{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 8. Blinking bacteria: The repressilator enables self-sustaining oscillations\n", "\n", "(c) 2019 Justin Bois and Michael Elowitz. With the exception of pasted graphics, where the source is noted, this work is licensed under a [Creative Commons Attribution License CC-BY 4.0](https://creativecommons.org/licenses/by/4.0/). All code contained herein is licensed under an [MIT license](https://opensource.org/licenses/MIT).\n", "\n", "This document was prepared at [Caltech](http://www.caltech.edu) with financial support from the [Donna and Benjamin M. Rosen Bioengineering Center](http://rosen.caltech.edu).\n", "\n", "\n", "\n", "
\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Design principle\n", "- Delayed, ultrasensitive, negative feedback can generate self-sustaining oscillations in cells.\n", "\n", "#### Techniques\n", "- Composition of functions\n", "- Linear stability analysis\n", "- Linear stability diagrams\n", "- Numerical calculation of a scalar fixed point\n", "- Synthetic biology\n", "\n", "#### References\n", "- [Elowitz & Leibler, A synthetic oscillatory network of transcriptional regulators, *Nature*, 2000](https://doi.org/10.1038/35002125)\n", "- [Synchronous long-term oscillations in a synthetic gene circuit, *Nature*, 2016](https://doi.org/10.1038/nature19841) \n", "
\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Prior to executing this lesson, you should be sure to update the `biocircuits` module by doing the following on the command line.**\n", "\n", " pip install --upgrade biocircuits " ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:04.356223Z", "start_time": "2019-05-03T03:15:04.334343Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "data": { "text/html": [ "\n", "
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" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Today's topic: designing clocks\n", "\n", "Today we will talk about how to build a clock in a living cell. More specifically, we will discuss a synthetic genetic clock circuit called the Repressilator ([Elowitz & Leibler, Nature, 2000](https://doi.org/10.1038/35002125)). We first discuss the important roles of oscillators and clocks in natural biological systems, and then ask how one might go about designing a synthetic clock circuit that can operate in a living cell. To do this, we will use **linear stability analysis**, a broadly useful approach for analyzing diverse systems. We will also introduce the concept of a **limit cycle**, which is an additional, and more dynamic, type of \"attractor\" compared to the fixed points that we have encountered so far. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Clocks are ubiquitous\n", "\n", "Modern life depends on accurate time-keeping, which has been enabled by relentless invention and improvement of mechanical and electronic clocks. For example, one of the major turning points in global navigation was the development of mechanical, temperature-compensated clocks to address the challenge of measuring longitude at sea. Notably, [John Harrison](https://en.wikipedia.org/wiki/John_Harrison) engineered an amazing and beautiful series of clocks, or \"marine chronometers,\" of increasing precision for this purpose. Fast forward to today, and we find our daily navigation through the mean streets of Los Angeles, across smaller distances and usually at far slower speeds depends on the even more precise atomic clocks that operate on satellites to enable the global positioning system (GPS). Today, many of you may find yourself staring at the clock in this very room.\n", "\n", "Within biology, clocks have been metaphorically identified with the perplexing mystery of how the undirected process of evolution could generate precise behaviors from seemingly \"messy\" molecular components. Dawkins's famous book, the blind watchmaker, personifies evolution as this eponymous watchmaker, who creates devices of astonishing precision (tissues and organisms) without being able to \"see,\" much less plan, what she is doing.\n", "\n", "
\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Clocks function within cells and organisms\n", "\n", "Meanwhile, as living organisms, we are controlled by clocks of many kinds. Circadian clocks control our 24 hour cycles of sleep, hunger, and activity. Humans confined to environments in constant conditions exhibit free running activity cycles with 24hr (or, more accurately, a [24.18 hour](https://science.sciencemag.org/content/284/5423/2177) periods). Our clocks do not just respond to light and temperature cycles, but constitute free-running clocks that adjust all too slowly to external inputs as we fly across time zones. \n", "\n", "The **cell cycle** represents another kind of oscillator that takes cells through repetitive cycles of growth and division. Hormones cycle on a range of timescales from hours to weeks. Plants contain ciracdian and seasonal clocks that control their movement and flowering, in response to time as well as light, temperature and other inputs. \n", "\n", "Can we understand how these biological clocks work? In 1971, Ronald Konopka and Seymour Benzer showed, here at Caltech, that one could [identify mutations that altered the circadian rhythms of fruit flies](https://doi.org/10.1073/pnas.68.9.2112). Over the last few decades, biologists have discovered key molecular components that enable these clocks to function. These include transcription factors, light sensors, and other components. In multicellular organisms, clocks synchronize between cells and organs. However, clocks are not a multicellular phenomenon: Even single cell cyanobacteria have precise, [cell-autonomous](https://doi.org/10.1038/nature02533) circadian clocks. And analysis of oscillations in individual mammalian cells indicates that they can still exhibit [circadian oscillations](https://doi.org/10.1016/0896-6273(95)90214-7), as one can see in this movie and time traces of individual fibroblasts, showing robust cycling as well as cell-cell variability in period and phase, from D. Welsh, et al. ([*Current Biology* 2004](https://doi.org/10.1016/j.cub.2004.11.057)); pardon the lossy compression. \n", "\n", "
\n", "\n", "
\n", "\n", "Based on the movie, we can look at time courses of singe cell oscillations.\n", "\n", "
\n", "\n", "Efforts from many labs have now identified many key biological components and interactions that generate circadian rhythms, culminating in the [2017 Nobel prize](https://www.nobelprize.org/prizes/medicine/2017/press-release/) to Jeffrey C. Hall, Michael Rosbash and Michael W. Young \"for their discoveries about how internal clocks and biological rhythms govern human life.\" One of the simplest clocks exists in cyanobacteria, where Kondo and colleagues showed in 2005 that [three proteins plus ATP](https://doi.org/10.1126/science.1108451) could, remarkably, biochemically reconstitute core clock oscillations in vitro through a circuit mechanism subsequently explained by Rust, et al. involving [ordered phosphorylation and feedback](https://doi.org/10.1126/science.1148596)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Can one design and build a synthetic clock inside a cell?\n", "\n", "Here we will ask a very simple question: What kind of biological circuit is sufficient to generate a clock that operates reliably in a single cell. Designing and building a clock \"from scratch\" is a **synthetic biology** approach that helps us identify the fundamental design principles underlying clock design, and address questions such as:\n", "\n", "* How \"hard\" is it to build a biological clock? \n", "* How precise can a biological clock be?\n", "* What minimum circuit designs are sufficient to generate self-sustaining oscillations?\n", "* What tradeoffs exist between alternative clock circuit designs?\n", "\n", "In addition, synthetic clocks provide modules for engineering more complex cellular behaviors. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Limit cycles are ideal dynamical behaviors for clocks\n", "\n", "Previously in this course, we have discussed only one kind of \"attractor\" -- the stable fixed point. When a system sits at a stable fixed point, it does not change over time. By contrast, in a functioning clock circuit, the state of the system constantly changes in a periodic fashion, progressing through a cyclic sequence of \"phases\" that returns it to its starting point without external input. For an ideal clock, perturbations that we might expect to occur in a cell, such as fluctuations in the abundance of cellular components, should generate minimal perturbations to the clock dynamics, which should ultimately return to the same cycle.\n", "\n", "In other words, we want to design a system that \"has to\" oscillate, that cannot do anything else.\n", "\n", "The kind of behavior we are looking for is called a **limit cycle**. Stable limit cycles are defined by Strogatz as \"isolated closed orbits\", meaning that the system goes around the limit cycle, and that neighboring points ultimately feed into the limit cycle. If the system is on a limit cycle, then it will ultimately return to the limit cycle after small perturbations, as sketched here:\n", "\n", "
\n", "\n", "
\n", "
\n", "\n", "Note that one can also have unstable limit cycles. Also, as Strogatz notes, linear systems such as a frictionless pendulum can produce a family of orbits but not a limit cycle, because multipling any solution of $\\dot{\\mathbf{x}}=\\mathsf{A} \\cdot \\mathbf{x}$ by a constant produces another solution.\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## General design framework: limit cycle dynamics across a broad range of parameter values\n", "\n", "Our first design requirement for the synthetic clock is that **it should produce limit cycle oscillations**.\n", "\n", "In addition to generating limit cycle oscillations, our clock circuit should also **oscillate across a broad range of biochemical parameter values.** This is because we may not be able to exactly know or control many cellular parameters, which can and do fluctuate, as we will discuss in the context of stochastic \"noise.\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Practical design constraints: use modular, well-characterized components\n", "\n", "In synthetic biology, we do not have the level of understanding or control that is available to evolution. We know a good deal about some kinds of components, and much less about many others. Among the best characterized regulatory components in biology are prokaryotic (bacterial) transcriptional repressors and their cognate target promoters. These components are also **modular** and **composable**. By modular, we mean that they can be taken out of their natural context and used to generate a new regulatory circuit. Composability is a stronger form of modularity in which a set of components can regulate each other in the same way. For instance, transcription factors are composable because any one can be engineered to regulate any other simply by combining corresponding target promoter sequences with open reading frames for the transcription factors. \n", "\n", "(Transcriptional activators, which we have already encountered, are also excellent components for synthetic design although, at the time this work was done, there were generally fewer examples that were as well-understood as repressors. Therefore, we will focus below on a circuit design built exclusively from repressors)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Design strategy:\n", "\n", "Based on the considerations above, we will try to design a biological circuit that generates **limit cycle oscillations** across a **broad range of biochemical parameter values** using the well-characterized composable **transcriptional repressors**. \n", "\n", "One of the first designs one can imagine building with repressors is a \"rock-scissors-paper\" feedback loop composed of three repressors, each of which represses the next one, in a cycle:\n", "\n", "
\n", " \n", "
\n", "\n", "This diagram refers to three specific repressors, TetR, $\\lambda$ cI, and LacI. We will discuss the rationale for choosing these below, after we work out the design. For now, the names of the repressors are unimportant, so we will call them repressor 1, 2, and 3. Repressor 1 represses production of repressor 2, which in turn represses production of repressor 3. Finally, repressor 3 represses production or repressor 1, completing the loop.\n", "\n", "\n", "\n", "This design is a three-component negative feedback loop (analogous to a \"three ring oscillator\" in electronics). If one were to turn up the level of the first protein in this system, it would lead to a decrease in the second, which would cause an increase in the third, and finally a decrease in the first. Thus, one can see, intuitively, that this system produces a negative feedback that tends to push back in the opposite direction to any perturbation, after the delay required to propagate the perturbation around the loop. \n", "\n", "We can try to work out the dynamics of this system by intuitive reasoning. We might achieve a limit cycle oscillation: Say that initially repressor 1 has high copy number and repressors 2 and 3 are low. The high copy of number of repressor 1 will keep the numbers of repressor 2 down. This means that repressor 3 is free to be expressed. As its copy number grows, it will start to repress repressor 1. As repressor 1 goes down, repressor 2 is expressed in higher numbers. The increased repressor 2 copy number leads to less repressor 3. Then, repressor 1 comes back up again. So, we see a cycle, where repressor 1 is high, then repressor 3, and finally repressor 2. \n", "\n", "However, this behavior is by no means guaranteed. We might equally well just get a stable steady state, where all three repressors evolve to intermediate values, each sufficient to keep its target repressor at the appropriate level to maintain its target at its steady-state level. This behavior would be much more boring. \n", "\n", "In fact, both behaviors are possible.\n", "\n", "So, our questions are now: \n", "1. What kinds of behaviors does this circuit produce?\n", "2. How can we engineer the circuit to favor, or guarantee, limit cycle oscillations?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Dynamical equations for the repressilator\n", "To analyze the repressilator, we will write down our usual differential equations. For simplicity, we will assume symmetry among the species (this will not be true in the real system) and, initially, we will consider only protein dynamics, ignoring mRNA. Later on, we will ask how including mRNA modifies the conclusions.\n", "\n", "\\begin{align}\n", " \\frac{\\mathrm{d}x_1}{\\mathrm{d}t} &= \\frac{\\beta}{1 + (x_3/k)^n} - \\gamma x_1, \\\\[1em]\n", " \\frac{\\mathrm{d}x_2}{\\mathrm{d}t} &= \\frac{\\beta}{1 + (x_1/k)^n} - \\gamma x_2, \\\\[1em]\n", " \\frac{\\mathrm{d}x_3}{\\mathrm{d}t} &= \\frac{\\beta}{1 + (x_2/k)^n} - \\gamma x_3.\n", "\\end{align}\n", "\n", "In dimensionless units, this is\n", "\n", "\\begin{align}\n", " \\frac{\\mathrm{d}x_i}{\\mathrm{d}t} &= \\frac{\\beta}{1 + x_j^n} - x_i, \\quad \\text{ with } i,j \\text{ pairs } (1,3), (2,1), (3,2).