On a stochastic approach to model the double phosphorylation/dephosphorylation cycle

Because of the unavoidable intrinsic noise affecting biochemical processes, astochastic approach is usually preferred whenever a deterministic model givestoo rough information or, worse, may lead to erroneous qualitative behaviorsand/or quantitatively wrong results. In this work we focus on the chemicalmaster equation (CME)-based method which provides an accurate stochasticdescription of complex biochemical reaction networks in terms of the probabilitydistribution of the underlying chemical populations. Indeed, deterministic mod-els can be dealt with as first-order approximations of the average-value dynamicscoming from the stochastic CME approach. Here we investigate the double phos-phorylation/dephosphorylation cycle, a well-studied enzymatic reaction networkwhere the inherent double time scale requires one to exploit quasisteady stateapproximation (QSSA) approaches to infer qualitative and quantitative informa-tion. Within the deterministic realm, several researchers have deeply investi-gated the use of the proper QSSA, agreeing to highlight that only one type ofQSSA (the total QSSA) is able to faithfully replicate the qualitative behaviorof bistability occurrences, as well as the correct assessment of the equilibriumpoints, accordingly to the not approximated (full) model. Based on recent resultsproviding CME solutions that do not resort to Monte Carlo simulations, the pro-posed stochastic approach shows some counterintuitive facts arising when tryingto straightforwardly transfer bistability deterministic results into the stochasticrealm, and suggests how to handle such cases according to both theoretical andnumerical results

Induction and Maintenance of Synaptic Plasticity

Synaptic long-term modifications following neuronal activation are believed to be at the origin of learning and long-term memory. Recent experiments suggest that these long-term synaptic changes are all-or-none switch-like events between discrete states of a single synapse. The biochemical network involving calcium/calmodulin-dependent protein kinase II (CaMKII) and its regulating protein signaling cascade has been hypothesized to durably maintain the synaptic state in form of a bistable switch. Furthermore, it has been shown experimentally that CaMKII and associated proteins such as protein kinase A and calcineurin are necessary for the induction of long-lasting increases (long-term potentiation, LTP) and/or long-lasting decreases (long-term depression, LTD) of synaptic efficacy. However, the biochemical mechanisms by which experimental LTP/LTD protocols lead to corresponding transitions between the two states in realistic models of such networks are still unknown. We present a detailed biochemical model of the calcium/calmodulin-dependent autophosphorylation of CaMKII and the protein signaling cascade governing the dephosphorylation of CaMKII. As previously shown, two stable states of the CaMKII phosphorylation level exist at resting intracellular calcium concentrations. Repetitive high calcium levels switch the system from a weakly- to a highly phosphorylated state (LTP). We show that the reverse transition (LTD) can be mediated by elevated phosphatase activity at intermediate calcium levels. It is shown that the CaMKII kinase-phosphatase system can qualitatively reproduce plasticity results in response to spike-timing dependent plasticity (STDP) and presynaptic stimulation protocols. A reduced model based on the CaMKII system is used to elucidate which parameters control the synaptic plasticity outcomes in response to STDP protocols, and in particular how the plasticity results depend on the differential activation of phosphatase and kinase pathways and the level of noise in the calcium transients. Our results show that the protein network including CaMKII can account for (i) induction - through LTP/LTD-like transitions - and (ii) storage - due to its bistability - of synaptic changes. The model allows to link biochemical properties of the synapse with phenomenological 'learning rules' used by theoreticians in neural network studies

