On Signal Transduction in Human Embryonic Stem Cells: Towards a Systems View

Human embryonic stem cells (hESC) have been a major cell source for research in regenerative medicine due to the demonstration of properties of self-renewal and efficient lineage specific differentiation, both on additions of external cues. Self-renewal provides the potential to extract large quantities of naïve cells that can then be differentiated to clinically relevant mature lineages. While there exists significant proof-of-concept to transform stem cells to the desired lineage, generating fully functional cell types is still an unmet challenge. A major reason for this is our limited understanding of the complexity of the transformation process. The overarching goal of this PhD research was to provide strategies to bring mathematical modeling into the realm of stem cell research, particularly to analyze the complex regulatory network of signaling events controlling cell fate. This work focused on the signaling pathways that in concert control the balance of self-renewal and endoderm differentiation of hESCs. We proposed a framework for developing mechanistic understanding from disparate signaling pathways using combinations of data-driven and equation based models. As a first step, we analyzed growth factor mediated PI3K/AKT pathway that must remain highly active to inhibit differentiation in self-renewal state. Using an integrated approach of mechanistic modeling, systems analysis and experimental validation we identified the role of a regulatory process (negative feedback) in maintaining signal amplitudes and controlling the propagation of parameter uncertainty down the pathway in the self-renewal state. To analyze endoderm differentiation, biclustering with bootstrapping formulation was used to identify co-regulated transcription factor patterns under a combinatorial modulation of endoderm inducing signaling pathways. In the final step, a detailed mechanistic analysis was done to characterize the dynamic features of TGF-β/SMAD pathway for inducing endoderm. Utilizing a dynamic Bayesian network formulism, AKT mediated crosstalk connections were inferred from the detailed time series data. Modeling of competing AKT-SMAD interactions followed by parametric ensemble analysis enabled identification of plausible hypotheses that could explain experimental observations. Using our integrated approach, we can now begin to rationally optimize for desirable fate of hESCs with reduced variability and accelerate the path towards therapeutic applications of hESCs

Considering Abundance, Affinity, and Binding Site Availability in the NF-κB Target Selection Puzzle

The NF-κB transcription regulation system governs a diverse set of responses to various cytokine stimuli. With tools from in vitro biochemical characterizations, to omics-based whole genome investigations, great strides have been made in understanding how NF-κB transcription factors control the expression of specific sets of genes. Nonetheless, these efforts have also revealed a very large number of potential binding sites for NF-κB in the human genome, and a puzzle emerges when trying to explain how NF-κB selects from these many binding sites to direct cell-type- and stimulus-specific gene expression patterns. In this review, we surmise that target gene transcription can broadly be thought of as a function of the nuclear abundance of the various NF-κB dimers, the affinity of NF-κB dimers for the regulatory sequence and the availability of this regulatory site. We use this framework to place quantitative information that has been gathered about the NF-κB transcription regulation system into context and thus consider questions it answers, and questions it raises. We end with a brief discussion of some of the future prospects that new approaches could bring to our understanding of how NF-κB transcription factors orchestrate diverse responses in different biological contexts

Potential for pancreatic maturation of differentiating human embryonic stem cells is sensitive to the specific pathway of definitive endoderm commitment

This study provides a detailed experimental and mathematical analysis of the impact of the initial pathway of definitive endoderm (DE) induction on later stages of pancreatic maturation. Human embryonic stem cells (hESCs) were induced to insulin-producing cells following a directed-differentiation approach. DE was induced following four alternative pathway modulations. DE derivatives obtained from these alternate pathways were subjected to pancreatic progenitor (PP) induction and maturation and analyzed at each stage. Results indicate that late stage maturation is influenced by the initial pathway of DE commitment. Detailed quantitative analysis revealed WNT3A and FGF2 induced DE cells showed highest expression of insulin, are closely aligned in gene expression patterning and have a closer resemblance to pancreatic organogenesis. Conversely, BMP4 at DE induction gave most divergent differentiation dynamics with lowest insulin upregulation, but highest glucagon upregulation. Additionally, we have concluded that early analysis of PP markers is indicative of its potential for pancreatic maturation. © 2014 Jaramillo et al

A Neutrophil Phenotype Model for Extracorporeal Treatment of Sepsis

Neutrophils play a central role in eliminating bacterial pathogens, but may also contribute to end-organ damage in sepsis. Interleukin-8 (IL-8), a key modulator of neutrophil function, signals through neutrophil specific surface receptors CXCR-1 and CXCR-2. In this study a mechanistic computational model was used to evaluate and deploy an extracorporeal sepsis treatment which modulates CXCR-1/2 levels. First, a simplified mechanistic computational model of IL-8 mediated activation of CXCR-1/2 receptors was developed, containing 16 ODEs and 43 parameters. Receptor level dynamics and systemic parameters were coupled with multiple neutrophil phenotypes to generate dynamic populations of activated neutrophils which reduce pathogen load, and/or primed neutrophils which cause adverse tissue damage when misdirected. The mathematical model was calibrated using experimental data from baboons administered a two-hour infusion of E coli and followed for a maximum of 28 days. Ensembles of parameters were generated using a Bayesian parallel tempering approach to produce model fits that could recreate experimental outcomes. Stepwise logistic regression identified seven model parameters as key determinants of mortality. Sensitivity analysis showed that parameters controlling the level of killer cell neutrophils affected the overall systemic damage of individuals. To evaluate rescue strategies and provide probabilistic predictions of their impact on mortality, time of onset, duration, and capture efficacy of an extracorporeal device that modulated neutrophil phenotype were explored. Our findings suggest that interventions aiming to modulate phenotypic composition are time sensitive. When introduced between 3–6 hours of infection for a 72 hour duration, the survivor population increased from 31% to 40–80%. Treatment efficacy quickly diminishes if not introduced within 15 hours of infection. Significant harm is possible with treatment durations ranging from 5–24 hours, which may reduce survival to 13%. In severe sepsis, an extracorporeal treatment which modulates CXCR-1/2 levels has therapeutic potential, but also potential for harm. Further development of the computational model will help guide optimal device development and determine which patient populations should be targeted by treatment

Network Analysis Identifies Crosstalk Interactions Governing TGF-β Signaling Dynamics during Endoderm Differentiation of Human Embryonic Stem Cells

The fate choice of human embryonic stem cells (hESCs) is controlled by complex signaling milieu synthesized by diverse chemical factors in the growth media. Prevalence of crosstalks and interactions between parallel pathways renders any analysis probing the process of fate transition of hESCs elusive. This work presents an important step in the evaluation of network level interactions between signaling molecules controlling endoderm lineage specification from hESCs using a statistical network identification algorithm. Network analysis was performed on detailed signaling dynamics of key molecules from TGF-β/SMAD, PI3K/AKT and MAPK/ERK pathways under two common endoderm induction conditions. The results show the existence of significant crosstalk interactions during endoderm signaling and they identify differences in network connectivity between the induction conditions in the early and late phases of signaling dynamics. Predicted networks elucidate the significant effect of modulation of AKT mediated crosstalk leading to the success of PI3K inhibition in inducing efficient endoderm from hESCs in combination with TGF-β/SMAD signaling

Evaluation of Background Transport Protocols in Production and Experimental LTE Networks.

As cellular networks are becoming faster, cheaper, and wider in terms of reach, it is today the carrier of ever-increasing bulk of network traffic. Cisco has predicted mobile data traffic to exceed 77 exabytes per month by 2022. Based on the time critical nature of traffic, it can be classified into high priority foreground (multimedia, real-time app data) and lower priority background traffic (software, firmware updates and cloud-sync) and it is highly undesirable for foreground flows to be affected by competing background flows in the same bottleneck link. Network policy dictates that such lower priority traffic should be transmitted only using spare capacity. State of the art congestion control schemes for background traffic achieves this by using one-way delay or round trip time as an indicator for congestion. This is an effective solution in wired or Wi-Fi networks, however they are inefficient in cellular networks due to operational characteristics of cellular scheduler (Proportional Fair (PF)), that aims at providing fairness at short time granularities. We present Legilimens, an end to end transport for low priority background flows in cellular networks. Legilimens leverages the traits of PF scheduler to detect contention in the last hop. This thesis evaluates Legilimens in real LTE production network and in emulated LTE test setup: Phantomnet. We compare Legilimens with several background transport protocols like LEDBAT, TCP-LP, and Vegas and with popular congestion control schemes like Cubic and Reno using specifically designed test methodologies like, one-on-one and mixed workloads. We demonstrate that Legilimens efficiently yields to foreground traffic and is agile enough to capture spare bandwidth when available

Network Analysis Identifies Crosstalk Interactions Governing TGF-β Signaling Dynamics during Endoderm Differentiation of Human Embryonic Stem Cells

The fate choice of human embryonic stem cells (hESCs) is controlled by complex signaling milieu synthesized by diverse chemical factors in the growth media. Prevalence of crosstalks and interactions between parallel pathways renders any analysis probing the process of fate transition of hESCs elusive. This work presents an important step in the evaluation of network level interactions between signaling molecules controlling endoderm lineage specification from hESCs using a statistical network identification algorithm. Network analysis was performed on detailed signaling dynamics of key molecules from TGF-β/SMAD, PI3K/AKT and MAPK/ERK pathways under two common endoderm induction conditions. The results show the existence of significant crosstalk interactions during endoderm signaling and they identify differences in network connectivity between the induction conditions in the early and late phases of signaling dynamics. Predicted networks elucidate the significant effect of modulation of AKT mediated crosstalk leading to the success of PI3K inhibition in inducing efficient endoderm from hESCs in combination with TGF-β/SMAD signaling

Marker Progression.

<p>A representative sample (based on <i>INS</i> expression) for each group was analyzed and compared to in-vivo <b>(A)</b> pancreatic development <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094307#pone.0094307-OliverKrasinski1" target="_blank">[24]</a> in order to identify which DE pathway modulation(s) lead to better resemblance to pancreatic organogenesis. Similarities can be observed when DE induction is achieved by modulation of <b>(B)</b> FGF2, <b>(C)</b> BMP4, <b>(D)</b> WNT3A and <b>(E)</b> PI3KI while we observed that marker progression greatly differs under BMP4 induction. The different stages of pancreatic development were grouped to represent the 3 stages of the differentiation protocol. Primitive gut endoderm (PGE) and prospective pancreatic endoderm (PPE) represent definitive endoderm induction (light green) pancreatic progenitor (PP) and early endocrine progenitors (EEP) represent pancreatic progenitor induction (medium green) and endocrine progenitors (EP), immature β- cells, mature β- cells (MC) represent the maturation stage (dark green).</p