\n", "\\end{align}\n", "\n", "### Fixed point\n", "To find the fixed point of the repressilator, we solve for $x_i$ with $\\dot{x}_i = 0\\;\\forall i$. We get that\n", "\n", "\\begin{align}\n", " x_1 &= \\frac{\\beta}{1+x_3^n}, \\\\[1em]\n", " x_2 &= \\frac{\\beta}{1+x_1^n}, \\\\[1em]\n", " x_3 &= \\frac{\\beta}{1+x_2^n}.\n", "\\end{align}\n", "\n", "We can substitute the expression for $x_3$ into that for $x_1$ to get\n", "\n", "\\begin{align}\n", " x_1 = \\frac{\\beta}{1 + \\left(\\displaystyle{\\frac{\\beta}{1 + x_2^n}}\\right)^n}.\n", "\\end{align}\n", "\n", "We can then substitute the expression for for $x_2$ to get\n", "\n", "\\begin{align}\n", " x_1 = \\frac{\\beta}{1 + \\displaystyle{\\left(\\frac{\\beta}{1 + \\left(\\displaystyle{\\frac{\\beta}{1+x_1^n}}\\right)^n}\\right)^n}}.\n", "\\end{align}\n", "\n", "This looks like a gnarly expression, but we can write it conveniently as a **composition of functions**. Specifically,\n", "\n", "\\begin{align}\n", " x_1 = f(f(f(x_1))) \\equiv f\\!f\\!f(x_1),\n", "\\end{align}\n", "\n", "where\n", "\\begin{align}\n", " f(x) = \\frac{\\beta}{1+x^n}.\n", "\\end{align}\n", "\n", "By symmetry, this relation holds for repressors 2 and 3 as well, so we have\n", "\n", "\\begin{align}\n", " x_i = f\\!f\\!f(x_i).\n", "\\end{align}\n", "\n", "Writing the relationship for the fixed point with a composition of functions is useful because we can easily compute the derivatives of the composite function using the chain rule.\n", "\n", "\\begin{align}\n", " (f\\!f\\,)'(x) &= f\\,'(f(x))\\cdot f\\,'(x), \\\\[1em]\n", " (f\\!f\\!f\\,)'(x) &= f\\,'(f\\!f(x)) \\cdot (f\\!f\\,)'(x) = f\\,'(f(f(x))) \\cdot f\\,'(f(x)) \\cdot f\\,'(x).\n", "\\end{align}\n", "\n", "Now, since $f(x)$ is monotonically decreasing, $f\\,'(x) < 0$, and also $f\\,'(f(x)) < 0$. This means that $f\\!f\\,'(x) > 0$, so $f\\!f(x)$ is monotonically increasing. Now, $f\\,'(f\\!f(x)) < 0$, since $f\\,'(\\text{anything monotonically increasing}) < 0$. This means that $f\\!f\\!f(x)$ is monotonically decreasing. Since $x_i$ is increasing, there is a single fixed point with $x = f\\!f\\!f(x)$. This is more clear if we look at a plot." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:04.409153Z", "start_time": "2019-05-03T03:15:04.358742Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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x**n)\n", "\n", "# Make composition of functions\n", "x = np.linspace(0, 3, 200)\n", "fff = f(f(f(x)))\n", "\n", "# Show plot\n", "p = bokeh.plotting.figure(height=300, width=350, x_axis_label='x')\n", "p.line(x, x, line_width=2, legend='x')\n", "p.line(x, fff, line_width=2, color='orange', legend='fff(x)')\n", "p.legend.location = 'center_right'\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Because the time derivative of $x_1$, $x_2$ and $x_3$ _all_ vanish at the fixed point, and we have shown that the fixed point is unique, we have\n", " \n", "\\begin{align}\n", " x_1 = x_2 = x_3 \\equiv x_0 = \\frac{\\beta}{1 + x_0^n},\n", "\\end{align}\n", "\n", "or\n", "\n", "\\begin{align}\n", " \\beta = x_0(1+x_0^n).\n", "\\end{align}\n", "\n", "Because we have a single fixed point, we cannot have multistability in the repressilator. So what happens at this fixed point? To answer this question, we turn to **linear stability analysis**." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Linear stability analysis\n", "We first give a minimal introduction to the technique of linear stability analysis. The basic idea is that to approximate a *nonlinear* dynamical system by its Taylor series to first order near the fixed point and then look at the behavior of the simpler linear system. The Hartman-Grobman theorem (which we will not derive here) ensures that the linearized system faithfully represents the phase portrait of the full nonlinear system near the fixed point.\n", "\n", "Say we have a dynamical system with variables $\\mathbf{u}$ with\n", "\n", "\\begin{align}\n", " \\frac{\\mathrm{d}\\mathbf{u}}{\\mathrm{d}t} = \\mathbf{f}(\\mathbf{u}),\n", "\\end{align}\n", "\n", "where $\\mathbf{f}(\\mathbf{u})$ is a vector-valued function, i.e.,\n", "\n", "\\begin{align}\n", " \\mathbf{f}(\\mathbf{u}) = (f_1(u_1, u_2, \\ldots), f_2(u_1, u_2, \\ldots), \\ldots).\n", "\\end{align}\n", "\n", "Say that we have a fixed point $\\mathbf{u}_0$. Then, linear stability analysis proceeds with the following steps.\n", "\n", "1. Linearize about $\\mathbf{u}_0$, defining $\\delta\\mathbf{u} = \\mathbf{u} - \\mathbf{u}_0$. To do this, expand $f(\\mathbf{u})$ in a Taylor series about $\\mathbf{u}_0$ to first order.\n", " \n", " \\begin{align}\n", " \\mathbf{f}(\\mathbf{u}) = \\mathbf{f}(\\mathbf{u}_0) + \\nabla \\mathbf{f}(\\mathbf{u}_0)\\cdot \\delta\\mathbf{u} + \\cdots,\n", " \\end{align}\n", " \n", " where $\\nabla \\mathbf{f}(\\mathbf{u}_0) \\equiv \\mathsf{A}$ is the Jacobi matrix,\n", " \n", " \\begin{align}\n", " \\nabla \\mathbf{f}(\\mathbf{u}_0) \\equiv \\mathsf{A} = \\left.\\begin{pmatrix}\n", " \\frac{\\partial f_1}{\\partial u_1} & \\frac{\\partial f_1}{\\partial u_2} & \\cdots \\\\[0.5em]\n", " \\frac{\\partial f_2}{\\partial u_1} & \\frac{\\partial f_2}{\\partial u_2} & \\cdots \\\\\n", " \\vdots & \\vdots & \\ddots\n", " \\end{pmatrix}\\right|_{\\mathbf{u}_0}.\n", " \\end{align}\n", " \n", " Thus, we have\n", " \n", " \\begin{align}\n", " \\frac{\\mathrm{d}\\mathbf{u}}{\\mathrm{d}t} = \\frac{\\mathrm{d}\\mathbf{u}_0}{\\mathrm{d}t} + \\frac{\\mathrm{d}\\delta\\!\\mathbf{u}}{\\mathrm{d}t}\n", " = \\mathbf{f}(\\mathbf{u}_0) + \\mathsf{A} \\cdot \\delta\\mathbf{u} + \\text{higher order terms}.\n", " \\end{align}\n", " \n", " Since\n", " \n", " \\begin{align}\n", " \\frac{\\mathrm{d}\\mathbf{u}_0}{\\mathrm{d}t} = \\mathbf{f}(\\mathbf{u}_0) = 0,\n", " \\end{align}\n", " \n", " we have, to linear order,\n", " \n", " \\begin{align}\n", " \\frac{\\mathrm{d}\\delta\\mathbf{u}}{\\mathrm{d}t} = \\mathsf{A} \\cdot \\delta\\mathbf{u}.\n", " \\end{align}\n", "2. Compute the eigenvalues, $\\lambda$ of $\\mathsf{A}$.\n", "3. Determine the stability of the fixed point using the following rules.\n", "\n", " - If $\\mathrm{Re}(\\lambda) < 0$ for all $\\lambda$, then the fixed point $\\mathbf{u}_0$ is linearly stable.\n", " - If $\\mathrm{Re}(\\lambda) > 0$ for any $\\lambda$, then the fixed point $\\mathbf{u}_0$ is linearly unstable. \n", " - If $\\mathrm{Im}(\\lambda) \\ne 0$ for a linearly unstable fixed point, the instability is oscillatory.\n", " - If $\\mathrm{Re}(\\lambda) = 0$ for one or more $\\lambda$, with the rest having $\\mathrm{Re}(\\lambda) < 0$, then the fixed point $\\mathbf{u}_0$ lies at a bifurcation.\n", "\n", "So, if we can assess the dynamics of the linearized system near the fixed point, we can get an idea what is happening with the full system.\n", "\n", "To do the linearization, we need to do Taylor expansions of Hill functions. We do this so often in this course, that we will write them here and/or memorize for future use.\n", "\\begin{align}\n", " \\frac{x^n}{1+x^n} &= \\frac{x_0^n}{1+x_0^n} + \\frac{n x_0^{n-1}}{(1+x_0^n)^2}\\,\\delta\\!x + \\text{higher order terms}, \\\\\n", " \\frac{1}{1+x^n} &= \\frac{1}{1+x_0^n} - \\frac{n x_0^{n-1}}{(1+x_0^n)^2}\\,\\delta\\!x + \\text{higher order terms}.\n", "\\end{align}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Linear stability analysis for the repressilator\n", "\n", "To perform linear stability analysis for the repressilator, we begin by writing the linearized system.\n", "\n", "\\begin{align}\n", " \\frac{\\mathrm{d}\\delta x_1}{\\mathrm{d}t} &\\approx -\\frac{\\beta n x_0^{n-1}}{(1+x_0^n)^2}\\,\\delta x_3 - \\delta x_1, \\\\[1em]\n", " \\frac{\\mathrm{d}\\delta x_2}{\\mathrm{d}t} &\\approx -\\frac{\\beta n x_0^{n-1}}{(1+x_0^n)^2}\\,\\delta x_1 - \\delta x_2, \\\\[1em]\n", " \\frac{\\mathrm{d}\\delta x_3}{\\mathrm{d}t} &\\approx -\\frac{\\beta n x_0^{n-1}}{(1+x_0^n)^2}\\,\\delta x_2 - \\delta x_3.\n", "\\end{align}\n", "\n", "Defining\n", "\n", "\\begin{align}\n", " a = \\frac{\\beta n x_0^{n-1}}{(1+x_0^n)^2},\n", "\\end{align}\n", "\n", "we can write this in matrix form as\n", "\n", "\\begin{align}\n", " \\frac{\\mathrm{d}}{\\mathrm{d}t}\\begin{pmatrix}\n", " \\delta x_1 \\\\\n", " \\delta x_2 \\\\\n", " \\delta x_3\n", "\\end{pmatrix}\n", "= \\mathsf{A}\\cdot\\begin{pmatrix}\n", "\\delta x_1 \\\\\n", "\\delta x_2 \\\\\n", "\\delta x_3\n", "\\end{pmatrix},\n", "\\end{align}\n", "\n", "with\n", "\n", "\\begin{align}\n", " \\mathsf{A} = -\\begin{pmatrix}\n", " 1 & 0 & a \\\\\n", " a & 1 & 0 \\\\\n", " 0 & a & 1\n", "\\end{pmatrix}.\n", "\\end{align}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To compute the eigenvalues of $\\mathsf{A}$, we compute the characteristic polynomial using cofactors,\n", "\n", "\\begin{align}\n", " (1+\\lambda)(1+\\lambda)^2 + a(a^2) = (1+\\lambda)^3 + a^3 = 0.\n", "\\end{align}\n", "\n", "This is solved to give\n", "\n", "\\begin{align}\n", " \\lambda = -1 + a \\sqrt[3]{-1}.\n", "\\end{align}\n", "\n", "Recalling that there are three cube roots of $-1$, we get our three eigenvalues.\n", "\n", "\\begin{align}\n", " &\\lambda = -1 - a, \\\\[1em]\n", " &\\lambda = -1 + \\frac{a}{2}(1 + i\\sqrt{3}),\\\\[1em]\n", " &\\lambda = -1 + \\frac{a}{2}(1-i\\sqrt{3}).\n", "\\end{align}\n", "\n", "The first eigenvalue is always real and negative. The second two have a positive real part if $a > 2$;\n", "\n", "\\begin{align}\n", " a = \\frac{\\beta n x_0^{n-1}}{(1 + x_0^n)^2} > 2.\n", "\\end{align}\n", "\n", "Now, we previously derived that the fixed point $x_0$ satisfies\n", "\n", "\\begin{align}\n", " \\beta = x_0(1+x_0^n),\n", "\\end{align}\n", "\n", "so\n", "\n", "\\begin{align}\n", " a = \\frac{\\beta n x_0^{n-1}}{(1 + x_0^n)^2} = \\frac{n x_0^n}{1 + x_0^n}.\n", "\\end{align}\n", "\n", "So, $a>2$ only if $n > 2$, meaning that we _must_ have ultrasensitivity for the fixed point to be unstable.\n", "\n", "At the bifurcation,\n", "\n", "\\begin{align}\n", " a = \\frac{n x_0^n}{1+x_0^n} = 2,\n", "\\end{align}\n", "\n", "so\n", "\n", "\\begin{align}\n", " x_0^n = \\frac{2}{n-2}.\n", "\\end{align}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again using $\\beta = x_0(1+x_0^n)$, we can write\n", "\n", "\\begin{align}\n", " \\beta = \\frac{n}{2}\\left(\\frac{n}{2} - 1\\right)^{-\\frac{n+1}{n}}\n", "\\end{align}\n", "\n", "at the bifurcation. So, for $n > 2$ and\n", "\n", "\\begin{align}\n", "\\beta > \\frac{n}{2}\\left(\\frac{n}{2} - 1\\right)^{-\\frac{n+1}{n}},\n", "\\end{align}\n", "\n", "we have imaginary eigenvalues with positive real parts. This is therefore an **oscillatory instability**." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Solving for the fixed point\n", "\n", "We have shown that there is a single fixed point, $x_1 = x_2 = x_3 \\equiv x_0$ with \n", "\n", "\\begin{align}\n", "\\beta = x_0(1 + x_0^n).\n", "\\end{align}\n", "\n", "Getting an analytical solution of this equation for $x_0$ is usually impossible. We therefore seek a numerical method for finding $x_0$. This is an example of a **root finding problem**. It can be cast into a problem of finding $f(x) = 0$ for some function $f(x)$. Do not confuse this $f(x)$ with that defined in the previous sections to define the right hand side of the dynamical equations; we are using $f(x)$ here to be an arbitrary function. In the present case, $f(x) = \\beta - x_0(1+x_0^n)$.\n", "\n", "There are many algorithms for finding roots of functions. We will explore algorithms for doing so for the more general multidimensional case in future lessons. For now, we seek a scalar $x_0$. In this case, we know a lot about the fixed point. We know that it exists and is unique. We also know that it lies between $x_0 = 0$ (where $f(0) = \\beta > 0$) and $x_0 = \\beta$ (since $f(\\beta) < 0$). When we have bounds and guarantees of uniqueness for a scalar root, we can use a **[bisection method](https://en.wikipedia.org/wiki/Bisection_method)** to find the root. The benefit of the bisection method is that is guaranteed to find the root of the function $f(x)$ on an interval $[a,b]$, provided $f(x)$ is continuous and $f(a)$ and $f(b)$ have opposite sign, which is the case here. **[Brent's method](https://en.wikipedia.org/wiki/Brent%27s_method)** also has this guarantee, but is more efficient that using bisection. Brent's method is available in the `scipy.optimize.brentq()` function. It takes as an argument the function $f(x)$ whose root is to be found, and the left and right bounds for the root. We can write a function to find the fixed point for given $\\beta$ and $n$." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:04.414984Z", "start_time": "2019-05-03T03:15:04.411732Z" } }, "outputs": [], "source": [ "def fixed_point(beta, n):\n", " return scipy.optimize.brentq(lambda x: beta - x*(1+x**n), 0, beta)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can use this equation to map out the fixed point for various values of $\\beta$ for fixed $n = 3$." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:04.458098Z", "start_time": "2019-05-03T03:15:04.417646Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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Application\",\"version\":\"1.0.4\"}};\n", " var render_items = [{\"docid\":\"e6fdff7e-2a70-4e61-9b8b-e6fda628476e\",\"roots\":{\"1295\":\"f1d2d3ef-22be-4560-b917-b522e7f7024e\"}}];\n", " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", "\n", " }\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " } else {\n", " var attempts = 0;\n", " var timer = setInterval(function(root) {\n", " if (root.Bokeh !== undefined) {\n", " embed_document(root);\n", " clearInterval(timer);\n", " }\n", " attempts++;\n", " if (attempts > 100) {\n", " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", " clearInterval(timer);\n", " }\n", " }, 10, root)\n", " }\n", "})(window);" ], "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "id": "1295" } }, "output_type": "display_data" } ], "source": [ "# Compute the fixed point for various beta\n", "beta = np.linspace(0.1, 100, 200)\n", "x_fp = [fixed_point(b, 3) for b in beta]\n", "\n", "# Make the plot\n", "p = bokeh.plotting.figure(width=400, height=200,\n", " x_axis_label='beta',\n", " y_axis_label='fixed point, x0')\n", "p.line(beta, x_fp, line_width=2)\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Temporal dynamics\n", "\n", "We can integrate the dynamical equations to see the levels of the respective proteins using interactive plotting of the result so we can see how the dynamics depend on the parameters $\\beta$ and $n$. For sufficiently large $\\beta$ and $n$, given by the linear stability relation we derived above,\n", "\n", "\\begin{align}\n", "\\beta > \\frac{n}{2}\\left(\\frac{n}{2} - 1\\right)^{-\\frac{n+1}{n}},\n", "\\end{align}\n", "\n", "we see oscillations. A few things to notice: \n", "* If you set $n<2$, oscillations diminish over time.\n", "* If you set $n>2$, oscillations are sustained only for large enough $\\beta$\n", "* If you set $n=2$, see what happens...\n", "\n", "

Note that to see and interact with this plot, you need to be running this Jupyter notebook; the plot is lost in the static HTML rendering.

" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:04.762548Z", "start_time": "2019-05-03T03:15:04.680465Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "data": { "application/vnd.bokehjs_exec.v0+json": "", "text/html": [ "\n", "" ] }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "server_id": "5f962d65aa8640b8ad53b2a8251a70f1" } }, "output_type": "display_data" } ], "source": [ "def repressilator_rhs(x, t, beta, n):\n", " \"\"\"\n", " Returns 3-array of (dx_1/dt, dx_2/dt, dx_3/dt)\n", " \"\"\"\n", " x_1, x_2, x_3 = x\n", " return np.array([beta / (1 + x_3**n) - x_1,\n", " beta / (1 + x_1**n) - x_2,\n", " beta / (1 + x_2**n) - x_3])\n", "\n", "# Initial condiations\n", "x0 = np.array([1, 1, 1.2])\n", "\n", "# Number of points to use in plots\n", "n_points = 1000\n", "\n", "# Parameters for each slider\n", "slider_params = (biocircuits.AttributeContainer(title='β', \n", " start=1, end=100, \n", " value=10, step=0.1),\n", " biocircuits.AttributeContainer(title='n', \n", " start=1, end=5, \n", " value=3, step=0.1))\n", "\n", "def callback(source, x_range, y_range, sliders, toggles):\n", " # Set up time values, keeping minimum at zero\n", " t = np.linspace(0, x_range.end, n_points)\n", " \n", " # Pull out slider values\n", " slider_args = tuple(slider.value for slider in sliders)\n", "\n", " # Solve it!\n", " x = scipy.integrate.odeint(repressilator_rhs, x0, t, args=slider_args)\n", "\n", " # Update data source\n", " source.data['t'] = t\n", " source.data['x1'] = x[:,0]\n", " source.data['x2'] = x[:,1]\n", " source.data['x3'] = x[:,2]\n", "\n", "\n", "def base_plot(callback, sliders, toggles, extra_args):\n", " # Set up plot and data source\n", " p = bokeh.plotting.figure(width=600, height=300, \n", " x_axis_label='t')\n", "\n", " source = bokeh.models.ColumnDataSource()\n", "\n", " colors = bokeh.palettes.d3['Category10'][3]\n", " p.line('t', 'x1', source=source, line_width=3, color=colors[0], legend='1')\n", " p.line('t', 'x2', source=source, line_width=3, color=colors[1], legend='2')\n", " p.line('t', 'x3', source=source, line_width=3, color=colors[2], legend='3')\n", " p.legend.location = 'top_left'\n", "\n", " \n", " # Update data according to callback\n", " callback(source, bokeh.models.Range1d(0, 30), None, \n", " sliders, toggles, *extra_args)\n", "\n", " return p, source\n", "\n", "# Build the interactive plotting app\n", "app = biocircuits.interactive_xy_plot(base_plot, callback, slider_params)\n", "\n", "# Show the app\n", "bokeh.io.show(app, notebook_url=notebook_url)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Trajectory in phase space\n", "\n", "It is also instructive to plot the trajectory of the system as a projection in the $x_2$-$x_1$ plane (or in either of the other two planes this three-dimensional system can be projected onto).\n", "\n", "When the fixed point is stable, the trajectory in the $x_2$-$x_1$ plane spirals into the fixed point. When it is unstable, the trajectory spirals away from it, eventually cycling around the fixed point to join an orbit-like trajectory called a [**limit cycle**](https://en.wikipedia.org/wiki/Limit_cycle).\n", "\n", "

Note that to see and interact with this plot, you need to be running this Jupyter notebook; the plot is lost in the static HTML rendering.

" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:04.803480Z", "start_time": "2019-05-03T03:15:04.788570Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "data": { "application/vnd.bokehjs_exec.v0+json": "", "text/html": [ "\n", "" ] }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "server_id": "686a76c417524db483233392a29bd5ef" } }, "output_type": "display_data" } ], "source": [ "t = np.linspace(0, 100, n_points)\n", "\n", "def traj_callback(source, x_range, y_range, sliders, toggles):\n", " # Pull out slider values\n", " slider_args = tuple(slider.value for slider in sliders)\n", "\n", " # Solve it!\n", " x = scipy.integrate.odeint(repressilator_rhs, x0, t, args=slider_args)\n", "\n", " # Update data source for trajectory\n", " source.data['x1'] = x[:,0]\n", " source.data['x2'] = x[:,1]\n", "\n", " # Update data source for fixed point\n", " beta, n = slider_args\n", " x_fp = fixed_point(beta, n)\n", " source.data['x1_fp'] = [x_fp] + [np.nan] * (len(x)-1)\n", " source.data['x2_fp'] = [x_fp] + [np.nan] * (len(x)-1)\n", "\n", " \n", "def traj_base_plot(callback, sliders, toggles, extra_args):\n", " # Set up plot and data source\n", " p = bokeh.plotting.figure(width=350, height=300, \n", " x_axis_label='x₁', y_axis_label='x₂')\n", "\n", " source = bokeh.models.ColumnDataSource()\n", "\n", " # Show trajectory and fixed point\n", " p.line('x1', 'x2', source=source, line_width=2)\n", " p.circle('x1_fp', 'x2_fp', source=source, color='orange', size=12)\n", " \n", " # Update data according to callback\n", " callback(source, bokeh.models.Range1d(0, 30), None, \n", " sliders, toggles, *extra_args)\n", "\n", " return p, source\n", "\n", "# Build the interactive plotting app\n", "app = biocircuits.interactive_xy_plot(traj_base_plot, traj_callback, \n", " slider_params, (), ())\n", "\n", "# Show the app\n", "bokeh.io.show(app, notebook_url=notebook_url)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The limit cycle in 3D\n", "\n", "Finally, here is a simple three-dimensional plot of the limit cycle in the space of the three protein concentrations." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:05.299210Z", "start_time": "2019-05-03T03:15:04.805287Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "image/png": { "height": 231, "width": 349 }, "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Resolve problem for β = 20 and n = 3\n", "x = scipy.integrate.odeint(repressilator_rhs, x0, t, args=(20, 3))\n", "\n", "# Generate the plot\n", "fig = plt.figure()\n", "ax = fig.add_subplot(111, projection='3d')\n", "ax.view_init(30, 30)\n", "ax.plot(x[:,0], x[:,1], x[:,2])\n", "ax.set_xlabel('$p_1$')\n", "ax.set_ylabel('$p_2$')\n", "ax.set_zlabel('$p_3$');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Linear stability analysis provides insight into repressilator design\n", "\n", "It is useful to make a **linear stability diagram**, which is a map of parameter space highlighting stable and unstable regions. We know the bifurcation line is\n", "\n", "\\begin{align}\n", "\\beta = \\frac{n}{2}\\left(\\frac{n}{2} - 1\\right)^{-\\frac{n+1}{n}}\n", "\\end{align}\n", "\n", "We can plot this line and delineate the regions of stability and instability. It clearly shows that, from a design point of view, it is desirable to make both $n$ and $\\beta$ as high as possible." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:05.352035Z", "start_time": "2019-05-03T03:15:05.300759Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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2 - 1)**(-(1 + 1/n))\n", "\n", "# Build the plot\n", "p = bokeh.plotting.figure(height=300, width=400, \n", " x_axis_label='n', y_axis_label='β',\n", " y_axis_type='log', x_range=[2, 5], \n", " y_range=[1, 2000])\n", "p.patch(np.append(n, n[-1]), np.append(beta, beta[0]), \n", " color='lightgray', alpha=0.7)\n", "p.line(n, beta, line_width=4, color='black')\n", "p.text(x=2.1, y=2, text=['stable'])\n", "p.text(x=2.5, y=100, text=['unstable (limit cycle oscillations)'])\n", "\n", "bokeh.io.show(p);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Intuition from the protein-only model\n", "\n", "This analysis shows that high Hill coefficients and strong promoters favor oscillations. This can be understood intuitively: oscillations occur when the feedback \"overshoots.\" The sharper and stronger the response as one goes around the complete feedback loop, the longer and higher a pulse in one factor can grow before it is, inevitably, yanked back down by the feedback. Consistent with this view, there is a tradeoff between the length of the cycle (number of repressors in the loop) and the minimum Hill coefficient required [Elowitz, PhD thesis, 1999](https://catalog.princeton.edu/catalog/2244277).\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Including mRNA and protein in the model provides additional insights\n", "\n", "In the above analysis, we only considered the three proteins. Now, we will consider the mRNA dynamics explicitly as well. We will again assume a symmetry among the various genes, wherein all promoters have the same strength and all repressors have the same Hill coefficient $n$ and Hill activation constant $k$. The dynamical equations are then\n", "\n", "\\begin{align}\n", " \\frac{\\mathrm{d}m_i}{\\mathrm{d}t} &= \\alpha + \\frac{\\beta_m}{1 + (x_j/k)^n} - \\gamma_m m_i,\\\\[1em]\n", " \\frac{\\mathrm{d}x_i}{\\mathrm{d}t} &= \\beta_p m_i - \\gamma_p x_i, \\\\[1em]\n", "\\end{align}\n", "\n", "with $i,j$ pairs $(1,3), (2,1), (3,2)$. Here, we have introduced $\\rho$ to allow for leaky transcription. In dimensionless units, these equations are\n", "\n", "\\begin{align}\n", "\\frac{\\mathrm{d}m_i}{\\mathrm{d}t} &= \\beta\\left(\\rho + \\frac{1}{1 + x_j^n}\\right) - m_i, \\\\[1em]\n", "\\gamma^{-1}\\,\\frac{\\mathrm{d}x_i}{\\mathrm{d}t} &= m_i - x_i,\n", "\\end{align}\n", "\n", "where $\\gamma \\equiv \\gamma_p/\\gamma_m$ is the ratio of the two timescales in the system--the protein and mRNA degradation/decay rates, $\\beta = \\beta_m\\beta_p/\\gamma_m\\gamma_p k$ is a dimensionless promoter strength, and $\\rho = \\alpha/\\beta_m$ is the relative strength of leaky versus regulated expression.\n", "\n", "We can solve this system numerically and plot the dynamics. \n", "\n", "

Note that to see and interact with this plot, you need to be running this Jupyter notebook; the plot is lost in the static HTML rendering.

" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:05.394220Z", "start_time": "2019-05-03T03:15:05.368933Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "data": { "application/vnd.bokehjs_exec.v0+json": "", "text/html": [ "\n", "" ] }, "metadata": { "application/vnd.bokehjs_exec.v0+json": { "server_id": "ebe66d72b88241399655f81b6f879f21" } }, "output_type": "display_data" } ], "source": [ "def repressilator_rhs_6(mx, t, beta, n, gamma, rho):\n", " \"\"\"\n", " Returns 6-array of (dm_1/dt, dm_2/dt, dm_3/dt, dx_1/dt, dx_2/dt, dx_3/dt)\n", " \"\"\"\n", " m_1, m_2, m_3, x_1, x_2, x_3 = mx\n", " return np.array([beta * (rho + 1 / (1 + x_3**n)) - m_1,\n", " beta * (rho + 1 / (1 + x_1**n)) - m_2,\n", " beta * (rho + 1 / (1 + x_2**n)) - m_3,\n", " gamma * (m_1 - x_1),\n", " gamma * (m_2 - x_2),\n", " gamma * (m_3 - x_3)])\n", "\n", "# Initial condiations\n", "x0 = np.array([1, 1.1, 1.2, 0, 0, 0])\n", "\n", "# Number of points to use in plots\n", "n_points = 1000\n", "\n", "# Parameters for each slider\n", "slider_params_6 = (biocircuits.AttributeContainer(title='log₁₀ β', \n", " start=0, end=4, \n", " value=1, step=0.1),\n", " biocircuits.AttributeContainer(title='n', \n", " start=1, end=5, \n", " value=3, step=0.1),\n", " biocircuits.AttributeContainer(title='log₁₀ γ', \n", " start=-3, end=0, \n", " value=0, step=0.1),\n", " biocircuits.AttributeContainer(title='log₁₀ ρ', \n", " start=-6, end=0, \n", " value=-6, step=0.1))\n", "\n", "def callback_6(source, x_range, y_range, sliders, toggles):\n", " # Set up time values, keeping minimum at zero\n", " t = np.linspace(0, x_range.end, n_points)\n", " \n", " # Pull out slider values\n", " slider_args = tuple(10**slider.value if 'log' in slider.title else slider.value \n", " for slider in sliders)\n", "\n", " # Solve it!\n", " mx = scipy.integrate.odeint(repressilator_rhs_6, x0, t, args=slider_args)\n", "\n", " # Update data source\n", " source.data['t'] = t\n", " for i, name in enumerate(['m1', 'm2', 'm3', 'x1', 'x2', 'x3']):\n", " source.data[name] = mx[:,i]\n", "\n", "\n", "def base_plot_6(callback, sliders, toggles, extra_args):\n", " # Set up plot and data source\n", " p = bokeh.plotting.figure(width=800, height=300, \n", " x_axis_label='t')\n", "\n", " source = bokeh.models.ColumnDataSource()\n", "\n", " colors = bokeh.palettes.d3['Category20'][6]\n", " p.line('t', 'm1', source=source, line_width=2, color=colors[1], legend='m1')\n", " p.line('t', 'x1', source=source, line_width=2, color=colors[0], legend='x1')\n", " p.line('t', 'm2', source=source, line_width=2, color=colors[3], legend='m2')\n", " p.line('t', 'x2', source=source, line_width=2, color=colors[2], legend='x2')\n", " p.line('t', 'm3', source=source, line_width=2, color=colors[5], legend='m3')\n", " p.line('t', 'x3', source=source, line_width=2, color=colors[4], legend='x3')\n", " p.legend.location = 'top_left'\n", " p.legend.click_policy = 'hide'\n", " \n", " # Update data according to callback\n", " callback(source, bokeh.models.Range1d(0, 50), None, \n", " sliders, toggles, *extra_args)\n", "\n", " return p, source\n", "\n", "# Build the interactive plotting app\n", "app = biocircuits.interactive_xy_plot(base_plot_6, callback_6, slider_params_6)\n", "\n", "# Show the app\n", "bokeh.io.show(app, notebook_url=notebook_url)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using a similar technique as for the simplified three-component system, we can show that there is a unique fixed point with $m_i = x_i = x_0$ for all $i$ with\n", "\n", "\\begin{align}\n", "(x_0 - \\beta\\rho)(1+x_0^n) = \\beta.\n", "\\end{align}\n", "\n", "We can perform linear stability for this fixed point. The linear stability matrix is now 6 by 6 rather than 3 by 3. Nonetheless, we can derive analytically that when we get an eigenvalue with a positive real part, it also has a nonzero imaginary part, which means that the instability is oscillatory. We get (not derived here; can you do it?) an eigenvalue with positive real part when\n", "\n", "\\begin{align}\n", "\\left(\\sqrt{\\gamma} + \\sqrt{\\gamma^{-1}}\\right)^2 < \\frac{3f_0^2}{4+2f_0},\n", "\\end{align}\n", "\n", "where\n", "\n", "\\begin{align}\n", "f_0 = \\frac{\\beta n x_0^{n-1}}{(1+x_0^n)^2}.\n", "\\end{align}\n", "\n", "Note something interesting here: $x_0$ is independent of $\\gamma$, while the $\\left(\\sqrt{\\gamma} + \\sqrt{\\gamma^{-1}}\\right)^2$ term is invariant to exchanging $\\gamma \\leftrightarrow \\gamma^{-1}$. This is telling us that the magnitude of the ratio matters, but not whether protein or mRNA are more stable.\n", "\n", "We can compute the phase boundary to be the line for which the inequality above becomes an equality. To compute this, we first need to write a function to find the fixed point for the six-component system." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:05.401015Z", "start_time": "2019-05-03T03:15:05.396128Z" } }, "outputs": [], "source": [ "def fixed_point_6(beta, n, rho):\n", " return scipy.optimize.brentq(lambda x: beta - (x - beta*rho)*(1+x**n), 0, beta*(1+rho))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we write a function to compute the values of $\\gamma$ along the bifurcation line for various values of $\\beta$. It is useful to rewrite the expression for the bifurcation.\n", "\n", "\\begin{align}\n", "\\gamma -\\xi\\sqrt{\\gamma} + 1 = 0,\n", "\\end{align}\n", "\n", "where\n", "\n", "\\begin{align}\n", "\\xi = \\sqrt{\\frac{3f_0^2}{4+2f_0}}.\n", "\\end{align}\n", "\n", "Then, we have\n", "\n", "\\begin{align}\n", "\\gamma = \\frac{1}{4}\\left(\\xi \\pm \\sqrt{\\xi^2-4}\\right)^2.\n", "\\end{align}\n", "\n", "Evidently, if $\\xi < 2$, there is no value of $\\gamma$ that satisfies this relation. There is no problem with this; it just says that there are regions in parameter space outside of the zone where oscillations can occur.\n", "\n", "When we make a plot of the bifurcation, we will only show the plot for $\\gamma > 1$ because of the symmetry of $\\gamma$ and $1/\\gamma$ we have described." ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:05.411235Z", "start_time": "2019-05-03T03:15:05.404108Z" } }, "outputs": [], "source": [ "def gamma_bifurcation(beta, n, rho):\n", " # Initialize gamma\n", " gamma = np.empty_like(beta)\n", "\n", " for i, b in enumerate(beta):\n", " x0 = fixed_point_6(b, n, rho)\n", "\n", " f0 = -b * n * x0**(n-1) / (1 + x0**n)**2\n", " xi = np.sqrt(3 * f0**2 / (4 + 2 * f0))\n", "\n", " if xi < 2:\n", " gamma[i] = np.nan\n", " else:\n", " gamma[i] = (xi + np.sqrt(xi**2 - 4))**2 / 4\n", " \n", " return gamma" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now, we can make plots of the bifurcation lines. In each case, the oscillatory region is below and to the right of the boundary. We will start with $\\rho = 0$ and will vary $n$. In the following plot, we see something interesting: when $n>2$, the boundary approaches a vertical asymptote. This means that for strong enough promoters, one can get oscillations for any decay rates. By contrast when $n<2$ it approaches a horizontal asymptote. In this regime, it is essential that the mRNA and protein decay rates be sufficiently close together. $n=2$ is a critical value in between these two regimes. 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h5QTmQnQNNcIeXkhidACvztnq6pJ0CsGCTJq8wnQM0c06/c7ydAyul6n0ETKECmfgzl2jYoQEef6s2oWihAoHzqp6t+KED+XVTB46IoQCFL5GhRxyhAY7fK7fTrKEDqLa2fzhApQMX+ps7eNSlADu1JyyVbKUAJ3p7mo4ApQFyJJnJZpilANCrav0bMKUBrMSwibPIpQNf4COzJGCpAhHfXcGA/KkD19nkEMGYqQJTJTvs4jSpADAIxqnu0KkDEK3lm+NsqQFoE/oWvAytAUTYVX6ErK0CzFJRIzlMrQMxX0Jk2fCtAFtugqtqkK0AjXF7Tus0rQJ865GzX9itAjjmR0DAgLECGQUhYx0ksQBokcV6bcyxAVWD5Pa2dLEB16FRS/ccsQLPofveL8ixAKI/6iVkdLUAA1dNmZkgtQLRIoOuycy1Abdl/dj+fLUC3ox1mDMstQEG/sBka9y1A3Q398GgjLkCaC1RM+U8uQEaglYzLfC5A9PEwE+CpLkC6OCVCN9cuQNqTAnzRBC9A8t/qI68yL0BwjpKd0GAvQGt+QU02jy9AjNbTl+C9L0Bf4Lriz+wvQF/y/kkCDjBA3oQdib8lMEDWGFTinz0wQLTtiYmjVTBADwLzssptMEAbhRCTFYYwQMNIsV6EnjBAhDTyShe3MEDcuD6Nzs8wQGlDUVuq6DBAsLMz66oBMUCi0D9z0BoxQLu+HyobNDFA03bORotNMUCqPZgAIWcxQB8cG4/cgDFACVhHKr6aMUDh7V8KxrQxQAoL+2f0zjFA1IgCfEnpMUAsaLR/xQMyQBpOo6xoHjJA4gC3PDM5MkDc5SxqJVQyQB6AmG8/bzJAyu/jh4GKMkAZclDu66UyQDridt5+wTJA0zpIlDrdMkBYGA5MH/kyQAo8a0ItFTNA3A9ctGQxM0D4KjffxU0zQBTXrQBRajNAmJbMVgaHM0B6q/sf5qMzQO2e/5rwwDNAxMn5BibeM0DF3WijhvszQKNvKbASGTRAyoF2bco2NEASEOobrlQ0QCKcffy9cjRAq7qKUPqQNECDoctZY680QH62W1r5zTRAKR+4lLzsNEBEUcBLrQs1QDmktsLLKjVAQuNAPRhKNUBx4Gj/kmk1QKwInU08iTVAYfiwbBSpNUAhEd6hG8k1QCcQxDJS6TVArKVpZbgJNkAjDT2ATio2QEemFMoUSzZAMI8vigtsNkAiPzYIM402QFEiO4yLrjZAnja7XhXQNkAfqZ7I0PE2QJR0ORO+EzdA4wBMiN01N0BawwNyL1g3QPzf+xq0ejdAmcs9zmudN0AK70HXVsA3QC5L8IF14zdA6R2hGsgGOEAoiB3uTio4QMg0oEkKTjhAaADWevpxOEBeot7PH5Y4QHhWTZd6ujhA1ocpIAvfOECmfO+50QM5QAQDkbTOKDlAtx52YAJOOUDzt30ObXM5QDhL/g8PmTlAHJrGtui+OUASXR5V+uQ5QGD2xj1ECzpA9iX8w8YxOkBivnQ7glg6QL5aY/h2fzpA0RV3T6WmOkAWQtyVDc46QNoiPSGw9TpAjqbCR40dO0ACIhVgpUU7QMEMXcH4bTtAmr5Dw4eWO0AmLvS9Ur87QHKwGwpa6DtAvrnqAJ4RPEBtnxX8Hjs8QAFb1VXdZDxALE7oaNmOPEAsCJOQE7k8QCcMoSiM4zxAq5hljUMOPUB1cLwbOjk9QESkCjFwZD1A410/K+aPPUBJrNRonLs9QBlR0EiT5z1AII/EKssTPkAM+tBuREA+QH1Ho3X/bD5AGyF4oPyZPkDx9xtRPMc+QBzZ6+m+9D5AkEPWzYQiP0As/1tgjlA/QPv0kAXcfj9A2AgdIm6tP0Az9DwbRdw/QAqRYauwBUBASEaMnWEdQECqzZ6XNTVAQM2BZc0sTUBAolT5ckdlQEDCQMC8hX1AQEm7bd/nlUBAYSYDEG6uQECMRNCDGMdAQHysc3Dn30BAoz3bC9v4QEBzlUSM8xFBQEiFPSgxK0FA+4ikFpREQUAmPqmOHF5BQCXczMfKd0FAuazi+Z6RQUBdhRBdmatBQGJBzym6xUFAqDzrmAHgQUASz4Tjb/pBQMXIEEMFFUJA/+5Y8cEvQkDDeXwopkpCQCCS8CKyZUJAWdGAG+aAQkCtwE9NQpxCQNlZ1/PGt0JAdojpSnTTQkD4q7COSu9CQHEasPtJC0NAL6TEznInQ0D8FyVFxUNDQDjIYpxBYENAohBqEuh8Q0AJ3YLluJlDQKIwUVS0tkNALq7VndrTQ0AAIW4BLPFDQLYG1r6oDkRAthknFlEsRECd3NlHJUpEQFcmxpQlaERAGK8jPlKGREAdnoqFq6REQEwY9Kwxw0RAnc+69uThREBKk5ulxQBFQPrgtfzTH0VAnHaMPxA/RUAj5QWyel5FQDQkbZgTfkVAjSZyN9udRUBdbyrU0b1FQGSoEbT33UVAETkKHU3+RUBm3l1V0h5GQLZDvqOHP0ZAapxFT21gRkCCPnefg4FGQAc+QNzKokZAdQn4TUPERkDzBmE97eVGQIIyqfPIB0dABb1qutYpR0BWrKzbFkxHQCh846GJbkdA1b/xVy+RR0BAxShJCLRHQII4ScEU10dAjciDDFX6R0DizHl3yR1IQBfsPU9yQUhAZ8NU4U9lSEAsj7V7YolIQG3UymyqrUhASAtzAyjSSEBfSgGP2/ZIQFvzPV/FG0lAUGBnxOVASUAjkjIPPWZJQBLgy5DLi0lAGajXmpGxSUBzAHN/j9dJQA9qNJHF/UlAKoQsIzQkSkDZwOaI20pKQJkaaha8cUpAD8s5INaYSkCyAlb7KcBKQJahPP2350pAO/Hpe4APS0CHX9nNgzdLQMQ6BkrCX0tAn27sRzyIS0B1Qokf8rBLQIoYXCnk2UtAXi5nvhIDTEBEXjA4fixMQOrhwfAmVkxAIharQg2ATECrPwGJMapMQEpRYB+U1ExA5LLrYTX/TEC4CU+tFSpNQPIBv141VU1ANhn605SATUBhaklrNKxNQJR6gYMU2E1ASgcDfDUETkC41bu0lzBOQESDJ447XU5AV1dQaSGKTkBMFtCnSbdOQIXV0Ku05E5A8dAN2GIST0CZQdSPVEBPQHY1BDeKbk9AomgRMgSdT0CtHwTmwstPQDwDerjG+k9Ac37TBwgVUEC6CiupzyxQQCUq9XO6RFBAENAvnMhcUECM0CVW+nRQQA5Sb9ZPjVBAtz/yUcmlUEBivOL9Zr5QQEOWww8p11BAPLtmvQ/wUEDWre08GwlRQPv6ycRLIlFARLC9i6E7UUAB09vIHFVRQP3XiLO9blFA4Rt7g4SIUUBKXLtwcaJRQKUxpbOEvFFAq4nnhL7WUUCZIoUdH/FRQB0H1bamC1JABAuDilUmUkCSSJDSK0FSQJSeU8kpXFJAPy96qU93UkC43weunZJSQFXYVxIUrlJAswUdErPJUkB1mmLpeuVSQM6RjNRrAVNAvjJYEIYdU0AslNzZyTlTQKwhi243VlNABSEwDM9yU0CZOPPwkI9TQH32V1t9rFNAU1g+ipTJU0AIVOO81uZTQERh4TJEBFRAsQMxLN0hVEAAVinpoT9UQNeVgKqSXVRAdrBMsa97VEAp0AM/+ZlUQKnqfJVvuFRAMVDw9hLXVEBqO/il4/VUQEZikeXhFFVAkIcb+Q00VUBpDVokaFNVQI2IdKvwclVAiFT30qeSVUC3KNTfjbJVQBauYhej0lVAGBZhv+fyVUAwsvQdXBNWQFmMqnkANFZAZAB4GdVUVkBKVrtE2nVWQE1dPEMQl1ZA8QctXXe4VkAGCSrbD9pWQHRxOwba+1ZA9E7VJ9YdV0DRS9iJBEBXQHRPknZlYldA7x+/OPmEV0BqBIkbwKdXQJdoiWq6yldAAoHJcejtV0BS8MJ9ShFYQJhtYNvgNFhAfWv+16tYWEBkwGvBq3xYQJ5P6uXgoFhAf7MvlEvFWEB96GUb7OlYQD/5K8vCDllAtKuW888zWUA1LzHlE1lZQI/L/fCOfllAH5F2aEGkWUDyCY6dK8pZQOfrr+JN8FlA5cvBiqgWWkDs0SPpOz1aQIZusVEIZFpA8hDCGA6LWkCB3imTTbJaQAJrOhbH2VpAN3LD93oBW0BlkhOOaSlbQNsH+S+TUVtAy2nCNPh5W0D5Zz/0mKJbQKmJwcZ1y1tAmO0cBY/0W0AeC6kI5R1cQEl0QSt4R1xAXJlGx0hxXEAtjZ43V5tcQMDKtdejxVxACvx/Ay/wXEDQwXgX+RpdQL98pHACRl1AeReRbEtxXUAq0lZp1JxdQPMOmcWdyF1ArB+H4Kf0XUDLFN0Z8yBeQIiN5NF/TV5ALol1aU56XkCEOfdBX6deQLvWYL2y1F5AQnQ6PkkCX0AA150nIzBfQMJMN91AXl9A8IRGw6KMX0BVap8+SbtfQIT+qrQ06l9AFBu0xbIMYEBka7YUbiRgQOAq83pMPGBAS1xNLE5UYEBJu/Rcc2xgQL4tZkG8hGBABzZsDimdYECnZR/5ubVgQLnQ5jZvzmBABYJ4/UjnYEDE79mCRwBhQBJxYP1qGWFA+rOxo7MyYUBdNMSsIUxhQFiz30+1ZWFAdq+dxG5/YUCP3elCTplhQFSiAgNUs2FAm4x5PYDNYUBC0DMr0+dhQPzBagVNAmJAolOsBe4cYkBWkdtltjdiQFYfMWCmUmJAl7g7L75tYkD2reAN/ohiQGRmXDdmpGJAkd9C5/a/YkB4L4BZsNtiQKEGWcqS92JAJDNrdp4TY0B0JK6a0y9jQNFvc3QyTGNAtFVnQbtoY0DOR5E/boVjQN9vVK1LomNAWDdwyVO/Y0DDzwDThtxjQPe7fwnl+WNAAFrErG4XZEAGbgT9IzVkQM6t1DoFU2RAIU0ppxJxZED+ilaDTI9kQKo/ERGzrWRAZGtvkkbMZEA8xuhJB+tkQHFQV3r1CWVAzuP3ZhEpZUDQxWpTW0hlQK86tIPTZ2VANxk9PHqHZUBuX9PBT6dlQELIqllUx2VA6GFdSYjnZUAqJezW6wdmQJaNv0h/KGZAjDKo5UJJZkA3Yd/0NmpmQES3B75bi2ZAxb4tibGsZkC0isieOM5mQINUukfx72ZAihpRzdsRZ0BpP0d5+DNnQDEqxJVHVmdAxOdcbcl4Z0DUzBRLfptnQAEZXnpmvmdA2JoaR4LhZ0DJVJz90QRoQBUjpupVKGhAj2JsWw5MaECemJWd+29oQOsbO/8dlGhALr7pznW4aEDxdqJbA91oQEsP2/TGAWlAqM5+6sAmaUBgKO+M8UtpQKdqBC1ZcWlAJm4OHPiWaUDKRtWrzrxpQIr1mS7d4mlAPRsX9yMJakBSrIFYoy9qQOCliaZbVmpAccNaNU19akAHNp1ZeKRqQCBcdmjdy2pAz3qJt3zzakDwd/icVhtrQECVZG9rQ2tA5Czvhbtra0Cubjo4R5RrQKUeat4OvWtAo1Qk0RLma0ADPZJpUw9sQIPaYAHROGxAEMnB8otibEAHAmyYhIxsQEyhnE27tmxApKsXbjDhbEAy1ihW5AttQBxPpGLXNm1AXYfn8AlibUCY/dlefI1tQHAK7govuW1Asa0hVCLlbUDeXP+ZVhFuQNzSnjzMPW5A4+ClnINqbkBvQEkbfZduQMpmTRq5xG5AalkH/DfybkDAg10j+h9vQDeOyPP/TW9AbDZU0Ul8b0C2KKAg2KpvQL7a4Ear2W9A2jPw1GEEcEC8tv/XEBxwQJP1GuDiM3BAexAKIdhLcECruOHO8GNwQLKhAx4tfHBARfMeQ42UcEDeuzBzEa1wQN1jhOO5xXBAZCG0yYbecEDgbKlbePdwQD52nc+OEHFAuZoZXMopcUCA2/c3K0NxQOZUY5qxXHFAUbbYul12cUDYuibRL5BxQJWibhUoqnFAr6wkwEbEcUD8kRAKjN5xQJQATiz4+HFA2BdNYIsTckBc5dLfRS5yQHfi+eQnSXJAlHIyqjFkckBAYkNqY39yQNpmSmC9mnJANJ+8xz+2ckDCFGfc6tFyQJg9b9q+7XJAMX9T/rsJc0DuseuE4iVzQEulaasyQnNA/6RZr6xec0C6/qLOUHtzQLSIiEcfmHNACimpWBi1c0DfXQBBPNJzQEjG5j+L73NA7asSlQUNdECpjZiAqyp0QMCq60J9SHRAAo/eHHtmdECxn6NPpYR0QD2pzRz8onRA121Qxn/BdEC2NIGOMOB0QGxaF7gO/3RA2uEshhoedUAQBj88VD11QAXNLh68XHVALZtBcFJ8dUDFxyF3F5x1QEMy33cLvHVAWNjvty7cdUD6bDB9gfx1QD7w5A0EHXZAHki5sLY9dkAX2sGsmV52QJslfEmtf3ZAnV/PzvGgdkDEDg2FZ8J2QKuo8bQO5HZA+y+lp+cFd0Bz07um8id3QOSNNvwvSndA88aD8p9sd0AR9X/UQo93QBlAdu0YsndABiUhiSLVd0CTGqvzX/h3QMs2r3nRG3hAmtU5aHc/eEAqQMkMUmN4QIlVTrVhh3hA9jMtsKareEBR4z1MIdB4QIMAzdjR9HhA5WmcpbgZeUCE7OMC1j55QLHyUUEqZHlAQjMMsrWJeUAFYrCmeK95QCjhVHFz1XlAr3OJZKb7eUDv8FfTESJ6QPn4RBG2SHpAUapQcpNvekBtWPdKqpZ6QGVDMvD6vXpAplB4t4XlekDExL72Sg17QFb+eQRLNXtAyjGeN4Zde0CZJqDn/IV7QEj1dWyvrntAo8aXHp7Xe0AQlABXyQB8QATpLm8xKnxAcKUlwdZTfECbwWynuX18QNISEn3ap3xAWhGqnTnSfECKn1Bl1/x8QAPSqTC0J31AHLniXNBSfUBMK7JHLH59QBiRWU/IqX1A0rGl0qTVfUC4ge8wwgF+QDzxHMogLn5Adb2h/sBafkDZQYAvo4d+QPxKSr7HtH5A2eohDS/ifkAHTrp+2Q9/QFCSWHbHPX9Ae57UV/lrf0Bg+5mHb5p/QBOuqGoqyX9AphOWZir4f0Dt3sbwtxOAQKAoKaF9K4BATTIfeGZDgEDJsKKpcluAQFYz+mmic4BAOpW57fWLgEAlcMJpbaSAQBGPRBMJvYBA52G+H8nVgEDJcf3Ere6AQAbWHjm3B4FAwKmPsuUggUAugg1oOTqBQLLlppCyU4FAeMO7Y1FtgUDd6/0YFoeBQH2JcegAoYFA/pptChK7gUB6bZy3SdWBQMMX/Cio74FAPfbely0KgkB1J+w92iSCQH4JIFWuP4JA9rfMF6pagkDbiprAzXWCQPGViIoZkYJAJyntsI2sgkB8UXZvKsiCQMVaKgLw44JAIFJopd7/gkA6ieiV9huDQE4avRA4OINA02xSU6NUg0Ahu2+bOHGDQKuYNyf4jYNAE3koNeKqg0ADOB0E98eDQNehTdM25YNABf1O4qEChEBJlBRxOCCEQMRB8L/6PYRAu/qSD+lbhEA9XA2hA3qEQJI40LVKmIRAhSWtj762hEBgC9dwX9WEQPe04pst9IRATGDHUykThUArUN/bUjKFQI5e6HeqUYVA5Y8EbDBxhUA1p7r85JCFQPm69m7IsIVAF8sKCNvQhUB6V68NHfGFQKr3A8aOEYZAN/OPdzAyhkAQ20JpAlOGQLcjdeIEdIZARcDoKjiVhkCLvsmKnLaGQNzjrkoy2IZA4Uqas/n5hkBMAvoO8xuHQIGsqKYePodABCDuxHxgh0AfCYC0DYOHQCyMgsDRpYdA8+iINMnIh0D3HpZc9OuHQLGSHYVTD4hAybMD++YyiEAfpJ4Lr1aIQBLgtgSseohAgOeHNN6eiEDX58DpRcOIQCZnhXPj54hAIfBtIbcMiUA0v4hDwTGJQGxwWioCV4lAqa7eJnp8iUCO44iKKaKJQJfoRKcQyIlAMLl3zy/uiUDWJQBWhxSKQCOIN44XO4pAJXjyy+BhikCDgoFj44iKQMjfsakfsIpAvSzO85XXikDUI5+XRv+KQKdXbOsxJ4tAa+78RVhPi0DBXpj+uXeLQFMtB21XoItArauT6TDJi0AvuArNRvKLQBN/vHCZG4xAnTx9LilFjEBAAKZg9m6MQDdxFWIBmYxA75MwjkrDjEC3kONA0u2MQJh7otaYGI1AVx1qrJ5DjUB2vcAf5G6NQLXtto5pmo1AblboVy/GjUBChHzaNfKNQPm2J3Z9Ho5AirEriwZLjkBgi1h60XeOQLSCDaXepI5AY9A5bS7SjkC5fF01wf+OQJM1imCXLY9AviVkUrFbj0CQzSJvD4qPQM7ckRuyuI9ApA0SvZnnj0CdAM1cYwuQQJ2O27scI5BAYzVHL/k6kEBYu+7q+FKQQH+Z/SIca5BA5GzsC2ODkECVaIHazZuQQH7I0MNctJBAsEQ9/Q/NkEB9hXi85+WQQCiYgzfk/pBAVGSvpAUYkUADIp06TDGRQHTQPjC4SpFAga3XvElkkUDErfwXAX6RQG/1lHnel5FAzVHaGeKxkUCDs1kxDMyRQGup8/hc5pFAVtzcqdQAkkBSi559cxuSQMQIF645NpJALzh6dSdRkkDDDFIOPWySQJsIf7N6h5JAprw4oOCikkCISQ4Qb76SQPPg5j4m2pJA70cCaQb2kkDMWfnKDxKTQOOLvqFCLpNA/3GeKp9Kk0C+Q0CjJWeTQIJipknWg5NAQeAuXLGgk0AaB5QZt72TQLDh7MDn2pNAWcStkUP4k0Dz1qjLyhWUQMOfDq99M5RA7o5ufFxRlEDNird0Z2+UQB59ONmejZRA9OCg6wKslECPUQHuk8qUQNoZzCJS6ZRABMXVzD0IlUCxr1UvVyeVQBma5o2eRpVABDuHLBRmlUCb05pPuIWVQPnD6TuLpZVA3CCiNo3FlUDmSViFvuWVQOyAB24fBpZAEYISN7AmlkDPHEQncUeWQNnNz4ViaJZAz1lSmoSJlkAOadKs16qWQCskwQVczJZAcdH67RHulkBHc8eu+Q+XQHtn25ETMpdAgQdY4V9Ul0CCSczn3naXQJJiNfCQmZdAnGn/RXa8l0Bh+wU1j9+XQFfflAncAphAka1oEF0mmEBxda+WEkqYQJplCer8bZhAknSJWBySmECACrYwcbaYQOGricH72phAOaVzWrz/mEDGt1hLsySZQA/Hk+TgSZlAwIf2dkVvmUA7L8pT4ZSZQFUk0My0uplAC7FCNMDgmUBHtdXcAweaQK5atxmALZpAUcmQPjVUmkC83YafI3uaQL/fOpFLoppAcDrLaK3JmkAzNdR7SfGaQNStcCAgGZtAwNM6rTFBm0Ah5Ex5fmmbQGznQdwGkptAsm82Lsu6m0AtWMnHy+ObQOqFHAIJDZxAlKnVNoM2nEAxAh/AOmCcQFYhqPgvipxAKrCmO2O0nECxNdfk1N6cQD3efVCFCZ1A+0Nn23Q0nUC6OOnio1+dQK2Q48QSi51Are7A38G2nUBdkXeSseKdQJghijziDp5AGIIIPlQ7nkBDoJD3B2ieQEJGT8r9lJ5AFO4AGDbCnkBBlvJCse+eQGGXAq5vHZ9AFHuhvHFLn0Av1NLSt3mfQCsYLlVCqJ9Aq3nfqBHXn0BUYtQZEwOgQL4d8S3AGqBAsro9RJAyoEAkH36Qg0qgQOW7wkaaYqBA1P1om9R6oECjvxvDMpOgQG280/K0q6BAzQLYX1vEoECzaL4/Jt2gQOD/a8gV9qBADosVMCoPoUDN8z+tYyihQPLAwHbCQaFA5I2+w0ZboUB1grHL8HShQHLLY8bAjqFA8RPy67aooUBN/8t008KhQMCjtJkW3aFA6QXDk4D3oUDRlGKcERKiQL+mU+3JLKJAx/arwKlHokAOI9dQsWKiQMwrl9jgfaJA8fIEkziZokDCvJC7uLSiQPOwAo5h0KJApVx7RjPsokAZNXQhLgijQCgbwFtSJKNAgN+LMqBAo0CIx17jF12jQEcTG6y5eaNAzYP+yoWWo0CP4qJ+fLOjQHOJ/gWe0KNAu+tkoOrto0CVH4eNYgukQLJodA0GKaRAccOaYNVGpEDxcMfH0GSkQPSDJ4T4gqRAim5I10yhpECakBgDzr+kQBrH50l83qRAW/xn7lf9pEDtuK0zYRylQHm1MF2YO6VAZm3Mrv1apUBhssBskXqlQL1AsttTmqVAlVSrQEW6pUADQBzhZdqlQPwB3AK2+qVAJ94o7DUbpkCS9ajj5TumQETgajDGXKZAuUfmGdd9pkArgvznGJ+mQPEu+eKLwKZAlNOSUzDipkDneeuCBgSnQP1OkboOJqdAF0N/RElIp0Beqh1rtmqnQMneQnlWjadAseIzuimwp0B4BKV5MNOnQByDugNr9qdAuTMJpdkZqEAMKJeqfD2oQMdV3GFUYahAHz/DGGGFqEAWnKkdo6moQNkEYb8azqhAF50vTcjyqEBXwNAWrBepQFCvdWzGPKlAIj7GnhdiqUDUg+H+n4epQI6KXt5fralABAFNj1fTqUDR7DVkh/mpQO9dHLDvH6pACiN+xpBGqkAvf1T7am2qQDngFKN+lKpAb5axEsy7qkAxjZqfU+OqQLAEvp8VC6tAwUyJaRIzq0CigOlTSlurQB1ETLa9g6tAeIGg6Gysq0CgKFdDWNWrQHTvYx+A/qtAFxM+1uQnrEB9GuHBhlGsQOSZzTxme6xAvvcJooOlrEBzMiNN38+sQG6nLZp5+qxARdvF5VIlrUAXQxGNa1CtQOMOv+3De61AZPUIZlynrUDFALRUNdOtQKlcERlP/61AZSX/EqorrkBiOOmiRliuQMAFyiklha5ACGMrCUayrkBmXyejqd+uQMcYaVpQDa9AYJItkjo7r0BqjESuaGmvQBhdERPbl69A3sqLJZLGr0DF50BLjvWvQDT3KfVnErBA6Y+/tCsqsEBvUQqYEkKwQGWy/9IcWrBAlf3hmUpysEB9w0AhnIqwQKxM+Z0Ro7BAmAw3Rau7sEA8FXRMadSwQFaLeelL7bBAURtgUlMGsUDobpC9fx+xQFKjw2HROLFAW8ADdkhSsUDyL6wx5WuxQIY2asynhbFAD2w9fpCfsUDGNXh/n7mxQJxAwAjV07FAS/wOUzHusUBMF7KXtAiyQFX7SxBfI7JAqUrU9jA+skAZXpiFKlmyQMTDO/dLdLJAkr64hpWPskBWxmBvB6uyQN8I3eyhxrJAlusuO2XiskDzjbCWUf6yQK9MFTxnGrNAwEVqaKY2s0D23BZZD1OzQJtB3Uuib7NAnPTafl+Ms0CVT4kwR6mzQKMMvp9ZxrNA+M6rC5fjs0BGrOKz/wC0QNK2UNiTHrRAkohCuVM8tEDazmOXP1q0QPjWv7NXeLRAnRvCT5yWtEAM0zatDbW0QDF+Sw6s07RAXHiPtXfytEAeiPTlcBG1QLNwz+KXMLVAZ4TY7+xPtUDMNyxRcG+1QNG1S0sij7VAlnQdIwOvtUBRy+0dE8+1QOSIb4FS77VAYIu8k8EPtkBnWFabYDC2QHi2Jt8vUbZAFUeApi9ytkC6IR85YJO2QPFvKd/BtLZAEQow4VTWtkACFS+IGfi2QOagjh0QGrdArkgj6zg8t0Cc0i47lF63QJXRYFgigbdAqUfXjeOjt0A5SR8n2Ma3QEahNXAA6rdAlnaHtVwNuEDl8fJD7TC4QN/kx2iyVLhAXHLIcax4uEBKtymt25y4QLp0lGlAwbhA27ol9trluED5lG+iqwq5QHa2eb6yL7lAryjCmvBUuUAa+j2IZXq5QCvuWdgRoLlAWy773PXFuUAs/H/oEey5QDpkwE1mErpAWvIOYPM4ukCcZjlzuV+6QKNridu4hrpAxE3F7fGtukBWszD/ZNW6QAtWjWUS/bpAZr0bd/oku0AX+puKHU27QMNiTvd7dbtAjVH0FBaeu0Dk4tA77Ma7QGC1qcT+77tAvarHCE4ZvED3qfdh2kK8QGRiiyqkbLxAOBBavauWvEDgQcF18cC8QKeepa9167xAda5zxzgWvUDAoiAaO0G9QKAgKwV9bL1A8guc5v6XvUDwUwcdwcO9QKzAjAfE771A38HYBQgcvkDiPiV4jUi+QOFnOr9Udb5AQ4hvPF6ivkAj2qtRqs++QFZbZ2E5/b5AWqOrzgsrv0CmuhT9IVm/QDPz0VB8h79AUMKmLhu2v0CIm+v7/uS/QJNmRw8UCsBA1a6KfsshwEBU9U3/pTnAQHjEa8WjUcBAAlMLBcVpwEBv9aDyCYLAQOiP7sJymsBAFQkEq/+ywEBdvT/gsMvAQPTyTpiG5MBAhE4uCYH9wECQSCppoBbBQHuj3+7kL8FAM+I70U5JwUCvv31H3mLBQPumNYmTfMFA/ytGzm6WwUACheROcLDBQNgEmUOYysFAuZU/5ebkwUD0NAhtXP/BQC5vdxT5GcJAct1mFb00wkDuogWqqE/CQHLr2Ay8asJArGq8ePeFwkAD3OIoW6HCQGqD1ljnvMJAtK55RJzYwkDNNwcoevTCQKUHE0CBEMNA3pmKybEsw0BHgbUBDEnDQPzsNSaQZcNAfy4JdT6Cw0BrQIgsF5/DQOlNaIsavMNAODu70EjZw0B5LvA7ovbDQO4Z1AwnFMRAS0aSg9cxxECW3rTgs0/EQCF8JWW8bcRAx7MtUvGLxED9o3fpUqrEQD2DDm3hyMRA+i9fH53nxEChwDhDhgbFQDcVzRudJcVAGWmx7OFExUAF5t75VGTFQAY4s4f2g8VAvSHx2sajxUA2EsE4xsPFQOa6seb048VAOae4KlMExkBY1DJL4STGQDxK5Y6fRcZAsbX9PI5mxkC1AhOdrYfGQIH4Jff9qMZApNWhk3/KxkDa7Vy7MuzGQApImbcXDsdApT0F0i4wx0ABG7