-autonomously by a coupled positive–negative intercellular feedback circuit, composed of megakaryocyte-derived stimulatory growth factors (VEGF, PDGF, EGF, and serotonin) versus monocyte-derived inhibitory factors (CCL3, CCL4, CXCL10, TGFB2, and TNFSF9).The antagonistic signals converge in a core intracellular network focused around PI3K, Raf, PLC, and Akt.Model simulations enable functional classification of the novel endogenous ligands and signaling molecules

Intercellular network structure and regulatory motifs in the human hematopoietic system.

The hematopoietic system is a distributed tissue that consists of functionally distinct cell types continuously produced through hematopoietic stem cell (HSC) differentiation. Combining genomic and phenotypic data with high-content experiments, we have built a directional cell-cell communication network between 12 cell types isolated from human umbilical cord blood. Network structure analysis revealed that ligand production is cell type dependent, whereas ligand binding is promiscuous. Consequently, additional control strategies such as cell frequency modulation and compartmentalization were needed to achieve specificity in HSC fate regulation. Incorporating the in vitro effects (quiescence, self-renewal, proliferation, or differentiation) of 27 HSC binding ligands into the topology of the cell-cell communication network allowed coding of cell type-dependent feedback regulation of HSC fate. Pathway enrichment analysis identified intracellular regulatory motifs enriched in these cell type- and ligand-coupled responses. This study uncovers cellular mechanisms of hematopoietic cell feedback in HSC fate regulation, provides insight into the design principles of the human hematopoietic system, and serves as a foundation for the analysis of intercellular regulation in multicellular systems

Distinguishing autocrine and paracrine signals in hematopoietic stem cell culture using a biofunctional microcavity platform

Homeostasis of hematopoietic stem cells (HSC) in the mammalian bone marrow stem cell niche is regulated by signals of the local microenvironment. Besides juxtacrine, endocrine and metabolic cues, paracrine and autocrine signals are involved in controlling quiescence, proliferation and differentiation of HSC with strong implications on expansion and differentiation ex vivo as well as in vivo transplantation. Towards this aim, a cell culture analysis on a polymer microcavity carrier platform was combined with a partial least square analysis of a mechanistic model of cell proliferation. We could demonstrate the discrimination of specific autocrine and paracrine signals from soluble factors as stimulating and inhibitory effectors in hematopoietic stem and progenitor cell culture. From that we hypothesize autocrine signals to be predominantly involved in maintaining the quiescent state of HSC in single-cell niches and advocate our analysis platform as an unprecedented option for untangling convoluted signaling mechanisms in complex cell systems being it of juxtacrine, paracrine or autocrine origin

Endogenous suppression of WNT signalling in human embryonic stem cells leads to low differentiation propensity towards definitive endoderm

Low differentiation propensity towards a targeted lineage can significantly hamper the utility of individual human pluripotent stem cell (hPSC) lines in biomedical applications. Here, we use monolayer and micropatterned cell cultures, as well as transcriptomic profiling, to investigate how variability in signalling pathway activity between human embryonic stem cell lines affects their differentiation efficiency towards definitive endoderm (DE). We show that endogenous suppression of WNT signalling in hPSCs at the onset of differentiation prevents the switch from self-renewal to DE specification. Gene expression profiling reveals that this inefficient switch is reflected in NANOG expression dynamics. Importantly, we demonstrate that higher WNT stimulation or inhibition of the PI3K/AKT signalling can overcome the DE commitment blockage. Our findings highlight that redirection of the activity of Activin/NODAL pathway by WNT signalling towards mediating DE fate specification is a vulnerable spot, as disruption of this process can result in poor hPSC specification towards DE

Models predict change in plasma triglyceride concentrations and long-chain n-3 polyunsaturated fatty acid proportions in healthy participants after fish oil intervention

Introduction: Substantial response heterogeneity is commonly seen in dietary intervention trials. In larger datasets, this variability can be exploited to identify predictors, for example genetic and/or phenotypic baseline characteristics, associated with response in an outcome of interest. Objective: Using data from a placebo-controlled crossover study (the FINGEN study), supplementing with two doses of long chain n-3 polyunsaturated fatty acids (LC n-3 PUFAs), the primary goal of this analysis was to develop models to predict change in concentrations of plasma triglycerides (TG), and in the plasma phosphatidylcholine (PC) LC n-3 PUFAs eicosapentaenoic acid (EPA) + docosahexaenoic acid (DHA), after fish oil (FO) supplementation. A secondary goal was to establish if clustering of data prior to FO supplementation would lead to identification of groups of participants who responded differentially. Methods: To generate models for the outcomes of interest, variable selection methods (forward and backward stepwise selection, LASSO and the Boruta algorithm) were applied to identify suitable predictors. The final model was chosen based on the lowest validation set root mean squared error (RMSE) after applying each method across multiple imputed datasets. Unsupervised clustering of data prior to FO supplementation was implemented using k-medoids and hierarchical clustering, with cluster membership compared with changes in plasma TG and plasma PC EPA + DHA. Results: Models for predicting response showed a greater TG-lowering after 1.8 g/day EPA + DHA with lower pre-intervention levels of plasma insulin, LDL cholesterol, C20:3n-6 and saturated fat consumption, but higher pre-intervention levels of plasma TG, and serum IL-10 and VCAM-1. Models also showed greater increases in plasma PC EPA + DHA with age and female sex. There were no statistically significant differences in PC EPA + DHA and TG responses between baseline clusters. Conclusion: Our models established new predictors of response in TG (plasma insulin, LDL cholesterol, C20:3n-6, saturated fat consumption, TG, IL-10 and VCAM-1) and in PC EPA + DHA (age and sex) upon intervention with fish oil. We demonstrate how application of statistical methods can provide new insights for precision nutrition, by predicting participants who are most likely to respond beneficially to nutritional interventions