{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 18. Molecular titration generates ultrasensitive responses in biological circuits\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", "\n", "- Molecular titration creates ultrasensitive switches and promotes unidirectional communication\n", "\n", "#### Techniques\n", "\n", "- \n", "\n", "#### Papers\n", "- N.E. Buchler and M. Louis, Molecular Titration and Ultrasensitivity in Regulatory Networks, J.M.B. (2008).\n", "- N.E. Bucher and F.R. Cross, Protein sequestration generates a flexible ultrasensitive response in a genetic network, Mol. Syst. Biol. (2009).\n", "- S. Mukherji et al, “MicroRNAs can generate thresholds in target gene expression”, Nat. Gen. 2011\n", "- Levine et al, PLoS Biol, 2007; Mukherji et al, 2011: Regulation of mRNA level by small RNAs\n", "- D. Sprinzak et al, Nature 2010; D. Sprinzak et al, PLoS Comput. Biol. 2011\n", "- E. Rotem et al, Regulation of phenotypic variability by a threshold- based mechanism underlies bacterial persistence, PNAS 2010.\n", "- See also: F. Corson et al, “Self-organized Notch dynamics generate stereotyped sensory organ patterns in Drosophila,” Science 2017\n", "\n", "\n", "
\n", "\n", "
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\n", "
\n", "\n", "Let's pause to ask: \n", "\n", "1. How could you insert ultrasensitivity into the dependence of Y on A?\n", "2. How could you make the threshold and sensitivity of the overall input function tunable?\n", "\n", "

\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## \"Subtraction\" by titration\n", "\n", "Today we will discuss **molecular titration**, a simple and general mechanism that provides tunable ultrasensitivity across diverse natural systems, and allows engineering of ultrasensitive responses in synthetic circuits.\n", "\n", "One of the most striking features of biological molecules is their tendency to form strong and specific complexes with one another. Depending on the system, the complex itself may provide a particular activity, such as gene regulation. Or, alternatively, one of the monomers may provide an activity, with the complex inhibiting it.\n", "\n", "
\n", "\n", "In this example, molecular titration performs a kind of \"subtraction\" operation, in which an inhibitor (inactive species) \"subtracts off\" a fraction of otherwise active molecules.\n", "\n", "Molecular titration occurs in diverse contexts:\n", "\n", "* In bacterial gene regulation, specialized transcription factors called sigma factors are stoichiometrically inhibited by cognate anti-sigma factors. \n", "\n", "* Transcription factors, such as basic helix-loop-helix proteins, form specific homo- and hetero-dimeric complexes with one another, each with a distinct binding specificity or activity.\n", "\n", "* Small RNA regulators can bind to cognate target mRNAs, inhibiting their translation. \n", "\n", "* In toxin-antitoxin systems, the \"anti-toxin\" protein can bind to its cognate toxin, blocking its activity.