Regulatory Mechanisms of Bacterial Stress Responses

Bacterial growth and survival critically hinges on the ability to rapidly adapt to ever-changing environmental conditions. Elaborated stress response systems allow bacteria to sensitively detect and adequately respond to fluctuations in environmental conditions, such as pH, temperature, osmolarity, or the concentrations of nutrients and harmful substances. Often, bacterial stress responses towards a specific stressor involve multiple interconnected mechanisms - controlled by a sophisticated network involving signal-transduction cascades, metabolic pathways and gene expression regulation. In this thesis, bacterial stress responses towards two different environmental stressors are analysed; mainly focussing on the regulatory mechanisms that give rise to the overall cellular response. The first part of this thesis addresses the heme stress response in Corynebacterium glutamucim. Heme is an essential cofactor and alternative iron source for almost all bacterial species but can cause severe toxicity when present in elevated concentrations. Consequently, heme homeostasis needs to be tightly controlled. Therefore, one important challenge is to understand how bacteria regulate heme stress responses to both benefit from heme while simultaneously eliminating the associated toxicity. It is shown that C. glutamicum induces a heme detoxification mechanism (mediated via the heme exporter HrtBA) and a heme utilization mechanism (mediated via the heme ogygenase HmuO) in a temporal hierarchy, with prioritisation of detoxification over utilization. A combined approach of experimental reporter profiling and computational modelling reveals how differential biochemical properties of the two two-component systems that sense heme in C. glutamicum - ChrSA and HrrSA - and an additional regulator (the global iron-regulator DtxR) control this hierarchical expression of the two stress response modules. This analysis sheds light on the multi-layered heme stress response that contributes to overall heme homeostasis in C. glutamicum and adds on to the understanding of bacterial strategies to deal with the Janus-faced nature of heme. The second part of this thesis focusses on bacterial response strategies towards cell wall antibiotics, which play a key role in bacterial antibiotic resistance. To combat resistance evolution, it is important to understand how cell wall antibiotics affect bacterial cell wall biosynthesis and how bacteria orchestrate stress response mechanisms to protect themselves from cell wall damage. The first question is addressed through a comprehensive mathematical model describing the bacterial cell wall synthetic pathway - the lipid II cycle - and its systems-level behaviour under antibiotic treatment. It is found that the lipid II cycle features a highly asymmetric distribution of pathway intermediates and that the efficacy of antibiotics in vivo scales directly with the abundance of targeted pathway intermediates: The lower the relative abundance of a lipid II intermediate within the lipid II cycle, the lower the in vivo efficacy of an antibiotic targeting this intermediate. This leads to the formulation of a novel principle of ‘minimal target exposure’ as an intrinsic bacterial resistance mechanism and it is demonstrated that cooperativity in drug-target binding can mitigate the associated resistance. The development of new drugs to counteract antibiotic resistance clearly benefit from these insights. The second question is then addresses by an experimental-based expansion of the model, which allows the analysis of the interplay between multiple stress response mechanisms that protect against a single antibiotic - focussing here on the well-studied response of Bacillus subtilis towards the cell wall antibiotic bacitracin. This study reveals that the properties of the lipid II cycle itself control the interaction between the primary bacitracin stress response determinant BceAB mediating bacitracin detoxification, and the secondary determinant BcrC, which contributes to cell wall homeostasis under bacitracin treatment. By elucidating regulatory mechanisms of the multi-layered response towards bacitracin, this analysis contributes to an advanced understanding of bacterial antibiotic resistance

Understanding MAPK signaling pathways in apoptosis

MAPK (mitogen-activated protein kinase) signaling pathways regulate a variety of biological processes through multiple cellular mechanisms. In most of these processes, such as apoptosis, MAPKs have a dual role since they can act as activators or inhibitors, depending on the cell type and the stimulus. In this review, we present the main pro-and anti-apoptotic mechanisms regulated by MAPKs, as well as the crosstalk observed between some MAPKs. We also describe the basic signaling properties of MAPKs (ultrasensitivity, hysteresis, digital response), and the presence of different positive feedback loops in apoptosis. We provide a simple guide to predict MAPKs' behavior, based on the intensity and duration of the stimulus. Finally, we consider the role of MAPKs in osmostress-induced apoptosis by using Xenopus oocytes as a cell model. As we will see, apoptosis is plagued with multiple positive feedback loops. We hope this review will help to understand how MAPK signaling pathways engage irreversible cellular decisions

WNK1-dependent osmoregulation in CD4⁺ T cell activation

CD4+ T cell activation is critical for the initiation of the adaptive immune response. In particular, through the provision of help to B cells, CD4+ T cells are essential for the generation of high-affinity, class-switched antibodies specific for epitopes on invading pathogens. CD4+ T cells also augment the activation of CD8+ cytotoxic T lymphocytes and modulate the effector function of innate immune cells. These features of the immune response are essential for the clearance of many pathogens and are conditional on the ability of a small population of antigen-specific CD4+ T cells to rapidly expand in response to antigenic challenge. In this study we show that this expansion is strongly dependent on the activity of the WNK1 kinase, and that in the absence of WNK1, CD4+ T cells are unable to support a class-switched antibody response. WNK1 has been extensively studied in the distal nephron of the kidney, where it regulates ion transport, and consequently blood pressure, via the STK39 and OXSR1 kinases and the SLC12A-family of ion co-transporters. Here we show that this osmoregulatory function of WNK1 is required for TCR signalling in CD4+ T cells and the subsequent entry of these cells into G1 phase of the cell cycle. Furthermore, having entered the cell cycle, WNK1-deficient T cells show a reduced rate of DNA replication and activate the ATR-mediated cell cycle checkpoint, resulting in a G2/M blockade. CD4+ T cells carrying mutations in both Oxsr1 and Stk39 phenocopy WNK1-deficient T cells, although the defects in TCR-induced proliferation are less severe. Taken together, these data suggest that WNK1 regulates cell cycle progression via the OXSR1 and STK39 signalling pathways, as well as via another, non-canonical pathway. Importantly, the defective TCR signalling and G1 entry exhibited by WNK1-deficient CD4+ T cells can be rescued by activating the cells in hypotonic medium. These novel findings reveal fundamental roles for WNK1 activity and transmembrane water movement in antigen receptor signalling and cell cycle dynamics

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

A Study of Human Genomic Variants of a Microtuble and Kinetochore Associated Protein Astrin.

PhD Theses.During cell division, chromosomes are captured by microtubules via a multiprotein complex called the kinetochore. Genomic variations in kinetochore proteins can cause pregnancy loss and developmental defects such as primary microcephaly and cancer-susceptible disorder mosaic variegated aneuploidy. The kinetochore protein Astrin is specifically recruited to kinetochores following their attachment to microtubule-ends, and its arrival stabilizes chromosome-microtubule attachments. Human genomic variations in Astrin are known, but their impact on chromosome segregation has not been studied. I have used a combination of cell biology techniques to study the impact of Astrin variants- p.Q1012* and p.L7Qfs*21 - identified in a screen of healthy individuals and Astrin p.E755K found in cancer cells. I have shown that the Astrin p.Q1012* variant normally localizes at spindle microtubules but not kinetochores. Moreover, p.Q1012* expression prolongs mitosis and induces chromosome congression and segregation defects. Consistent with the defects observed, Astrin p.Q1012* expressing metaphase cells display an active spindle assembly checkpoint and reduced microtubule pulling forces. Additionally, Astrin p.Q1012* overexpression impairs the kinetochore localization of endogenous Astrin-SKAP complex suggesting a dominant-negative phenotype. To explore the impact of the Astrin p.L7Qfs*21 variant, I introduced a stop codon at 7 a.a in Astrin-GFP and show that Astrin p.L7* expresses as a shorter protein. Next, I generated N-terminal deletions of Astrin (Δ151 and Δ274), mimicking new transcriptional start sites; these deletion mutants localize normally at spindle microtubules and kinetochores. Moreover, Astrin Δ151 migrates similarly to the short p.L7* on an immunoblot, suggesting that p.M152 and not p.M275 is the new start site in Astrin p.L7*. Lastly, I have shown that the cancer-associated Astrin p.E755K normally localizes at spindle microtubules and kinetochores. In summary, unlike the p.Q1012* variant, the other two variants localize normally during mitosis. My findings explain the occurrence of Astrin p.L7Qfs*21, but not p.Q1012, homozygotes within a healthy general population

Unraveling the intricacies of spatial organization of the ErbB receptors and downstream signaling pathways

Faced with the complexity of diseases such as cancer which has 1012 mutations, altering gene expression, and disrupting regulatory networks, there has been a paradigm shift in the biological sciences and what has emerged is a much more quantitative field of biology. Mathematical modeling can aid in biological discovery with the development of predictive models that provide future direction for experimentalist. In this work, I have contributed to the development of novel computational approaches which explore mechanisms of receptor aggregation and predict the effects of downstream signaling. The coupled spatial non-spatial simulation algorithm, CSNSA is a tool that I took part in developing, which implements a spatial kinetic Monte Carlo for capturing receptor interactions on the cell membrane with Gillespies stochastic simulation algorithm, SSA, for temporal cytosolic interactions. Using this framework we determine that receptor clustering significantly enhances downstream signaling. In the next study the goal was to understand mechanisms of clustering. Cytoskeletal interactions with mobile proteins are known to hinder diffusion. Using a Monte Carlo approach we simulate these interactions, determining at what cytoskeletal distribution and receptor concentration optimal clustering occurs and when it is inhibited. We investigate oligomerization induced trapping to determine mechanisms of clustering, and our results show that the cytoskeletal interactions lead to receptor clustering. After exploring the mechanisms of clustering we determine how receptor aggregation effects downstream signaling. We further proceed by implementing the adaptively coarse grained Monte Carlo, ACGMC to determine if \u27receptor-sharing\u27 occurs when receptors are clustered. In our proposed \u27receptor-sharing\u27 mechanism a cytosolic species binds with a receptor then disassociates and rebinds a neighboring receptor. We tested our hypothesis using a novel computational approach, the ACGMC, an algorithm which enables the spatial temporal evolution of the system in three dimensions by using a coarse graining approach. In this framework we are modeling EGFR reaction-diffusion events on the plasma membrane while capturing the spatial-temporal dynamics of proteins in the cytosol. From this framework we observe \u27receptor-sharing\u27 which may be an important mechanism in the regulation and overall efficiency of signal transduction. In summary, I have helped to develop predictive computational tools that take systems biology in a new direction.\u2