"TORCing" neutrophil chemotaxis

Three-dimensional stochastic simulation of chemoattractant-mediated excitability in cells

During the last decade, a consensus has emerged that the stochastic triggering of an excitable system drives pseudopod formation and subsequent migration of amoeboid cells. The presence of chemoattractant stimuli alters the threshold for triggering this activity and can bias the direction of migration. Though noise plays an important role in these behaviors, mathematical models have typically ignored its origin and merely introduced it as an external signal into a series of reaction-diffusion equations. Here we consider a more realistic description based on a reaction-diffusion master equation formalism to implement these networks. In this scheme, noise arises naturally from a stochastic description of the various reaction and diffusion terms. Working on a three-dimensional geometry in which separate compartments are divided into a tetrahedral mesh, we implement a modular description of the system, consisting of G-protein coupled receptor signaling (GPCR), a local excitation-global inhibition mechanism (LEGI), and signal transduction excitable network (STEN). Our models implement detailed biochemical descriptions whenever this information is available, such as in the GPCR and G-protein interactions. In contrast, where the biochemical entities are less certain, such as the LEGI mechanism, we consider various possible schemes and highlight the differences between them. Our simulations show that even when the LEGI mechanism displays perfect adaptation in terms of the mean level of proteins, the variance shows a dose-dependence. This differs between the various models considered, suggesting a possible means for determining experimentally among the various potential networks. Overall, our simulations recreate temporal and spatial patterns observed experimentally in both wild-type and perturbed cells, providing further evidence for the excitable system paradigm. Moreover, because of the overall importance and ubiquity of the modules we consider, including GPCR signaling and adaptation, our results will be of interest beyond the field of directed migration.

Though the term noise usually carries negative connotations, it can also contribute positively to the characteristic dynamics of a system. In biological systems, where noise arises from the stochastic interactions between molecules, its study is usually confined to genetic regulatory systems in which copy numbers are small and fluctuations large. However, noise can have important roles when the number of signaling molecules is large. The extension of pseudopods and the subsequent motion of amoeboid cells arises from the noise-induced trigger of an excitable system. Chemoattractant signals bias this triggering thereby directing cell motion. To date, this paradigm has not been tested by mathematical models that account accurately for the noise that arises in the corresponding reactions. In this study, we employ a reaction-diffusion master equation approach to investigate the effects of noise. Using a modular approach and a three-dimensional cell model with specific subdomains attributed to the cell membrane and cortex, we explore the spatiotemporal dynamics of the system. Our simulations recreate many experimentally-observed cell behaviors thereby supporting the biased-excitable network hypothesis.

Proteomic and Transcriptomic Profiling Identifies Early Developmentally Regulated Proteins in Dictyostelium Discoideum

Cyclic AMP acts as a secondary messenger involving different cellular functions in eukaryotes. Here, proteomic and transcriptomic profiling has been combined to identify novel early developmentally regulated proteins in eukaryote cells. These proteomic and transcriptomic experiments were performed in Dictyostelium discoideum given the unique advantages that this organism offers as a eukaryotic model for cell motility and as a nonmammalian model of human disease. By comparing whole-cell proteome analysis of developed (cAMP-pulsed) wild-type AX2 cells and an independent transcriptomic analysis of developed wild-type AX4 cells, our results show that up to 70% of the identified proteins overlap in the two independent studies. Among them, we have found 26 proteins previously related to cAMP signaling and identified 110 novel proteins involved in calcium signaling, adhesion, actin cytoskeleton, the ubiquitin-proteasome pathway, metabolism, and proteins that previously lacked any annotation. Our study validates previous findings, mostly for the canonical cAMP-pathway, and also generates further insight into the complexity of the transcriptomic changes during early development. This article also compares proteomic data between parental and cells lacking glkA, a GSK-3 kinase implicated in substrate adhesion and chemotaxis in Dictyostelium. This analysis reveals a set of proteins that show differences in expression in the two strains as well as overlapping protein level changes independent of GlkA.

De- and repolarization mechanism of flagellar morphogenesis during a bacterial cell cycle

Eukaryotic morphogenesis is seeded with the establishment and subsequent amplification of polarity cues at key times during the cell cycle, often using (cyclic) nucleotide signals. We discovered that flagellum de- and repolarization in the model prokaryote Caulobacter crescentus is precisely orchestrated through at least three spatiotemporal mechanisms integrated at TipF. We show that TipF is a cell cycle-regulated receptor for the second messenger--bis-(3'-5')-cyclic dimeric guanosine monophosphate (c-di-GMP)--that perceives and transduces this signal through the degenerate c-di-GMP phosphodiesterase (EAL) domain to nucleate polar flagellum biogenesis. Once c-di-GMP levels rise at the G1 → S transition, TipF is activated, stabilized, and polarized, enabling the recruitment of downstream effectors, including flagellar switch proteins and the PflI positioning factor, at a preselected pole harboring the TipN landmark. These c-di-GMP-dependent events are coordinated with the onset of tipF transcription in early S phase and together enable the correct establishment and robust amplification of TipF-dependent polarization early in the cell cycle. Importantly, these mechanisms also govern the timely removal of TipF at cell division coincident with the drop in c-di-GMP levels, thereby resetting the flagellar polarization state in the next cell cycle after a preprogrammed period during which motility must be suspended.

Mast cell chemotaxis - chemoattractants and signaling pathways

Migration of mast cells is essential for their recruitment within target tissues where they play an important role in innate and adaptive immune responses. These processes rely on the ability of mast cells to recognize appropriate chemotactic stimuli and react to them by a chemotactic response. Another level of intercellular communication is attained by production of chemoattractants by activated mast cells, which results in accumulation of mast cells and other hematopoietic cells at the sites of inflammation. Mast cells express numerous surface receptors for various ligands with properties of potent chemoattractants. They include the stem cell factor (SCF) recognized by c-Kit, antigen, which binds to immunoglobulin E (IgE) anchored to the high affinity IgE receptor (FcεRI), highly cytokinergic (HC) IgE recognized by FcεRI, lipid mediator sphingosine-1-phosphate (S1P), which binds to G protein-coupled receptors (GPCRs). Other large groups of chemoattractants are eicosanoids [prostaglandin E₂ and D₂, leukotriene (LT) B₄, LTD₄, and LTC₄, and others] and chemokines (CC, CXC, C, and CX3C), which also bind to various GPCRs. Further noteworthy chemoattractants are isoforms of transforming growth factor (TGF) β1–3, which are sensitively recognized by TGF-β serine/threonine type I and II β receptors, adenosine, C1q, C3a, and C5a components of the complement, 5-hydroxytryptamine, neuroendocrine peptide catestatin, tumor necrosis factor-α, and others. Here we discuss the major types of chemoattractants recognized by mast cells, their target receptors, as well as signaling pathways they utilize. We also briefly deal with methods used for studies of mast cell chemotaxis and with ways of how these studies profited from the results obtained in other cellular systems.

Signaling mechanisms for chemotaxis

Cells recognize external chemical gradients and translate these environmental cues into amplified intracellular signaling that results in elongated cell shape, actin polymerization toward the leading edge, and movement along the gradient. Mechanisms underlying chemotaxis are conserved evolutionarily from Dictyostelium amoeba to mammalian neutrophils. Recent studies have uncovered several parallel intracellular signaling pathways that crosstalk in chemotaxing cells. Here, we review these signaling mechanisms in Dictyostelium discoideum.