xUeFLHQBXARor0dMdA4kKcvaOXx0AIkiI6hrrHQBQZr0uc3cdA+GSHPuYAyEAJymFfZCTIQOUKZvsWSMhAy/8tYP5ryEC+P8bbGpDIQM/JrrxstMhA56/bUfTYyECZwrXqsf3IQFk9G9elIslAk3RgZ9BHyUDRg1DsMW3JQNT9LbfKkslA1pyzGZu4yUBa9BRmo97JQA8k/+7jBMpAHouZB10rykBpfYYDD1LKQN344zb6eMpAyVxM9h6gykBdIdeWfcfKQM+QGW4W78pAmYEn0ukWy0AmEZQZ+D7LQIZgcptBZ8tAN1FWr8aPy0AGRFWth7jLQBjYBu6E4ctAtKuFyr4KzEAhHnCcNTTMQAkS6b3pXcxA7LGYiduHzECuNK1aC7LMQFOk24x53MxA5aRgfCYHzUAnPQGGEjLNQHSgCwc+Xc1AHvlXXamIzUDyNEnnVLTNQOXRzQNB4M1A86xgEm4MzkA60Qlz3DjOQPBIX4aMZc5Aiu+FrX6SzkByRDJKs7/OQPY/qb4q7c5AbijBbeUaz0BKaeK640jPQGBrCAomd89AzG3Cv6ylz0ARYTRBeNTPQDbhC3rEAdBAwzxen28Z0EAu2wTEPTHQQJJovxsvSdBAxhWa2kNh0EA5Ce40fHnQQBHRYV/YkdBATNXpjliq0EAwy8j4/MLQQMsokNLF29BAhZkgUrP00EBbc6qtxQ3RQGcsrhv9JtFAqtH80llA0UDmfbgK3FnRQMjRVPqDc9FAKWyX2VGN0UBwY5jgRafRQJy/wkdgwdFAofTUR6Hb0UAYXuEZCfbRQPy6TveXENJAwqrYGU4r0kCSKpC7K0bSQKMT3BYxYdJAS5p5Zl580kBrzXzls5fSQCoXUc8xs9JA0L25X9jO0kAHZtLSp+rSQDOVD2WgBtNABTU/U8Ii00DHF4naDT/TQP58bziDW9NAe5fPqiJ400B/E+Jv7JTTQFKeO8bgsdNAAm7N7P/O00BYyuUiSuzTQJaWMKi/CdRAk9u3vGAn1EBOU+SgLUXUQJn0fZUmY9RAG4Cs20uB1EAJDvi0nZ/UQFOcSWMcvtRARJ7rKMjc1EBAjIpIofvUQBB1NQWoGtVAXI9eotw51UBkzNtjP1nVQKFr543QeNVAwI4gZZCY1UAuz4suf7jVQL/Tky+d2NVA+OcJrur41UB8kybwZxnWQNsyijwVOtZAPJE92vJa1kBvgrIQAXzWQKd+xCdAndZAQT65Z7C+1kBMV0EZUuDWQDLbeIUlAtdAyfXn9Sok10BXjYO0YkbXQPnirQvNaNdAwTQ3RmqL10DrX16vOq7XQN2E0ZI+0ddAS6uuPHb010DYZ4T54RfYQKqCUhaCO9hAbp6K4FZf2EAg4RCmYIPYQOycPLWfp9hA7frYXBTM2EATpiXsvvDYQJN317KfFdlAWCQZAbc62UDh6osnBWDZQP1CSHeKhdlAsI3eQUer2UCsxlfZO9HZQNA2NpBo99lAIid2uc0d2kCnlY6oa0TaQFzqcbFCa9pAMK6OKFOS2kAdQtBinbnaQPWXn7Uh4dpAOOzjduAI20BpgAP92TDbQFdX5J4OWdtAivHss36B20C9CwWUKqrbQI1dlpcS09tA0VmNFzf820Af8FltmCXcQMhO8PI2T9xA4KbJAhN53EBs8OT3LKPcQLOwxy2FzdxAwcB+ABz43ECwFZ/M8SLdQBuKRu8GTt1AG6gcxlt53UBbdVOv8KTdQF0/qAnG0N1A8WlkNNz83UDfPV6PMyneQHS5+XrMVd5APGIpWKeC3kBLF2+IxK/eQL3l3G0k3d5AWt0Va8cK30CS507jrTjfQKeeTzrYZt9AyCZz1EaV30B0CKkW+sPfQGULdmby8t9A6In6FBgR4EDi/+vj2SjgQINDtNO+QOBAh41EGMdY4ECK5Nrl8nDgQLiOAnFCieBAvoOU7rWh4EAB4LeTTbrgQN1X4pUJ0+BA/qvYKurr4EBdHq+I7wThQI7nyeUZHuFASK3deGk34UAE+e943lDhQOSvVx15auFAw4q9nTmE4UBGjxwyIJ7hQLOJwhItuOFADodQeGDS4UCEULubuuzhQOfmS7Y7B+JAjf+fAeQh4kBCgaq3szziQGMCtBKrV+JAr0dbTcpy4kBrw5WiEY7iQOMVsE2BqeJA/Y1Oi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OzJGCpAhHfXcGA/KkD19nkEMGYqQJTJTvs4jSpADAIxqnu0KkDEK3lm+NsqQFoE/oWvAytAUTYVX6ErK0CzFJRIzlMrQMxX0Jk2fCtAFtugqtqkK0AjXF7Tus0rQJ865GzX9itAjjmR0DAgLECGQUhYx0ksQBokcV6bcyxAVWD5Pa2dLEB16FRS/ccsQLPofveL8ixAKI/6iVkdLUAA1dNmZkgtQLRIoOuycy1Abdl/dj+fLUC3ox1mDMstQEG/sBka9y1A3Q398GgjLkCaC1RM+U8uQEaglYzLfC5A9PEwE+CpLkC6OCVCN9cuQNqTAnzRBC9A8t/qI68yL0BwjpKd0GAvQGt+QU02jy9AjNbTl+C9L0Bf4Lriz+wvQF/y/kkCDjBA3oQdib8lMEDWGFTinz0wQLTtiYmjVTBADwLzssptMEAbhRCTFYYwQMNIsV6EnjBAhDTyShe3MEDcuD6Nzs8wQGlDUVuq6DBAsLMz66oBMUCi0D9z0BoxQLu+HyobNDFA03bORotNMUCqPZgAIWcxQB8cG4/cgDFACVhHKr6aMUDh7V8KxrQxQAoL+2f0zjFA1IgCfEnpMUAsaLR/xQMyQBpOo6xoHjJA4gC3PDM5MkDc5SxqJVQyQB6AmG8/bzJAyu/jh4GKMkAZclDu66UyQDridt5+wTJA0zpIlDrdMkBYGA5MH/kyQAo8a0ItFTNA3A9ctGQxM0D4KjffxU0zQBTXrQBRajNAmJbMVgaHM0B6q/sf5qMzQO2e/5rwwDNAxMn5BibeM0DF3WijhvszQKNvKbASGTRAyoF2bco2NEASEOobrlQ0QCKcffy9cjRAq7qKUPqQNECDoctZY680QH62W1r5zTRAKR+4lLzsNEBEUcBLrQs1QDmktsLLKjVAQuNAPRhKNUBx4Gj/kmk1QKwInU08iTVAYfiwbBSpNUAhEd6hG8k1QCcQxDJS6TVArKVpZbgJNkAjDT2ATio2QEemFMoUSzZAMI8vigtsNkAiPzYIM402QFEiO4yLrjZAnja7XhXQNkAfqZ7I0PE2QJR0ORO+EzdA4wBMiN01N0BawwNyL1g3QPzf+xq0ejdAmcs9zmudN0AK70HXVsA3QC5L8IF14zdA6R2hGsgGOEAoiB3uTio4QMg0oEkKTjhAaADWevpxOEBeot7PH5Y4QHhWTZd6ujhA1ocpIAvfOECmfO+50QM5QAQDkbTOKDlAtx52YAJOOUDzt30ObXM5QDhL/g8PmTlAHJrGtui+OUASXR5V+uQ5QGD2xj1ECzpA9iX8w8YxOkBivnQ7glg6QL5aY/h2fzpA0RV3T6WmOkAWQtyVDc46QNoiPSGw9TpAjqbCR40dO0ACIhVgpUU7QMEMXcH4bTtAmr5Dw4eWO0AmLvS9Ur87QHKwGwpa6DtAvrnqAJ4RPEBtnxX8Hjs8QAFb1VXdZDxALE7oaNmOPEAsCJOQE7k8QCcMoSiM4zxAq5hljUMOPUB1cLwbOjk9QESkCjFwZD1A410/K+aPPUBJrNRonLs9QBlR0EiT5z1AII/EKssTPkAM+tBuREA+QH1Ho3X/bD5AGyF4oPyZPkDx9xtRPMc+QBzZ6+m+9D5AkEPWzYQiP0As/1tgjlA/QPv0kAXcfj9A2AgdIm6tP0Az9DwbRdw/QAqRYauwBUBASEaMnWEdQECqzZ6XNTVAQM2BZc0sTUBAolT5ckdlQEDCQMC8hX1AQEm7bd/nlUBAYSYDEG6uQECMRNCDGMdAQHysc3Dn30BAoz3bC9v4QEBzlUSM8xFBQEiFPSgxK0FA+4ikFpREQUAmPqmOHF5BQCXczMfKd0FAuazi+Z6RQUBdhRBdmatBQGJBzym6xUFAqDzrmAHgQUASz4Tjb/pBQMXIEEMFFUJA/+5Y8cEvQkDDeXwopkpCQCCS8CKyZUJAWdGAG+aAQkCtwE9NQpxCQNlZ1/PGt0JAdojpSnTTQkD4q7COSu9CQHEasPtJC0NAL6TEznInQ0D8FyVFxUNDQDjIYpxBYENAohBqEuh8Q0AJ3YLluJlDQKIwUVS0tkNALq7VndrTQ0AAIW4BLPFDQLYG1r6oDkRAthknFlEsRECd3NlHJUpEQFcmxpQlaERAGK8jPlKGREAdnoqFq6REQEwY9Kwxw0RAnc+69uThREBKk5ulxQBFQPrgtfzTH0VAnHaMPxA/RUAj5QWyel5FQDQkbZgTfkVAjSZyN9udRUBdbyrU0b1FQGSoEbT33UVAETkKHU3+RUBm3l1V0h5GQLZDvqOHP0ZAapxFT21gRkCCPnefg4FGQAc+QNzKokZAdQn4TUPERkDzBmE97eVGQIIyqfPIB0dABb1qutYpR0BWrKzbFkxHQCh846GJbkdA1b/xVy+RR0BAxShJCLRHQII4ScEU10dAjciDDFX6R0DizHl3yR1IQBfsPU9yQUhAZ8NU4U9lSEAsj7V7YolIQG3UymyqrUhASAtzAyjSSEBfSgGP2/ZIQFvzPV/FG0lAUGBnxOVASUAjkjIPPWZJQBLgy5DLi0lAGajXmpGxSUBzAHN/j9dJQA9qNJHF/UlAKoQsIzQkSkDZwOaI20pKQJkaaha8cUpAD8s5INaYSkCyAlb7KcBKQJahPP2350pAO/Hpe4APS0CHX9nNgzdLQMQ6BkrCX0tAn27sRzyIS0B1Qokf8rBLQIoYXCnk2UtAXi5nvhIDTEBEXjA4fixMQOrhwfAmVkxAIharQg2ATECrPwGJMapMQEpRYB+U1ExA5LLrYTX/TEC4CU+tFSpNQPIBv141VU1ANhn605SATUBhaklrNKxNQJR6gYMU2E1ASgcDfDUETkC41bu0lzBOQESDJ447XU5AV1dQaSGKTkBMFtCnSbdOQIXV0Ku05E5A8dAN2GIST0CZQdSPVEBPQHY1BDeKbk9AomgRMgSdT0CtHwTmwstPQDwDerjG+k9Ac37TBwgVUEC6CiupzyxQQCUq9XO6RFBAENAvnMhcUECM0CVW+nRQQA5Sb9ZPjVBAtz/yUcmlUEBivOL9Zr5QQEOWww8p11BAPLtmvQ/wUEDWre08GwlRQPv6ycRLIlFARLC9i6E7UUAB09vIHFVRQP3XiLO9blFA4Rt7g4SIUUBKXLtwcaJRQKUxpbOEvFFAq4nnhL7WUUCZIoUdH/FRQB0H1bamC1JABAuDilUmUkCSSJDSK0FSQJSeU8kpXFJAPy96qU93UkC43weunZJSQFXYVxIUrlJAswUdErPJUkB1mmLpeuVSQM6RjNRrAVNAvjJYEIYdU0AslNzZyTlTQKwhi243VlNABSEwDM9yU0CZOPPwkI9TQH32V1t9rFNAU1g+ipTJU0AIVOO81uZTQERh4TJEBFRAsQMxLN0hVEAAVinpoT9UQNeVgKqSXVRAdrBMsa97VEAp0AM/+ZlUQKnqfJVvuFRAMVDw9hLXVEBqO/il4/VUQEZikeXhFFVAkIcb+Q00VUBpDVokaFNVQI2IdKvwclVAiFT30qeSVUC3KNTfjbJVQBauYhej0lVAGBZhv+fyVUAwsvQdXBNWQFmMqnkANFZAZAB4GdVUVkBKVrtE2nVWQE1dPEMQl1ZA8QctXXe4VkAGCSrbD9pWQHRxOwba+1ZA9E7VJ9YdV0DRS9iJBEBXQHRPknZlYldA7x+/OPmEV0BqBIkbwKdXQJdoiWq6yldAAoHJcejtV0BS8MJ9ShFYQJhtYNvgNFhAfWv+16tYWEBkwGvBq3xYQJ5P6uXgoFhAf7MvlEvFWEB96GUb7OlYQD/5K8vCDllAtKuW888zWUA1LzHlE1lZQI/L/fCOfllAH5F2aEGkWUDyCY6dK8pZQOfrr+JN8FlA5cvBiqgWWkDs0SPpOz1aQIZusVEIZFpA8hDCGA6LWkCB3imTTbJaQAJrOhbH2VpAN3LD93oBW0BlkhOOaSlbQNsH+S+TUVtAy2nCNPh5W0D5Zz/0mKJbQKmJwcZ1y1tAmO0cBY/0W0AeC6kI5R1cQEl0QSt4R1xAXJlGx0hxXEAtjZ43V5tcQMDKtdejxVxACvx/Ay/wXEDQwXgX+RpdQL98pHACRl1AeReRbEtxXUAq0lZp1JxdQPMOmcWdyF1ArB+H4Kf0XUDLFN0Z8yBeQIiN5NF/TV5ALol1aU56XkCEOfdBX6deQLvWYL2y1F5AQnQ6PkkCX0AA150nIzBfQMJMN91AXl9A8IRGw6KMX0BVap8+SbtfQIT+qrQ06l9AFBu0xbIMYEBka7YUbiRgQOAq83pMPGBAS1xNLE5UYEBJu/Rcc2xgQL4tZkG8hGBABzZsDimdYECnZR/5ubVgQLnQ5jZvzmBABYJ4/UjnYEDE79mCRwBhQBJxYP1qGWFA+rOxo7MyYUBdNMSsIUxhQFiz30+1ZWFAdq+dxG5/YUCP3elCTplhQFSiAgNUs2FAm4x5PYDNYUBC0DMr0+dhQPzBagVNAmJAolOsBe4cYkBWkdtltjdiQFYfMWCmUmJAl7g7L75tYkD2reAN/ohiQGRmXDdmpGJAkd9C5/a/YkB4L4BZsNtiQKEGWcqS92JAJDNrdp4TY0B0JK6a0y9jQNFvc3QyTGNAtFVnQbtoY0DOR5E/boVjQN9vVK1LomNAWDdwyVO/Y0DDzwDThtxjQPe7fwnl+WNAAFrErG4XZEAGbgT9IzVkQM6t1DoFU2RAIU0ppxJxZED+ilaDTI9kQKo/ERGzrWRAZGtvkkbMZEA8xuhJB+tkQHFQV3r1CWVAzuP3ZhEpZUDQxWpTW0hlQK86tIPTZ2VANxk9PHqHZUBuX9PBT6dlQELIqllUx2VA6GFdSYjnZUAqJezW6wdmQJaNv0h/KGZAjDKo5UJJZkA3Yd/0NmpmQES3B75bi2ZAxb4tibGsZkC0isieOM5mQINUukfx72ZAihpRzdsRZ0BpP0d5+DNnQDEqxJVHVmdAxOdcbcl4Z0DUzBRLfptnQAEZXnpmvmdA2JoaR4LhZ0DJVJz90QRoQBUjpupVKGhAj2JsWw5MaECemJWd+29oQOsbO/8dlGhALr7pznW4aEDxdqJbA91oQEsP2/TGAWlAqM5+6sAmaUBgKO+M8UtpQKdqBC1ZcWlAJm4OHPiWaUDKRtWrzrxpQIr1mS7d4mlAPRsX9yMJakBSrIFYoy9qQOCliaZbVmpAccNaNU19akAHNp1ZeKRqQCBcdmjdy2pAz3qJt3zzakDwd/icVhtrQECVZG9rQ2tA5Czvhbtra0Cubjo4R5RrQKUeat4OvWtAo1Qk0RLma0ADPZJpUw9sQIPaYAHROGxAEMnB8otibEAHAmyYhIxsQEyhnE27tmxApKsXbjDhbEAy1ihW5AttQBxPpGLXNm1AXYfn8AlibUCY/dlefI1tQHAK7govuW1Asa0hVCLlbUDeXP+ZVhFuQNzSnjzMPW5A4+ClnINqbkBvQEkbfZduQMpmTRq5xG5AalkH/DfybkDAg10j+h9vQDeOyPP/TW9AbDZU0Ul8b0C2KKAg2KpvQL7a4Ear2W9A2jPw1GEEcEC8tv/XEBxwQJP1GuDiM3BAexAKIdhLcECruOHO8GNwQLKhAx4tfHBARfMeQ42UcEDeuzBzEa1wQN1jhOO5xXBAZCG0yYbecEDgbKlbePdwQD52nc+OEHFAuZoZXMopcUCA2/c3K0NxQOZUY5qxXHFAUbbYul12cUDYuibRL5BxQJWibhUoqnFAr6wkwEbEcUD8kRAKjN5xQJQATiz4+HFA2BdNYIsTckBc5dLfRS5yQHfi+eQnSXJAlHIyqjFkckBAYkNqY39yQNpmSmC9mnJANJ+8xz+2ckDCFGfc6tFyQJg9b9q+7XJAMX9T/rsJc0DuseuE4iVzQEulaasyQnNA/6RZr6xec0C6/qLOUHtzQLSIiEcfmHNACimpWBi1c0DfXQBBPNJzQEjG5j+L73NA7asSlQUNdECpjZiAqyp0QMCq60J9SHRAAo/eHHtmdECxn6NPpYR0QD2pzRz8onRA121Qxn/BdEC2NIGOMOB0QGxaF7gO/3RA2uEshhoedUAQBj88VD11QAXNLh68XHVALZtBcFJ8dUDFxyF3F5x1QEMy33cLvHVAWNjvty7cdUD6bDB9gfx1QD7w5A0EHXZAHki5sLY9dkAX2sGsmV52QJslfEmtf3ZAnV/PzvGgdkDEDg2FZ8J2QKuo8bQO5HZA+y+lp+cFd0Bz07um8id3QOSNNvwvSndA88aD8p9sd0AR9X/UQo93QBlAdu0YsndABiUhiSLVd0CTGqvzX/h3QMs2r3nRG3hAmtU5aHc/eEAqQMkMUmN4QIlVTrVhh3hA9jMtsKareEBR4z1MIdB4QIMAzdjR9HhA5WmcpbgZeUCE7OMC1j55QLHyUUEqZHlAQjMMsrWJeUAFYrCmeK95QCjhVHFz1XlAr3OJZKb7eUDv8FfTESJ6QPn4RBG2SHpAUapQcpNvekBtWPdKqpZ6QGVDMvD6vXpAplB4t4XlekDExL72Sg17QFb+eQRLNXtAyjGeN4Zde0CZJqDn/IV7QEj1dWyvrntAo8aXHp7Xe0AQlABXyQB8QATpLm8xKnxAcKUlwdZTfECbwWynuX18QNISEn3ap3xAWhGqnTnSfECKn1Bl1/x8QAPSqTC0J31AHLniXNBSfUBMK7JHLH59QBiRWU/IqX1A0rGl0qTVfUC4ge8wwgF+QDzxHMogLn5Adb2h/sBafkDZQYAvo4d+QPxKSr7HtH5A2eohDS/ifkAHTrp+2Q9/QFCSWHbHPX9Ae57UV/lrf0Bg+5mHb5p/QBOuqGoqyX9AphOWZir4f0Dt3sbwtxOAQKAoKaF9K4BATTIfeGZDgEDJsKKpcluAQFYz+mmic4BAOpW57fWLgEAlcMJpbaSAQBGPRBMJvYBA52G+H8nVgEDJcf3Ere6AQAbWHjm3B4FAwKmPsuUggUAugg1oOTqBQLLlppCyU4FAeMO7Y1FtgUDd6/0YFoeBQH2JcegAoYFA/pptChK7gUB6bZy3SdWBQMMX/Cio74FAPfbely0KgkB1J+w92iSCQH4JIFWuP4JA9rfMF6pagkDbiprAzXWCQPGViIoZkYJAJyntsI2sgkB8UXZvKsiCQMVaKgLw44JAIFJopd7/gkA6ieiV9huDQE4avRA4OINA02xSU6NUg0Ahu2+bOHGDQKuYNyf4jYNAE3koNeKqg0ADOB0E98eDQNehTdM25YNABf1O4qEChEBJlBRxOCCEQMRB8L/6PYRAu/qSD+lbhEA9XA2hA3qEQJI40LVKmIRAhSWtj762hEBgC9dwX9WEQPe04pst9IRATGDHUykThUArUN/bUjKFQI5e6HeqUYVA5Y8EbDBxhUA1p7r85JCFQPm69m7IsIVAF8sKCNvQhUB6V68NHfGFQKr3A8aOEYZAN/OPdzAyhkAQ20JpAlOGQLcjdeIEdIZARcDoKjiVhkCLvsmKnLaGQNzjrkoy2IZA4Uqas/n5hkBMAvoO8xuHQIGsqKYePodABCDuxHxgh0AfCYC0DYOHQCyMgsDRpYdA8+iINMnIh0D3HpZc9OuHQLGSHYVTD4hAybMD++YyiEAfpJ4Lr1aIQBLgtgSseohAgOeHNN6eiEDX58DpRcOIQCZnhXPj54hAIfBtIbcMiUA0v4hDwTGJQGxwWioCV4lAqa7eJnp8iUCO44iKKaKJQJfoRKcQyIlAMLl3zy/uiUDWJQBWhxSKQCOIN44XO4pAJXjyy+BhikCDgoFj44iKQMjfsakfsIpAvSzO85XXikDUI5+XRv+KQKdXbOsxJ4tAa+78RVhPi0DBXpj+uXeLQFMtB21XoItArauT6TDJi0AvuArNRvKLQBN/vHCZG4xAnTx9LilFjEBAAKZg9m6MQDdxFWIBmYxA75MwjkrDjEC3kONA0u2MQJh7otaYGI1AVx1qrJ5DjUB2vcAf5G6NQLXtto5pmo1AblboVy/GjUBChHzaNfKNQPm2J3Z9Ho5AirEriwZLjkBgi1h60XeOQLSCDaXepI5AY9A5bS7SjkC5fF01wf+OQJM1imCXLY9AviVkUrFbj0CQzSJvD4qPQM7ckRuyuI9ApA0SvZnnj0CdAM1cYwuQQJ2O27scI5BAYzVHL/k6kEBYu+7q+FKQQH+Z/SIca5BA5GzsC2ODkECVaIHazZuQQH7I0MNctJBAsEQ9/Q/NkEB9hXi85+WQQCiYgzfk/pBAVGSvpAUYkUADIp06TDGRQHTQPjC4SpFAga3XvElkkUDErfwXAX6RQG/1lHnel5FAzVHaGeKxkUCDs1kxDMyRQGup8/hc5pFAVtzcqdQAkkBSi559cxuSQMQIF645NpJALzh6dSdRkkDDDFIOPWySQJsIf7N6h5JAprw4oOCikkCISQ4Qb76SQPPg5j4m2pJA70cCaQb2kkDMWfnKDxKTQOOLvqFCLpNA/3GeKp9Kk0C+Q0CjJWeTQIJipknWg5NAQeAuXLGgk0AaB5QZt72TQLDh7MDn2pNAWcStkUP4k0Dz1qjLyhWUQMOfDq99M5RA7o5ufFxRlEDNird0Z2+UQB59ONmejZRA9OCg6wKslECPUQHuk8qUQNoZzCJS6ZRABMXVzD0IlUCxr1UvVyeVQBma5o2eRpVABDuHLBRmlUCb05pPuIWVQPnD6TuLpZVA3CCiNo3FlUDmSViFvuWVQOyAB24fBpZAEYISN7AmlkDPHEQncUeWQNnNz4ViaJZAz1lSmoSJlkAOadKs16qWQCskwQVczJZAcdH67RHulkBHc8eu+Q+XQHtn25ETMpdAgQdY4V9Ul0CCSczn3naXQJJiNfCQmZdAnGn/RXa8l0Bh+wU1j9+XQFfflAncAphAka1oEF0mmEBxda+WEkqYQJplCer8bZhAknSJWBySmECACrYwcbaYQOGricH72phAOaVzWrz/mEDGt1hLsySZQA/Hk+TgSZlAwIf2dkVvmUA7L8pT4ZSZQFUk0My0uplAC7FCNMDgmUBHtdXcAweaQK5atxmALZpAUcmQPjVUmkC83YafI3uaQL/fOpFLoppAcDrLaK3JmkAzNdR7SfGaQNStcCAgGZtAwNM6rTFBm0Ah5Ex5fmmbQGznQdwGkptAsm82Lsu6m0AtWMnHy+ObQOqFHAIJDZxAlKnVNoM2nEAxAh/AOmCcQFYhqPgvipxAKrCmO2O0nECxNdfk1N6cQD3efVCFCZ1A+0Nn23Q0nUC6OOnio1+dQK2Q48QSi51Are7A38G2nUBdkXeSseKdQJghijziDp5AGIIIPlQ7nkBDoJD3B2ieQEJGT8r9lJ5AFO4AGDbCnkBBlvJCse+eQGGXAq5vHZ9AFHuhvHFLn0Av1NLSt3mfQCsYLlVCqJ9Aq3nfqBHXn0BUYtQZEwOgQL4d8S3AGqBAsro9RJAyoEAkH36Qg0qgQOW7wkaaYqBA1P1om9R6oECjvxvDMpOgQG280/K0q6BAzQLYX1vEoECzaL4/Jt2gQOD/a8gV9qBADosVMCoPoUDN8z+tYyihQPLAwHbCQaFA5I2+w0ZboUB1grHL8HShQHLLY8bAjqFA8RPy67aooUBN/8t008KhQMCjtJkW3aFA6QXDk4D3oUDRlGKcERKiQL+mU+3JLKJAx/arwKlHokAOI9dQsWKiQMwrl9jgfaJA8fIEkziZokDCvJC7uLSiQPOwAo5h0KJApVx7RjPsokAZNXQhLgijQCgbwFtSJKNAgN+LMqBAo0CIx17jF12jQEcTG6y5eaNAzYP+yoWWo0CP4qJ+fLOjQHOJ/gWe0KNAu+tkoOrto0CVH4eNYgukQLJodA0GKaRAccOaYNVGpEDxcMfH0GSkQPSDJ4T4gqRAim5I10yhpECakBgDzr+kQBrH50l83qRAW/xn7lf9pEDtuK0zYRylQHm1MF2YO6VAZm3Mrv1apUBhssBskXqlQL1AsttTmqVAlVSrQEW6pUADQBzhZdqlQPwB3AK2+qVAJ94o7DUbpkCS9ajj5TumQETgajDGXKZAuUfmGdd9pkArgvznGJ+mQPEu+eKLwKZAlNOSUzDipkDneeuCBgSnQP1OkboOJqdAF0N/RElIp0Beqh1rtmqnQMneQnlWjadAseIzuimwp0B4BKV5MNOnQByDugNr9qdAuTMJpdkZqEAMKJeqfD2oQMdV3GFUYahAHz/DGGGFqEAWnKkdo6moQNkEYb8azqhAF50vTcjyqEBXwNAWrBepQFCvdWzGPKlAIj7GnhdiqUDUg+H+n4epQI6KXt5fralABAFNj1fTqUDR7DVkh/mpQO9dHLDvH6pACiN+xpBGqkAvf1T7am2qQDngFKN+lKpAb5axEsy7qkAxjZqfU+OqQLAEvp8VC6tAwUyJaRIzq0CigOlTSlurQB1ETLa9g6tAeIGg6Gysq0CgKFdDWNWrQHTvYx+A/qtAFxM+1uQnrEB9GuHBhlGsQOSZzTxme6xAvvcJooOlrEBzMiNN38+sQG6nLZp5+qxARdvF5VIlrUAXQxGNa1CtQOMOv+3De61AZPUIZlynrUDFALRUNdOtQKlcERlP/61AZSX/EqorrkBiOOmiRliuQMAFyiklha5ACGMrCUayrkBmXyejqd+uQMcYaVpQDa9AYJItkjo7r0BqjESuaGmvQBhdERPbl69A3sqLJZLGr0DF50BLjvWvQDT3KfVnErBA6Y+/tCsqsEBvUQqYEkKwQGWy/9IcWrBAlf3hmUpysEB9w0AhnIqwQKxM+Z0Ro7BAmAw3Rau7sEA8FXRMadSwQFaLeelL7bBAURtgUlMGsUDobpC9fx+xQFKjw2HROLFAW8ADdkhSsUDyL6wx5WuxQIY2asynhbFAD2w9fpCfsUDGNXh/n7mxQJxAwAjV07FAS/wOUzHusUBMF7KXtAiyQFX7SxBfI7JAqUrU9jA+skAZXpiFKlmyQMTDO/dLdLJAkr64hpWPskBWxmBvB6uyQN8I3eyhxrJAlusuO2XiskDzjbCWUf6yQK9MFTxnGrNAwEVqaKY2s0D23BZZD1OzQJtB3Uuib7NAnPTafl+Ms0CVT4kwR6mzQKMMvp9ZxrNA+M6rC5fjs0BGrOKz/wC0QNK2UNiTHrRAkohCuVM8tEDazmOXP1q0QPjWv7NXeLRAnRvCT5yWtEAM0zatDbW0QDF+Sw6s07RAXHiPtXfytEAeiPTlcBG1QLNwz+KXMLVAZ4TY7+xPtUDMNyxRcG+1QNG1S0sij7VAlnQdIwOvtUBRy+0dE8+1QOSIb4FS77VAYIu8k8EPtkBnWFabYDC2QHi2Jt8vUbZAFUeApi9ytkC6IR85YJO2QPFvKd/BtLZAEQow4VTWtkACFS+IGfi2QOagjh0QGrdArkgj6zg8t0Cc0i47lF63QJXRYFgigbdAqUfXjeOjt0A5SR8n2Ma3QEahNXAA6rdAlnaHtVwNuEDl8fJD7TC4QN/kx2iyVLhAXHLIcax4uEBKtymt25y4QLp0lGlAwbhA27ol9trluED5lG+iqwq5QHa2eb6yL7lAryjCmvBUuUAa+j2IZXq5QCvuWdgRoLlAWy773PXFuUAs/H/oEey5QDpkwE1mErpAWvIOYPM4ukCcZjlzuV+6QKNridu4hrpAxE3F7fGtukBWszD/ZNW6QAtWjWUS/bpAZr0bd/oku0AX+puKHU27QMNiTvd7dbtAjVH0FBaeu0Dk4tA77Ma7QGC1qcT+77tAvarHCE4ZvED3qfdh2kK8QGRiiyqkbLxAOBBavauWvEDgQcF18cC8QKeepa9167xAda5zxzgWvUDAoiAaO0G9QKAgKwV9bL1A8guc5v6XvUDwUwcdwcO9QKzAjAfE771A38HYBQgcvkDiPiV4jUi+QOFnOr9Udb5AQ4hvPF6ivkAj2qtRqs++QFZbZ2E5/b5AWqOrzgsrv0CmuhT9IVm/QDPz0VB8h79AUMKmLhu2v0CIm+v7/uS/QJNmRw8UCsBA1a6KfsshwEBU9U3/pTnAQHjEa8WjUcBAAlMLBcVpwEBv9aDyCYLAQOiP7sJymsBAFQkEq/+ywEBdvT/gsMvAQPTyTpiG5MBAhE4uCYH9wECQSCppoBbBQHuj3+7kL8FAM+I70U5JwUCvv31H3mLBQPumNYmTfMFA/ytGzm6WwUACheROcLDBQNgEmUOYysFAuZU/5ebkwUD0NAhtXP/BQC5vdxT5GcJAct1mFb00wkDuogWqqE/CQHLr2Ay8asJArGq8ePeFwkAD3OIoW6HCQGqD1ljnvMJAtK55RJzYwkDNNwcoevTCQKUHE0CBEMNA3pmKybEsw0BHgbUBDEnDQPzsNSaQZcNAfy4JdT6Cw0BrQIgsF5/DQOlNaIsavMNAODu70EjZw0B5LvA7ovbDQO4Z1AwnFMRAS0aSg9cxxECW3rTgs0/EQCF8JWW8bcRAx7MtUvGLxED9o3fpUqrEQD2DDm3hyMRA+i9fH53nxEChwDhDhgbFQDcVzRudJcVAGWmx7OFExUAF5t75VGTFQAY4s4f2g8VAvSHx2sajxUA2EsE4xsPFQOa6seb048VAOae4KlMExkBY1DJL4STGQDxK5Y6fRcZAsbX9PI5mxkC1AhOdrYfGQIH4Jff9qMZApNWhk3/KxkDa7Vy7MuzGQApImbcXDsdApT0F0i4wx0ABG7xUeFLHQBXARor0dMdA4kKcvaOXx0AIkiI6hrrHQBQZr0uc3cdA+GSHPuYAyEAJymFfZCTIQOUKZvsWSMhAy/8tYP5ryEC+P8bbGpDIQM/JrrxstMhA56/bUfTYyECZwrXqsf3IQFk9G9elIslAk3RgZ9BHyUDRg1DsMW3JQNT9LbfKkslA1pyzGZu4yUBa9BRmo97JQA8k/+7jBMpAHouZB10rykBpfYYDD1LKQN344zb6eMpAyVxM9h6gykBdIdeWfcfKQM+QGW4W78pAmYEn0ukWy0AmEZQZ+D7LQIZgcptBZ8tAN1FWr8aPy0AGRFWth7jLQBjYBu6E4ctAtKuFyr4KzEAhHnCcNTTMQAkS6b3pXcxA7LGYiduHzECuNK1aC7LMQFOk24x53MxA5aRgfCYHzUAnPQGGEjLNQHSgCwc+Xc1AHvlXXamIzUDyNEnnVLTNQOXRzQNB4M1A86xgEm4MzkA60Qlz3DjOQPBIX4aMZc5Aiu+FrX6SzkByRDJKs7/OQPY/qb4q7c5AbijBbeUaz0BKaeK640jPQGBrCAomd89AzG3Cv6ylz0ARYTRBeNTPQDbhC3rEAdBAwzxen28Z0EAu2wTEPTHQQJJovxsvSdBAxhWa2kNh0EA5Ce40fHnQQBHRYV/YkdBATNXpjliq0EAwy8j4/MLQQMsokNLF29BAhZkgUrP00EBbc6qtxQ3RQGcsrhv9JtFAqtH80llA0UDmfbgK3FnRQMjRVPqDc9FAKWyX2VGN0UBwY5jgRafRQJy/wkdgwdFAofTUR6Hb0UAYXuEZCfbRQPy6TveXENJAwqrYGU4r0kCSKpC7K0bSQKMT3BYxYdJAS5p5Zl580kBrzXzls5fSQCoXUc8xs9JA0L25X9jO0kAHZtLSp+rSQDOVD2WgBtNABTU/U8Ii00DHF4naDT/TQP58bziDW9NAe5fPqiJ400B/E+Jv7JTTQFKeO8bgsdNAAm7N7P/O00BYyuUiSuzTQJaWMKi/CdRAk9u3vGAn1EBOU+SgLUXUQJn0fZUmY9RAG4Cs20uB1EAJDvi0nZ/UQFOcSWMcvtRARJ7rKMjc1EBAjIpIofvUQBB1NQWoGtVAXI9eotw51UBkzNtjP1nVQKFr543QeNVAwI4gZZCY1UAuz4suf7jVQL/Tky+d2NVA+OcJrur41UB8kybwZxnWQNsyijwVOtZAPJE92vJa1kBvgrIQAXzWQKd+xCdAndZAQT65Z7C+1kBMV0EZUuDWQDLbeIUlAtdAyfXn9Sok10BXjYO0YkbXQPnirQvNaNdAwTQ3RmqL10DrX16vOq7XQN2E0ZI+0ddAS6uuPHb010DYZ4T54RfYQKqCUhaCO9hAbp6K4FZf2EAg4RCmYIPYQOycPLWfp9hA7frYXBTM2EATpiXsvvDYQJN317KfFdlAWCQZAbc62UDh6osnBWDZQP1CSHeKhdlAsI3eQUer2UCsxlfZO9HZQNA2NpBo99lAIid2uc0d2kCnlY6oa0TaQFzqcbFCa9pAMK6OKFOS2kAdQtBinbnaQPWXn7Uh4dpAOOzjduAI20BpgAP92TDbQFdX5J4OWdtAivHss36B20C9CwWUKqrbQI1dlpcS09tA0VmNFzf820Af8FltmCXcQMhO8PI2T9xA4KbJAhN53EBs8OT3LKPcQLOwxy2FzdxAwcB+ABz43ECwFZ/M8SLdQBuKRu8GTt1AG6gcxlt53UBbdVOv8KTdQF0/qAnG0N1A8WlkNNz83UDfPV6PMyneQHS5+XrMVd5APGIpWKeC3kBLF2+IxK/eQL3l3G0k3d5AWt0Va8cK30CS507jrTjfQKeeTzrYZt9AyCZz1EaV30B0CKkW+sPfQGULdmby8t9A6In6FBgR4EDi/+vj2SjgQINDtNO+QOBAh41EGMdY4ECK5Nrl8nDgQLiOAnFCieBAvoOU7rWh4EAB4LeTTbrgQN1X4pUJ0+BA/qvYKurr4EBdHq+I7wThQI7nyeUZHuFASK3deGk34UAE+e943lDhQOSvVx15auFAw4q9nTmE4UBGjxwyIJ7hQLOJwhItuOFADodQeGDS4UCEULubuuzhQOfmS7Y7B+JAjf+fAeQh4kBCgaq3szziQGMCtBKrV+JAr0dbTcpy4kBrw5WiEY7iQOMVsE2BqeJA/Y1OihnF4kAyq22U2uDiQK+fYqjE/OJAmNPbAtgY40ATaeHgFDXjQKnA1X97UeNADv91HQxu40D/ktr3xorjQJS8d02sp+NAuRQeXbzE40DcFftl9+HjQGOlmadd/+NAgZ3iYe8c5EB+WB3VrDrkQBU88EGWWORAXEZh6at25EDNmtYM7pTkQJAQF+5cs+RAocFKz/jR5EBGmvvyw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\",\"dtype\":\"float64\",\"shape\":[2000]}},\"selected\":{\"id\":\"1777\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1778\",\"type\":\"UnionRenderers\"}},\"id\":\"1732\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1635\",\"type\":\"ResetTool\"},{\"attributes\":{\"line_color\":\"#c6dbef\",\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1733\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"1636\",\"type\":\"HelpTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1734\",\"type\":\"Line\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1631\",\"type\":\"PanTool\"},{\"id\":\"1632\",\"type\":\"WheelZoomTool\"},{\"id\":\"1633\",\"type\":\"BoxZoomTool\"},{\"id\":\"1634\",\"type\":\"SaveTool\"},{\"id\":\"1635\",\"type\":\"ResetTool\"},{\"id\":\"1636\",\"type\":\"HelpTool\"}]},\"id\":\"1637\",\"type\":\"Toolbar\"},{\"attributes\":{\"data_source\":{\"id\":\"1732\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1733\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1734\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"1736\",\"type\":\"CDSView\"}},\"id\":\"1735\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"source\":{\"id\":\"1732\",\"type\":\"ColumnDataSource\"}},\"id\":\"1736\",\"type\":\"CDSView\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1639\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"1752\",\"type\":\"Selection\"},{\"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y_axis_type='log',\n", " y_range=[1, 1e3], x_range=[1, 1e5])\n", "\n", "# Make the plots\n", "for n, color in zip([1.5, 1.75, 1.95, 2, 2.05, 2.5, 3][::-1], colors):\n", " gamma = gamma_bifurcation(beta, n, 0)\n", " p.line(beta, gamma, line_width=2, color=color, legend=f'n = {n}')\n", " \n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also see how leakage will affect the phase diagram. We will set $n = 2$ and make a plot of the phase boundary for different values of $\\rho$. As you can see in this plot, leaky transcription kills the oscillations roughly when the amount of leaky protein production becomes sufficient to shut off expression of the next repressor. " ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:06.803605Z", "start_time": "2019-05-03T03:15:06.275431Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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\",\"dtype\":\"float64\",\"shape\":[2000]}},\"selected\":{\"id\":\"2069\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"2070\",\"type\":\"UnionRenderers\"}},\"id\":\"2036\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"2070\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"label\":{\"value\":\"\\u03c1 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y_axis_label='γ',\n", " x_axis_type='log', y_axis_type='log',\n", " y_range=[1, 1e4], x_range=[1, 1e5])\n", "\n", "for rho, color in zip([1e-2, 1e-3, 1e-4, 0], colors[::2]):\n", " gamma = gamma_bifurcation(beta, 2, rho)\n", " p.line(beta, gamma, line_width=2, color=color, legend=f'ρ = {rho}')\n", " \n", "p.legend.location = 'top_left'\n", " \n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The repressilator design objectives\n", "\n", "Compared to the protein-only analysis, adding in the mRNAs gave us some additional insights. We see that when the protein and mRNA decay times are comparable, the effective delay around the loop is longer, reducing the minimum Hill coefficient and promoter strength required for oscillations. \n", "\n", "From this analysis we can extract several design objectives or guidelines that will optimize the chances of achieving self-sustaining oscillations. An ideal system should use:\n", "\n", "1. Low \"leakiness:\" $\\rho \\ll 1 \\rightarrow$ *Use tight, artificial promoters that can be fully repressed.