Deciphering the Dynamical Origin of Mixed Population during Neural Stem Cell Development.

Neural stem cells (NSCs) often give rise to a mixed population of cells during differentiation. However, the dynamical origin of these mixed states is poorly understood. In this article, our mathematical modeling study demonstrates that the bone morphogenetic protein 2 (BMP2) mediated disparate differentiation dynamics of NSCs in central and peripheral nervous systems essentially function through two distinct bistable switches that are mutually interconnected via a mushroom-like bifurcation. Stochastic simulations of the model reveal that the mixed population originates due to the existence of these bistable switching regulations and that the maintenance of such mixed states depends on the level of stochastic fluctuations of the system. It further demonstrates that due to extrinsic variability, cells in an NSC population can dynamically transit from mushroom to a unique isola kind of bifurcation state, which essentially extends the range of the BMP2-driven mixed population state during differentiation. Importantly, the model predicts that by individually altering the expression level of key regulatory proteins, the NSCs can be converted entirely to a preferred phenotype for BMP2 doses that previously resulted in a mixed population. Our findings show that efficient neuronal regeneration can be achieved by systematically maneuvering the differentiation dynamics.

Subversion of innate immune responses by Brucella through the targeted degradation of the TLR signaling adapter, MAL.

Gram-negative bacteria belonging to the Brucella species cause chronic infections that can result in undulant fever, arthritis, and osteomyelitis in humans. Remarkably, Brucella sp. genomes encode a protein, named TcpB, that bears significant homology with mammalian Toll/IL-1 receptor domains and whose expression causes degradation of the phosphorylated, signal competent form of the adapter MyD88-adapter-like (MAL). This effect of TcpB is mediated through its box 1 region and has no effect on other TLR adapter proteins such as MyD88 or TIR-domain containing adapter protein-inducing IFNbeta. TcpB also does not affect a mutant, signal-incompetent form of MAL that cannot be phosphorylated. Interestingly, the presence of TcpB leads to enhanced polyubiquitination of MAL, which is likely responsible for its accelerated degradation. A Brucella abortus mutant lacking TcpB fails to reduce levels of MAL in infected macrophages. Therefore, TcpB represents a unique pathogen-derived molecule that suppresses host innate-immune responses by specifically targeting an individual adapter molecule in the TLR signaling pathway for degradation.

Deciphering the Role of Fluctuation Dependent Intercellular Communication in Neural Stem Cell Development.

Neural stem cells (NPCs) efficiently communicate in an intercellular manner to govern specific cell fate decisions during the developmental process despite withstanding the fluctuating cellular environment. How these fluctuations from diverse origins functionally affect the precise cell fate decision making remains elusive. By taking a stochastic mathematical modeling approach, we unravel that the transcriptional variability arising within an NPC population due to intermittent cell cycle events significantly influences the neuron to NPC ratio during development. Our model proficiently quantifies the impact of different sources of heterogeneities in maintaining an exact neuron to NPC ratio and predicts plausible experimental ways to fine-tune the development of NPCs. In the future, these modeling insights may lead to better therapeutic avenues to regenerate neurons from NPCs.

Alteration in MicroRNA Expression Governs the Nature and Timing of Cellular Fate Commitment.

In the central nervous system, the expression level of transcriptional repressor Hes1 (hairy and enhancer of split-1) tightly controls the alternative cell fate commitment during differentiation as well as the time required for such cellular transitions. A microRNA, miR-9, that interacts with Hes1 in a mutually antagonistic manner, influences both the process of lineage specification and timing of differentiation significantly, but the impact of the miR-9 in guiding these events still remains poorly understood. Here, we proposed a stochastic mathematical model of the miR-9/Hes1 double-negative feedback interaction network that at the outset shows how alternative cell fate such as quiescence, progenitor, and neuronal states can be accomplished through fine-tuning the Hes1 dynamics by altering the expression level of miR-9. The model simulations further foretell a correlated variation of the period of oscillation of Hes1, and the time delay observed between Hes1 mRNA and protein as the transcription rate of miR-9 increases during the neural progenitor state attainment. Importantly, the model simulations aided by the systematic sensitivity analysis predict that the timing of differentiation to the neuronal state crucially depends on the negative regulators (miR-9 and Hes6) of the Hes1. Our results indicate that miR-9/Hes1 interaction network can be effectively exploited for an efficient and well-timed neuronal transformation.

Alteration in microRNA-17-92 dynamics accounts for differential nature of cellular proliferation.

MicroRNAs associated with the mir-17-92 cluster are crucial regulators of the mammalian cell cycle, as they inhibit transcription factors related to the E2F family that tightly control decision-making events for a cell to commit for active cellular proliferation. Intriguingly, in many solid cancers, these mir-17-92 cluster members are overexpressed, whereas in some hematopoietic cancers they are down-regulated. Our proposed model of the Myc/E2F/mir-17-92 network demonstrates that the differential expression pattern of mir-17-92 in different cell types can be conceived due to having a contrasting E2F dynamics induced by mir-17-92. The model predicts that by explicitly altering the mir-17-92-related part of the network, experimentally it is possible to control cellular proliferation in a cell type-dependent manner for therapeutic intervention.

Disproportionate feedback interactions govern cell-type specific proliferation in mammalian cells.

In mammalian cells, the decision to maintain quiescence over proliferation commitment during G1 -S transition depends on more than one intertwined feedback interaction and is highly cell-type dependent. However, the precise role played by these individual feedback regulations in organizing such diverse proliferation dynamics is still poorly understood. Herein, we propose a predictive mathematical model of G1 -S transition in mammalian cells that reconciles distinct single-cell experimental observations in a cell-type specific manner. The model analysis reveals that the feedback motifs responsible for the G1 -S transition act in a disparate fashion to organize the cell-type specific proliferation response. Importantly, the proposed model can be effectively tuned to gain insights into the proliferation commitment of diverse mammalian cell types and can find wide applicability.

Unraveling the differential dynamics of developmental fate in central and peripheral nervous systems.

Bone morphogenetic protein 2 (BMP2), differentially regulates the developmental lineage commitment of neural stem cells (NSC's) in central and peripheral nervous systems. However, the precise mechanism beneath such observations still remains illusive. To decipher the intricacies of this mechanism, we propose a generic mathematical model of BMP2 driven differentiation regulation of NSC's. The model efficiently captures the dynamics of the wild-type as well as various mutant and over-expression phenotypes for NSC's in central nervous system. Our model predicts that the differential developmental dynamics of the NSC's in peripheral nervous system can be reconciled by altering the relative positions of the two mutually interconnected bi-unstable switches inherently present in the steady state dynamics of the crucial developmental fate regulatory proteins as a function of BMP2 dose. This model thus provides a novel mechanistic insight and has the potential to deliver exciting therapeutic strategies for neuronal regeneration from NSC's of different origin.

Are Quasi-Steady-State Approximated Models Suitable for Quantifying Intrinsic Noise Accurately?

Large gene regulatory networks (GRN) are often modeled with quasi-steady-state approximation (QSSA) to reduce the huge computational time required for intrinsic noise quantification using Gillespie stochastic simulation algorithm (SSA). However, the question still remains whether the stochastic QSSA model measures the intrinsic noise as accurately as the SSA performed for a detailed mechanistic model or not? To address this issue, we have constructed mechanistic and QSSA models for few frequently observed GRNs exhibiting switching behavior and performed stochastic simulations with them. Our results strongly suggest that the performance of a stochastic QSSA model in comparison to SSA performed for a mechanistic model critically relies on the absolute values of the mRNA and protein half-lives involved in the corresponding GRN. The extent of accuracy level achieved by the stochastic QSSA model calculations will depend on the level of bursting frequency generated due to the absolute value of the half-life of either mRNA or protein or for both the species. For the GRNs considered, the stochastic QSSA quantifies the intrinsic noise at the protein level with greater accuracy and for larger combinations of half-life values of mRNA and protein, whereas in case of mRNA the satisfactory accuracy level can only be reached for limited combinations of absolute values of half-lives. Further, we have clearly demonstrated that the abundance levels of mRNA and protein hardly matter for such comparison between QSSA and mechanistic models. Based on our findings, we conclude that QSSA model can be a good choice for evaluating intrinsic noise for other GRNs as well, provided we make a rational choice based on experimental half-life values available in literature.