\n", "\n", "* Intercellular communication systems often work through direct complexes between ligands and receptors or ligands and inhibitors. \n", "\n", "Today we will discuss the way in which these systems use molecular titration, through complex formation, to generate ultrasensitivity. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Molecular titration: a minimal model\n", "\n", "To see how molecular titration produces ultrasensitivity we will consider the simplest possible example of two proteins, $A$ and $B$, that can bind to form a complex, $C$, that is inactive for both $A$ and $B$ activities. This system can be described by the following reactions:\n", "\n", "$ A + B \\underset{k_{\\it{off}}}{\\stackrel{k_\\it{on}}{\\rightleftharpoons}} C $\n", "\n", "At steady-state we have:\n", "\n", "$ k_\\it{on} A B = k_\\it{off} C $\n", "\n", "with \n", "\n", "$K_d = k_\\it{off}/k_\\it{on} = A B / C$\n", "\n", "We also will insist on conservation of mass:\n", "\n", "\\begin{align}\n", "A_T = A + C \\\\ \n", "B_T = B + C\n", "\\end{align}\n", "\n", "Here, $A_T$ and $B_T$ denote the total amounts of $A$ and $B$, respectively.\n", "\n", "From these equations, one can determine an expression for the amount of free $A$ (or $B$) as a function of $A_T$ and $B_T$ for different parameter values:\n", "\n", "\\begin{align}\n", "A = \\frac{1}{2} \\left( A_T-B_T-K_d+\\sqrt{(A_T-B_T-K_d)^2+4A_T K_d} \\right)\n", "\\end{align}\n", "\n", "What does this relationship look like? More specifically, let's consider a case in which we control the total amount of $A_T$ and see how much free $A$ we get, for different amounts of $B_T$. We will start by assuming the limit of very strong binding (small values of $K_d$):\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2019-05-13T17:41:37.087762Z", "start_time": "2019-05-13T17:41:36.896600Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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\",\"dtype\":\"float64\",\"shape\":[1001]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1001]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1001]},\"y\":{\"__ndarray__\":\"AAAAAJHYej4AAACAP0h7PgAAAIC+uXs+AAAA4BUtfD4AAAAgTaJ8PgAAACBsGX0+AAAAoHqSfT4AAADAgA1+PgAAAMCGin4+AAAAAJUJfz4AAADgs4p/PgAAAPD1BoA+AAAA8KJJgD4AAABgZY2APgAAAMBB0oA+AAAAoDwYgT4AAACwWl+BPgAAAKCgp4E+AAAAQBPxgT4AAACAtzuCPgAAAFCSh4I+AAAAwKjUgj4AAADw/yKDPgAAACCdcoM+AAAAgIXDgz4AAACQvhWEPgAAANBNaYQ+AAAAoDi+hD4AAADQhBSFPgAAACA4bIU+AAAAYFjFhT4AAABw6x+GPgAAAGD3e4Y+AAAAYILZhj4AAACgkjiHPgAAAGAumYc+AAAAIFz7hz4AAACAIl+IPgAAAPCHxIg+AAAAYJMriT4AAACgS5SJPgAAAKC3/ok+AAAAgN5qij4AAABgx9iKPgAAAKB5SIs+AAAAsPy5iz4AAAAwWC2MPgAAALCToow+AAAAALcZjT4AAAAwypKNPgAAADDVDY4+AAAAQOCKjj4AAACg8wmPPgAAAPAXi48+AAAA0CoHkD4AAADA2kmQPgAAAECgjZA+AAAAyH/SkD4AAADwfRiRPgAAAGCfX5E+AAAA4OinkT4AAAA4X/GRPgAAAEgHPJI+AAAAGOaHkj4AAACoANWSPgAAAChcI5M+AAAAuP1ykz4AAADI6sOTPgAAAKAoFpQ+AAAA0LxplD4AAADYrL6UPgAAAHD+FJU+AAAASLdslT4AAABA3cWVPgAAAEh2IJY+AAAAeIh8lj4AAADgGdqWPgAAAMAwOZc+AAAAcNOZlz4AAABwCPyXPgAAADDWX5g+AAAAYEPFmD4AAADQViyZPgAAAFAXlZk+AAAA6Iv/mT4AAACou2uaPgAAAMit2Zo+AAAAmGlJmz4AAACY9rqbPgAAAFBcLpw+AAAAcKKjnD4AAADQ0BqdPgAAAGDvk50+AAAAMAYPnj4AAACAHYyePgAAAJg9C58+AAAAAG+Mnz4AAAAo3QegPgAAACSUSqA+AAAA7GCOoD4AAAD8R9OgPgAAAPhNGaE+AAAAhHdgoT4AAABkyaihPgAAAGhI8qE+AAAAePk8oj4AAACU4YiiPgAAAMgF1qI