Mathematical modeling clarifies the paracrine roles of insulin and glucagon on the glucose-stimulated hormonal secretion of pancreatic alpha- and beta-cells

IntroductionBlood sugar homeostasis relies largely on the action of pancreatic islet hormones, particularly insulin and glucagon. In a prototypical fashion, glucagon is released upon hypoglycemia to elevate glucose by acting on the liver while elevated glucose induces the secretion of insulin which leads to sugar uptake by peripheral tissues. This simplified view of glucagon and insulin does not consider the paracrine roles of the two hormones modulating the response to glucose of α- and β-cells. In particular, glucose-stimulated glucagon secretion by isolated α-cells exhibits a Hill-function pattern, while experiments with intact pancreatic islets suggest a ‘U’-shaped response.MethodsTo this end, a framework was developed based on first principles and coupled to experimental studies capturing the glucose-induced response of pancreatic α- and β-cells influenced by the two hormones. The model predicts both the transient and steady-state profiles of secreted insulin and glucagon, including the typical biphasic response of normal β-cells to hyperglycemia.Results and discussionThe results underscore insulin activity as a differentiating factor of the glucagon secretion from whole islets vs. isolated α-cells, and highlight the importance of experimental conditions in interpreting the behavior of islet cells in vitro. The model also reproduces the hyperglucagonemia, which is experienced by diabetes patients, and it is linked to a failure of insulin to inhibit α-cell activity. The framework described here is amenable to the inclusion of additional islet cell types and extrapancreatic tissue cells simulating multi-organ systems. The study expands our understanding of the interplay of insulin and glucagon for pancreas function in normal and pathological conditions

Human pluripotent stem cell differentiation to functional pancreatic cells for diabetes therapies: Innovations, challenges and future directions

Abstract Recent advances in the expansion and directed pancreatogenic differentiation of human pluripotent stem cells (hPSCs) have intensified efforts to generate functional pancreatic islet cells, especially insulin-secreting β-cells, for cell therapies against diabetes. However, the consistent generation of glucose-responsive insulin-releasing cells remains challenging. In this article, we first present basic concepts of pancreatic organogenesis, which frequently serves as a basis for engineering differentiation regimens. Next, past and current efforts are critically discussed for the conversion of hPSCs along pancreatic cell lineages, including endocrine β-cells and α-cells, as well as exocrine cells with emphasis placed on the later stages of commitment. Finally, major challenges and future directions are examined, such as the identification of factors for in vivo maturation, large-scale culture and post processing systems, cell loss during differentiation, culture economics, efficiency, and efficacy and exosomes and miRNAs in pancreatic differentiation

Distinct Allelic Patterns of Nanog Expression Impart Embryonic Stem Cell Population Heterogeneity

<div><p>Nanog is a principal pluripotency regulator exhibiting a disperse distribution within stem cell populations in vivo and in vitro. Increasing evidence points to a functional role of Nanog heterogeneity on stem cell fate decisions. Allelic control of Nanog gene expression was reported recently in mouse embryonic stem cells. To better understand how this mode of regulation influences the observed heterogeneity of NANOG in stem cell populations, we assembled a multiscale stochastic population balance equation framework. In addition to allelic control, gene expression noise and random partitioning at cell division were considered. As a result of allelic Nanog expression, the distribution of Nanog exhibited three distinct states but when combined with transcriptional noise the profile became bimodal. Regardless of their allelic expression pattern, initially uniform populations of stem cells gave rise to the same Nanog heterogeneity within ten cell cycles. Depletion of NANOG content in cells switching off both gene alleles was slower than the accumulation of intracellular NANOG after cells turned on at least one of their Nanog gene copies pointing to Nanog state-dependent dynamics. Allelic transcription of Nanog also raises issues regarding the use of stem cell lines with reporter genes knocked in a single allelic locus. Indeed, significant divergence was observed in the reporter and native protein profiles depending on the difference in their half-lives and insertion of the reporter gene in one or both alleles. In stem cell populations with restricted Nanog expression, allelic regulation facilitates the maintenance of fractions of self-renewing cells with sufficient Nanog content to prevent aberrant loss of pluripotency. Our findings underline the role of allelic control of Nanog expression as a prime determinant of stem cell population heterogeneity and warrant further investigation in the contexts of stem cell specification and cell reprogramming.</p></div

Contribution of Stochastic Partitioning at Human Embryonic Stem Cell Division to NANOG Heterogeneity

<div><p>Heterogeneity is an often unappreciated characteristic of stem cell populations yet its importance in fate determination is becoming increasingly evident. Although gene expression noise has received greater attention as a source of non-genetic heterogeneity, the effects of stochastic partitioning of cellular material during mitosis on population variability have not been researched to date. We examined self-renewing human embryonic stem cells (hESCs), which typically exhibit a dispersed distribution of the pluripotency marker NANOG. In conjunction with our experiments, a multiscale cell population balance equation (PBE) model was constructed accounting for transcriptional noise and stochastic partitioning at division as sources of population heterogeneity. Cultured hESCs maintained time-invariant profiles of size and NANOG expression and the data were utilized for parameter estimation. Contributions from both sources considered in this study were significant on the NANOG profile, although elimination of the gene expression noise resulted in greater changes in the dispersion of the NANOG distribution. Moreover, blocking of division by treating hESCs with nocodazole or colcemid led to a 39% increase in the average NANOG content and over 68% of the cells had higher NANOG level than the mean NANOG expression of untreated cells. Model predictions, which were in excellent agreement with these findings, revealed that stochastic partitioning accounted for 17% of the total noise in the NANOG profile of self-renewing hESCs. The computational framework developed in this study will aid in gaining a deeper understanding of how pluripotent stem/progenitor cells orchestrate processes such as gene expression and proliferation for maintaining their pluripotency or differentiating along particular lineages. Such models will be essential in designing and optimizing efficient differentiation strategies and bioprocesses for the production of therapeutically suitable stem cell progeny.</p></div

Reporter and endogenous NANOG protein levels under different conditions.

<p>(A) Observed NANOG reporter (GFP) expression level in stem cells with a single-allele insertion of the <i>gfp</i>. The expression levels of NANOG and the reporter are shown assuming the same t_1/2 (2 hours) for the reporter and NANOG and the reporter gene inserted in (B) both alleles, or (C) one allele. NANOG and reporter levels are also shown for t_1/2(NANOG) = 2 and t_1/2(GFP) = 20 hours with the reporter gene inserted in (D) both, or (E) a single allele. The values of the Pearson correlation coefficient (ρ) for each case (B)–(E) are shown.</p

Proliferation arrest of hESCs and NANOG expression distribution.

<p>(A–D) Cell cycle analysis performed via flow cytometry on (A) untreated hESCs, and hESCs treated with (B) 200 ng/ml nocodazole or (C) 100 ng/ml colcemid for 16 hrs. (D) Human ESCs after a 2-hr recovery following nocodazole treatment as in (B). Flow cytometry data (black curves) were analyzed using the FCS Express 4.0 software (red, green curves). Results are shown as mean ± standard deviation from at least three independent experiments. (E) Histograms of NANOG expression for (top) untreated and (bottom) nocodazole-treated self-renewing hESCs. The dashed line denotes the mean NANOG fluorescence intensity (MFI) of untreated hESCs. The fractions (%) show the cells with fluorescence intensity above the MFI value. (F) The LN and HN regions were defined by 20% of hESCs with the lowest and highest NANOG expression, respectively. (G) The same gating criteria were applied to Nocodazole-treated NANOG⁺ hESCs; (H) The percentage of LN and HN hESCs under the conditions indicated: (i) Untreated hESCs (normal hESCs), (ii) hESCs treated with 200 ng/ml Nocodazole or (iii) 100 ng/ml colcemid for 16 hr, and (iv) hESCs recovered 24 hr after a 16-hr treatment with nocodazole. Error bars are calculated from at least three independent experiments (*p<0.001).</p

PBE model parameters [23].

<p>PBE model parameters <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003140#pcbi.1003140-Wu1" target="_blank">[23]</a>.</p

Parameter values calculated based on data from experiments (n = 3–7).

<p>Parameter values calculated based on data from experiments (n = 3–7).</p

NANOG dynamics for mESC populations and single cells.

<p>(A) Overall NANOG expression distribution in equilibrium. Three distinct peaks of low (‘L’), middle (‘M’) and high (‘H’) NANOG content are observed. (B) The distribution of NANOG at equilibrium taking into account transcriptional noise. (C) A map of the NANOG content of each cell in the population. Different colors represent the four patterns of allelic Nanog expression. (D) Fluctuations in NANOG by a randomly selected single mESC. After each division only one daughter cell is shown. Arrows mark divisions and allelic switch events. (E) Starting with a single mESC expressing Nanog monoallelically, the resulting population after 60 hours contains cells of all four types. Both daughter cells were shown after each cell division. The trajectory of one daughter cell is denoted with the same color as the mother cell.</p