Analyzing and engineering cell signaling modules with synthetic biology

Synthetic biology of B cell activation: understanding signal amplification at the B cell antigen receptor using a rebuilding approach

Upon activation of the B cell antigen receptor (BCR), the spleen tyrosine kinase (Syk) and the Src family kinase Lyn phosphorylate tyrosines of the immunoreceptor tyrosine-based activation motif (ITAM) of Igα and Igβ which further serve as binding sites for the SH2 domains of these kinases. Using a synthetic biology approach, we dissect the roles of different ITAM residues of Igα in Syk activation. We found that a leucine to glycine mutation at the Y+3 position after the first ITAM tyrosine prevents Syk binding and activation. However, a pre-activated Syk can still phosphorylate this tyrosine in trans. Our data show that the formation of a Syk/ITAM initiation complex and trans-ITAM phosphorylation is crucial for BCR signal amplification. In contrast, the interaction of Lyn with the first ITAM tyrosine is not altered by the leucine to glycine mutation. In addition, our study suggests that an ITAM-bound Syk phosphorylates the non-ITAM tyrosine Y204 of Igα only in cis. Collectively, our reconstitution experiments suggest a model whereby first trans-phosphorylation amplifies the BCR signal and subsequently cis-phosphorylation couples the receptor to downstream signaling elements.

Combining in silico evolution and nonlinear dimensionality reduction to redesign responses of signaling networks

The rational design of network behavior is a central goal of synthetic biology. Here, we combine in silico evolution with nonlinear dimensionality reduction to redesign the responses of fixed-topology signaling networks and to characterize sets of kinetic parameters that underlie various input-output relations. We first consider the earliest part of the T cell receptor (TCR) signaling network and demonstrate that it can produce a variety of input-output relations (quantified as the level of TCR phosphorylation as a function of the characteristic TCR binding time). We utilize an evolutionary algorithm (EA) to identify sets of kinetic parameters that give rise to: (i) sigmoidal responses with the activation threshold varied over 6 orders of magnitude, (ii) a graded response, and (iii) an inverted response in which short TCR binding times lead to activation. We also consider a network with both positive and negative feedback and use the EA to evolve oscillatory responses with different periods in response to a change in input. For each targeted input-output relation, we conduct many independent runs of the EA and use nonlinear dimensionality reduction to embed the resulting data for each network in two dimensions. We then partition the results into groups and characterize constraints placed on the parameters by the different targeted response curves. Our approach provides a way (i) to guide the design of kinetic parameters of fixed-topology networks to generate novel input-output relations and (ii) to constrain ranges of biological parameters using experimental data. In the cases considered, the network topologies exhibit significant flexibility in generating alternative responses, with distinct patterns of kinetic rates emerging for different targeted responses.

Biosynthetic infochemical communication

There is an ever-increasing demand for data to be embedded in our environment at ever-decreasing temporal and spatial scales. Whilst current communication and storage technologies generally exploit the electromagnetic properties of media, chemistry offers us a new alternative for nanoscale signaling using molecules as messengers with high information content. Biological systems effectively overcome the challenges of chemical communication using highly specific biosynthetic pathways for signal generation together with specialized protein receptors and nervous systems. Here we consider a new approach for information transmission based upon nature's quintessential example of infochemical communication, the moth pheromone system. To approach the sensitivity, specificity and versatility of infochemical communication seen in nature, we describe an array of biologically-inspired technologies for the production, transmission, detection, and processing of molecular signals. We show how it is possible to implement each step of the moth pheromone pathway for biosynthesis, transmission, receptor protein binding/transduction, and antennal lobe processing of monomolecular and multimolecular signals. For each implemented step, we discuss the value, current limitations, and challenges for the future development and integration of infochemical communication technologies. Together, these building blocks provide a starting point for future technologies that can utilize programmable emission and detection of multimolecular information for a new and robust means of communicating chemical information.

A network characteristic that correlates environmental and genetic robustness

As scientific advances in perturbing biological systems and technological advances in data acquisition allow the large-scale quantitative analysis of biological function, the robustness of organisms to both transient environmental stresses and inter-generational genetic changes is a fundamental impediment to the identifiability of mathematical models of these functions. An approach to overcoming this impediment is to reduce the space of possible models to take into account both types of robustness. However, the relationship between the two is still controversial. This work uncovers a network characteristic, transient responsiveness, for a specific function that correlates environmental imperturbability and genetic robustness. We test this characteristic extensively for dynamic networks of ordinary differential equations ranging up to 30 interacting nodes and find that there is a power-law relating environmental imperturbability and genetic robustness that tends to linearity as the number of nodes increases. Using our methods, we refine the classification of known 3-node motifs in terms of their environmental and genetic robustness. We demonstrate our approach by applying it to the chemotaxis signaling network. In particular, we investigate plausible models for the role of CheV protein in biochemical adaptation via a phosphorylation pathway, testing modifications that could improve the robustness of the system to environmental and/or genetic perturbation.

Advances in the ways that living systems can be perturbed in order to study how they function and sharp reductions in the cost of computer resources have allowed the collection of large amounts of data. The aim of biological system modeling is to analyze this data in order to pin down the precise interactions of molecules that underlie the observed functions. This is made difficult due to two features of biological systems: (1) Living things do not show an appreciable loss of function across large ranges of environmental factors. (2) Their function is inherited from parent to child more or less unchanged in spite of random mutations in genetic sequences. We find that these two features are more correlated in a specific subset of networks and show how to use this observation to find networks in which these two features appear together. Working within this smaller space of networks may make it easier to find suitable underlying models from data.

Synthetic biology: lessons from engineering yeast MAPK signalling pathways

All living cells respond to external stimuli and execute specific physiological responses through signal transduction pathways. Understanding the mechanisms controlling signalling pathways is important for diagnosing and treating diseases and for reprogramming cells with desired functions. Although many of the signalling components in the budding yeast Saccharomyces cerevisiae have been identified by genetic studies, many features concerning the dynamic control of pathway activity, cross-talk, cell-to-cell variability or robustness against perturbation are still incompletely understood. Comparing the behaviour of engineered and natural signalling pathways offers insight complementary to that achievable with standard genetic and molecular studies. Here, we review studies that aim at a deeper understanding of signalling design principles and generation of novel signalling properties by engineering the yeast mitogen-activated protein kinase (MAPK) pathways. The underlying approaches can be applied to other organisms including mammalian cells and offer opportunities for building synthetic pathways and functionalities useful in medicine and biotechnology.