*\n", "\n", "2. Strong promoters: $\\beta \\gg 1 \\rightarrow$ *Can be achieved using strong promoters derived from phages that produce high protein levels*\n", "\n", "3. Similar protein & mRNA decay rates $\\gamma\\approx 1 \\rightarrow$ *Destabilize repressors to increase their decay rates to be more comparable to those of mRNA. This can be done by adding destabilizing C-terminal tags based on the [ssrA protein degradation system](https://doi.org/10.1038/75843).\n", "\n", "
\n", "\n", "The protein production shut off was at time zero. This plot shows how adding different variants of the 11-amino acid ssrA tag can alter the decay rate of a fluorescent protein. The gap in data due to technical glitch.\n", "\n", "4. Ultrasensitive repression curves, ideally $n > 1.5$ or $2$, or as large as possible $\\rightarrow $ *Use intrinsically cooperative repression mechanisms, such as those from phage λ, or those that incorporate multiple binding sites, such as those in the TetR system. [Lutz & Bujard](https://academic.oup.com/nar/article/25/6/1203/1197243) showed that the phage λ $P_R$ promoter architecture provides a high regulatory range, and can be adapted to work with binding sites for LacI and TetR*.\n", " \n", "Additional biological design goals:\n", "\n", "5. To minimize toxicity from overexpressing repressors, put the circuit on a low copy plasmid (pSC101)...\n", "\n", "6. ...But to maximize the readout, put a fluorescent reporter gene on a higher copy number plasmid (ColE1).\n", "\n", "7. Destabilize the fluorescent protein so that it can track the circuit activity\n", "\n", "8. Avoid \"read through\" from one operon to the next $\\rightarrow$ add transcriptional terminators between promoter-repressor units.\n", "\n", "Based on these considerations, we designed the repressilator as a two plasmid system to be used in an *E. coli* strain deleted for the natural *lac* operon.\n", "\n", "\n", "\n", "Here, the repressilator consists of three repressors on the low copy pSC101 plasmid, with TetR additionally repressing a green fluorescent protein reporter on the higher copy ColE1 plasmid. The _lite_ suffix on the repressors signifies that they have a destruction tag to decrease their stability. The _aav_ suffix on the GFP indicates that it is a variant of intermediate stability. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Will it work?\n", "\n", "It took a long time to design and then construct the repressilator. In addition to the molecular cloning, there were many steps to characterize the repressors and promoters and make sure signals could propagate through sequential repressor cascades. \n", "\n", "After all of this, there was more than a little uncertainty as to whether the system would, indeed, exhibit self-sustaining oscillations.\n", "\n", "We did not expect that cells would be synchronized within a population. Therefore, we used time-lapse imaging to record movies of individual cells growing into microcolonies. (Lacking automated autofocus systems, one author slept near the microscope with an alarm clock to refocus the microscope every hour, all night long, exemplifying another important role for clocks in science and technology.) \n", "\n", "In these movies, the changing fluorescence intensity in each cell provided a glimpse into the state of the oscillator over time:\n", "\n", "
\n", "\n", "
\n", "\n", "This movie shows both clear oscillations in individual cells, as well as variability among cells in the amplitude, phase, and duration of each pulse. Analyzing these movies was done by manually tracking each cell backwards in time. This would now be done in a more automated fashion.\n", "\n", "
Depressilator?
\n", "\n", "
\n", "
\n", "\n", "This procedure revealed clear oscillations in most cells, such as this:\n", "\n", "
\n", "\n", "Analysis of many cells showed a typical repressilator period of 160 ± 40 min (SD, *n* = 63), with a cell division time of ≈50-60 min at 30°C. Sibling cells desynchronized with one another over about two cell cycles (95 ± 10 min). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Can the repressilator be improved?\n", "\n", "In Potvin-Trottier et al, [Synchronous long-term oscillations in a synthetic gene circuit,” Nature 2016](https://doi.org/10.1038/nature19841), Johan Paulsson and colleagues asked what accounted for the repressilator's variability and whether it could be further improved. The following is based on [Gao & Elowitz, Precision Timing in a Cell, *Nature* 2016](https://doi.org/10.1038/nature19478): \n", "\n", "* The first thing they changed is the observation method. Instead of growth on agarose pads, where waste products can build up and influence cell growth and behavior, they switched to a microfluidic device developed by [Suckjoon Joon](https://jun.ucsd.edu/) termed \"[the mother machine](https://doi.org/10.1016/j.cub.2010.04.045),\" which allows continuous observation of single cells over hundreds of generations by trapping it at the end of a channel (for more info, see [Suckjoon's website](https://jun.ucsd.edu/mother_machine.php)). This revealed that, despite its variability, the original repressilator exhibited self-sustaining oscillations that never terminate.\n", "\n", "* Now able to analyze the dynamics in more constant conditions, they found that much of this variation could be attributed to the reporter plasmid itself. Integrating the reporter into the repressilator plasmid reduced this variability.\n", "\n", "
\n", "\n", "
\n", "\n", "
\n", "\n", "
\n", "\n", "* The problem with TetR: A nice property of TetR is that it binds extremely tightly to its operator site. But this tightness of binding creates a problem as well. It means that the timing of de-repression by TetR depends sensitively on when the final molecules of TetR are degraded or diluted from the cell, as shown in the following figure from Potvin-Trottier et al. This leads to variability in the overall period. However, this effect can be mitigated by inclusion of a \"DNA sponge\"--a plasmid containing extra TetR binding sites. (In fact, in the original repressilator design the reporter plasmid fortuitously played this role.)\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* Finally, an additional source of variability stemmed from fluctuations in the protein degradation machinery. This could be circumvented by reducing the amounts of repressor made, or eliminating their degradation altogether. Of course, without protein degradation, oscillation periods stretch out to as much as 14 cell cycles, but with such a high precision that it would take 180 cell cycles to accumulate a half-period of phase drift! A remarkably precise clock. \n", "\n", "Here, with three colors to allow simultaneous observation of all three repressors, is one of the final repressilator designs as a movie and a typical trace:\n", "\n", "
\n", "\n", "
\n", "\n", "
\n", "\n", "In fact, this is so accurate that you can see it in a test tube:\n", "\n", "
\n", "\n", "
\n", "\n", "Or you can see it in the \"tree rings\" of a bacterial colony:\n", "\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusions\n", "\n", "* Limit cycle dynamics are ideal for self-sustaining oscillations in living cells.\n", "* The repressilator uses a cycle of three repressors to create a delayed negative feedback loop.\n", "* Linear stability analysis allows us to determine the stability of a fixed point.\n", "* The simplified protein-only repressilator model has a single fixed point, and generates limit cycle oscillations when this point becomes unstable.\n", "* High Hill coefficients and strong promoters favor oscillations.\n", "* The model can be extended from 3 to 6 variables to include mRNA as well as proteins. \n", "* The extended model further shows that destabilizing proteins to make the decay rates of mRNA and protein more similar should also favor oscillations and reduce the minimum Hill coefficient required for oscillations.\n", "* A repressilator designed to meet these conditions shows self-sustaining oscillations in individual *E. coli* cells.\n", "* Recently, several features of this circuit were improved to create an oscillator of astonishing precision." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Computing environment" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2019-05-03T03:15:06.826993Z", "start_time": "2019-05-03T03:15:06.811337Z" }, "tags": [ "remove_input" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPython 3.7.3\n", "IPython 7.4.0\n", "\n", "numpy 1.16.2\n", "scipy 1.2.1\n", "bokeh 1.0.4\n", "jupyterlab 0.35.4\n", "biocircuits 0.0.8\n" ] } ], "source": [ "%load_ext watermark\n", "%watermark -v -p numpy,scipy,bokeh,jupyterlab,biocircuits" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }