Relating topology and dynamics in cell signaling networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 153-163).Cells are constantly bombarded with stimuli that they must sense, process, and interpret to make decisions. This capability is provided by interconnected signaling pathways. Many of the components and interactions within pathways have been identified, and it is becoming clear that the precise dynamics they generate are necessary for proper system function. However, our understanding of how pathways are interconnected to drive decisions is limited. We must overcoming this limitation to develop interventions that can fine tune a cell decision by modulating specific features of its constituent pathway's dynamics. How can we quantatively map a whole cell decision process? Answering this question requires addressing challenges at three scales: the detailed biochemistry of protein-protein interactions, the complex, interlocked feedback loops of transcriptionally regulated signaling pathways, and the multiple mechanisms of connection that link distinct pathways together into a full cell decision process. In this thesis, we address challenges at each level. We develop new computational approaches for identifying the interactions driving dynamics in protein-protein networks. Applied to the cyanobacterial clock, these approaches identify two coupled motifs that together provide independent control over oscillation phase and period. Using the p53 pathway as a model transcriptional network, we experimentally isolate and characterize dynamics from a core feedback loop in individual cells. A quantitative model of this signaling network predicts and rationalizes the distinct effects on dynamics of additional feedback loops and small molecule inhibitors. Finally, we demonstrated the feasibility of combining individual pathway models to map a whole cell decision: cell cycle arrest elicited by the mammalian DNA damage response. By coupling modeling and experiments, we used this combined perspective to uncover some new biology. We found that multiple arrest mechanisms must work together in a proper cell cycle arrest, and identified a new role for p21 in preventing G2 arrest, paradoxically through its action on G1 cyclins. This thesis demonstrates that we can quantitatively map the logic of cellular decisions, affording new insight and revealing points of control.by Jared E. Toettcher.Ph.D

Stochastic Gene Expression in a Lentiviral Positive Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity

Stochastic gene expression has been implicated in a variety of cellular processes, including cell differentiation and disease. In this issue of Cell, Weinberger et al. (2005) take an integrated computational-experimental approach to study the Tat transactivation feedback loop in HIV-1 and show that fluctuations in a key regulator, Tat, can result in a phenotypic bifurcation. This phenomenon is observed in an isogenic population where individual cells display two distinct expression states corresponding to latent and productive infection by HIV-1. These findings demonstrate the importance of stochastic gene expression in molecular "decision-making."Comment: Supplemental data available as q-bio.MN/060800

Supplemental Data: Stochastic Gene Expression in a Lentiviral Positive Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity

Supplemental data for "Stochastic Gene Expression in a Lentiviral Positive Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity" [q-bio.MN/0608002, Cell. 2005 Jul 29;122(2):169-82].Comment: Supplemental data for q-bio.MN/060800

Unraveling the Mechanism of a LOV Domain Optogenetic Sensor:A Glutamine Lever Induces Unfolding of the Jα Helix

Light-activated protein domains provide a convenient, modular, and genetically encodable sensor for optogenetics and optobiology. Although these domains have now been deployed in numerous systems, the precise mechanism of photoactivation and the accompanying structural dynamics that modulate output domain activity remain to be fully elucidated. In the C-terminal light-oxygen-voltage (LOV) domain of plant phototropins (LOV2), blue light activation leads to formation of an adduct between a conserved Cys residue and the embedded FMN chromophore, rotation of a conserved Gln (Q513), and unfolding of a helix (Jα-helix) which is coupled to the output domain. In the present work, we focus on the allosteric pathways leading to Jα helix unfolding in Avena sativa LOV2 (AsLOV2) using an interdisciplinary approach involving molecular dynamics simulations extending to 7 μs, time-resolved infrared spectroscopy, solution NMR spectroscopy, and in-cell optogenetic experiments. In the dark state, the side chain of N414 is hydrogen bonded to the backbone N-H of Q513. The simulations predict a lever-like motion of Q513 after Cys adduct formation resulting in a loss of the interaction between the side chain of N414 and the backbone C═O of Q513, and formation of a transient hydrogen bond between the Q513 and N414 side chains. The central role of N414 in signal transduction was evaluated by site-directed mutagenesis supporting a direct link between Jα helix unfolding dynamics and the cellular function of the Zdk2-AsLOV2 optogenetic construct. Through this multifaceted approach, we show that Q513 and N414 are critical mediators of protein structural dynamics, linking the ultrafast (sub-ps) excitation of the FMN chromophore to the microsecond conformational changes that result in photoreceptor activation and biological function

Signaling Dynamics Control Cell Fate in the Early Drosophila Embryo.

The Erk mitogen-activated protein kinase plays diverse roles in animal development. Its widespread reuse raises a conundrum: when a single kinase like Erk is activated, how does a developing cell know which fate to adopt? We combine optogenetic control with genetic perturbations to dissect Erk-dependent fates in the early Drosophila embryo. We find that Erk activity is sufficient to "posteriorize" 88% of the embryo, inducing gut endoderm-like gene expression and morphogenetic movements in all cells within this region. Gut endoderm fate adoption requires at least 1 h of signaling, whereas a 30-min Erk pulse specifies a distinct ectodermal cell type, intermediate neuroblasts. We find that the endoderm-ectoderm cell fate switch is controlled by the cumulative load of Erk activity, not the duration of a single pulse. The fly embryo thus harbors a classic example of dynamic control, where the temporal profile of Erk signaling selects between distinct physiological outcomes

Illuminating developmental biology with cellular optogenetics.

In developmental biology, localization is everything. The same stimulus –a cell signaling event or expression of a gene – can have dramatically different effects depending on the time, spatial position, and cell types in which it is applied. Yet the field has long lacked the ability to deliver localized perturbations with high specificity in vivo. The advent of optogenetic tools, capable of delivering highly localized stimuli, is thus poised to profoundly expand our understanding of development. We describe the current state-of-the-art in cellular optogenetic tools, review the first wave of major studies showcasing their application in vivo, and discuss major obstacles that must be overcome if the promise of developmental optogenetics is to be fully realized

A bright future: optogenetics to dissect the spatiotemporal control of cell behavior.

Cells sense, process, and respond to extracellular information using signaling networks: collections of proteins that act as precise biochemical sensors. These protein networks are characterized by both complex temporal organization, such as pulses of signaling activity, and by complex spatial organization, where proteins assemble structures at particular locations and times within the cell. Yet despite their ubiquity, studying these spatial and temporal properties has remained challenging because they emerge from the entire protein network rather than a single node, and cannot be easily tuned by drugs or mutations. These challenges are being met by a new generation of optogenetic tools capable of directly controlling the activity of individual signaling nodes over time and the assembly of protein complexes in space. Here, we outline how these recent innovations are being used in conjunction with engineering-influenced experimental design to address longstanding questions in signaling biology

Optogenetic Reconstitution for Determining the Form and Function of Membraneless Organelles

It has recently become clear that large-scale macromolecular self-assembly is a rule, rather than an exception, of intracellular organization. A growing number of proteins and RNAs have been shown to self-assemble into micrometer-scale clusters that exhibit either liquid-like or gel-like properties. Given their proposed roles in intracellular regulation, embryo development, and human disease, it is becoming increasingly important to understand how these membraneless organelles form and to map their functional consequences for the cell. Recently developed optogenetic systems make it possible to acutely control cluster assembly and disassembly in live cells, driving the separation of proteins of interest into liquid droplets, hydrogels, or solid aggregates. Here we propose that these approaches, as well as their evolution into the next generation of optogenetic biophysical tools, will allow biologists to determine how the self-assembly of membraneless organelles modulates diverse biochemical processes

Light-switchable transcription factors obtained by direct screening in mammalian cells

Abstract Optogenetic tools can provide fine spatial and temporal control over many biological processes. Yet the development of new light-switchable protein variants remains challenging, and the field still lacks general approaches to engineering or discovering protein variants with light-switchable biological functions. Here, we adapt strategies for protein domain insertion and mammalian-cell expression to generate and screen a library of candidate optogenetic tools directly in mammalian cells. The approach is based on insertion of the AsLOV2 photoswitchable domain at all possible positions in a candidate protein of interest, introduction of the library into mammalian cells, and light/dark selection for variants with photoswitchable activity. We demonstrate the approach’s utility using the Gal4-VP64 transcription factor as a model system. Our resulting LightsOut transcription factor exhibits a > 150-fold change in transcriptional activity between dark and blue light conditions. We show that light-switchable function generalizes to analogous insertion sites in two additional Cys6Zn2 and C2H2 zinc finger domains, providing a starting point for optogenetic regulation of a broad class of transcription factors. Our approach can streamline the identification of single-protein optogenetic switches, particularly in cases where structural or biochemical knowledge is limited

Using optogenetics to interrogate the dynamic control of signal transmission by the Ras/Erk module

SUMMARY The complex, interconnected architecture of cellsignaling networks makes it challenging to disentangle how cells process extracellular information to make decisions. We have developed an optogenetic approach to selectively activate isolated intracellular signaling nodes with light and use this method to follow the flow of information from the signaling protein Ras. By measuring dose and frequency responses in single cells, we characterize the precision, timing, and efficiency with which signals are transmitted from Ras to Erk. Moreover, we elucidate how a single pathway can specify distinct physiological outcomes: by combining distinct temporal patterns of stimulation with proteomic profiling, we identify signaling programs that differentially respond to Ras dynamics, including a paracrine circuit that activates STAT3 only after persistent (>1 hr) Ras activation. Optogenetic stimulation provides a powerful tool for analyzing the intrinsic transmission properties of pathway modules and identifying how they dynamically encode distinct outcomes