+AAAANGskoz4AAAAkF3SjPgAAANgOxaM+AAAAxFcXpD4AAABc92qkPgAAAEDzv6Q+AAAAFFEWpT4AAACYFm6lPgAAALRJx6U+AAAAVPAhpj4AAACIEH6mPgAAAHiw26Y+AAAAZNY6pz4AAACoiJunPgAAALjN/ac+AAAAIKxhqD4AAACMKseoPgAAANBPLqk+AAAAxCKXqT4AAABoqgGqPgAAAODtbao+AAAAbPTbqj4AAABcxUurPgAAACxovas+AAAAdOQwrD4AAAD0QaasPgAAAHyIHa0+AAAABMCWrT4AAACw8BGuPgAAALQij64+AAAAdF4Orz4AAABsrI+vPgAAAKaKCbA+AAAA7FBMsD4AAAB+LZCwPgAAAOgk1bA+AAAAxjsbsT4AAADOdmKxPgAAALzaqrE+AAAAbmz0sT4AAADQMD+yPgAAAOAsi7I+AAAAuGXYsj4AAACA4CazPgAAAH6idrM+AAAABLHHsz4AAACGERq0PgAAAILJbbQ+AAAAmN7CtD4AAAB4Vhm1PgAAAPA2cbU+AAAA5oXKtT4AAABQSSW2PgAAAEqHgbY+AAAA/EXftj4AAAC2iz63PgAAANZen7c+AAAA3sUBuD4AAABox2W4PgAAAChqy7g+AAAA7LQyuT4AAACqrpu5PgAAAGheBro+AAAAUstyuj4AAACu/OC6PgAAAOT5ULs+AAAAdsrCuz4AAAAMdja8PgAAAGgErLw+AAAAcn0jvT4AAAA06Zy9PgAAANBPGL4+AAAAmrmVvj4AAAD6LhW/PgAAAIK4lr8+AAAAdy8NwD4AAACKFVDAPgAAAPwSlMA+AAAAXizZwD4AAABZZh/BPgAAAKbFZsE+AAAAE0+vwT4AAACDB/nBPgAAAO7zQ8I+AAAAXhmQwj4AAAD2fN3CPgAAAO4jLMM+AAAAkxN8wz4AAABIUc3DPgAAAIniH8Q+AAAA5sxzxD4AAAALFsnEPgAAALfDH8U+AAAAxtt3xT4AAAAqZNHFPgAAAPBiLMY+AAAAO96Ixj4AAABO3ObGPgAAAIJjRsc+AAAATHqnxz4AAAA/JwrIPgAAAAVxbsg+AAAAaF7UyD4AAABP9jvJPgAAAL0/pck+AAAA1EEQyj4AAADTA33KPgAAABmN68o+AAAAI+Vbyz4AAACQE87LPgAAAB4gQsw+AAAArhK4zD4AAABA8y/NPgAAAPfJqc0+AAAAG58lzj4AAAAUe6POPgAAAHFmI88+AAAA42mlzz4AAIAhxxTQPgAAAEbuV9A+AACA8i6c0D4AAIDLjeHQPgAAAIsPKNE+AACA/rhv0T4AAIAIj7jRPgAAAKGWAtI+AAAA1NRN0j4AAIDETprSPgAAAKsJ6NI+AACA1go30z4AAACtV4fTPgAAAKz12NM+AAAAaOor1D4AAICOO4DUPgAAAOXu1dQ+AAAASgot1T4AAIC1k4XVPgAAADmR39U+AAAAAAk71j4AAABSAZjWPgAAgJCA9tY+AAAAOo1W1z4AAIDnLbjXPgAAAE9pG9g+AACARUaA2D4AAAC8y+bYPgAAAMEAT9k+AACAg+y42T4AAABSliTaPgAAgJkFkto+AAAA50EB2z4AAIDqUnLbPgAAgHRA5ds+AAAAdxJa3D4AAIAI0dDcPgAAgGGESd0+AACA3zTE3T4AAIAD60DePgAAAHavv94+AACAAotA3z4AAACehsPfPgAAALJVJOA+AAAATAFo4D4AAMDSyqzgPgAAQBK38uA+AADA6co54T4AAIBPC4LhPgAAwE99y+E+AAAADCYW4j4AAEC9CmLiPgAAQLQwr+I+AABAWJ394j4AAEApVk3jPgAAAMBgnuM+AABAzcLw4z4AAIAcgkTkPgAAAJKkmeQ+AADALDDw5D4AAEAHK0jlPgAAQFaboeU+AACAa4f85T4AAEC09VjmPgAAALvstuY+AACAKHMW5z4AAEDCj3fnPgAAgG1J2uc+AAAALqc+6D4AAAAosKToPgAAwJ5rDOk+AABA+OB16T4AAAC7F+HpPgAAgJAXTuo+AADAROi86j4AAADHkS3rPgAAwCscoOs+AAAArI8U7D4AAMCm9IrsPgAAAKFTA+0+AACAR7V97T4AAABvIvrtPgAAQBSkeO4+AABAXkP57j4AAICeCXzvPgAAoCiAAPA+AADAjxhE8D4AAEDv0ojwPgAAwEi0zvA+AACgtcEV8T4AAKBmAF7xPgAAIKV1p/E+AAAg0yby8T4AAEBsGT7yPgAA4AVTi/I+AABgT9nZ8j4AAIATsinzPgAAYDjjevM+AADgv3LN8z4AAMDIZiH0PgAAoI7FdvQ+AACAa5XN9D4AAEDX3CX1PgAAwGiif/U+AAAg1+za9T4AACD5wjf2PgAAIMcrlvY+AAAgWy729j4AACDx0Vf3PgAAIOkdu/c+AABAxhkg+D4AAMAwzYb4PgAAYPY/7/g+AAAAC3pZ+T4AAMCJg8X5PgAAwLVkM/o+AADg+iWj+j4AAMDuzxT7PgAA4FFriPs+AAAAEAH++z4AAKBBmnX8PgAAAC1A7/w+AACgRvxq/T4AAOAy2Oj9PgAAgMbdaP4+AACACBfr/j4AAEAyjm//PgAAwLFN9v8+AADgFLA/AD8AAAA6aIUAPwAA0NBUzAA/AABQfnsUAT8AAAAF4l0BPwAA8ESOqAE/AADwPIb0AT8AAPAK0EECPwAAAO1xkAI/AADwQXLgAj8AADCK1zEDPwAAYGiohAM/AACQouvYAz8AAMAiqC4EPwAAwPfkhQQ/AABwVqneBD8AACCa/DgFPwAAMEbmlAU/AABwBm7yBT8AAJCwm1EGPwAA0ER3sgY/AABw7wgVBz8AAIAJWXkHPwAAMBpw3wc/AAAQ2FZHCD8AAMApFrEIPwAAECi3HAk/AACAHkOKCT8AAACNw/kJPwAAMClCawo/AADQ38jeCj8AAADWYVQLPwAAUGsXzAs/AACgOvRFDD8AADAcA8IMPwAAACdPQA0/AADgsuPADT8AAMBZzEMOPwAA8PkUyQ4/AACwt8lQDz8AAED/9toPPwAAkMPUMxA/AADQKHd7ED8AAMhXacQQPwAACCGyDhE/AACQflhaET8AAACVY6cRPwAAwLTa9RE/AABQW8VFEj8AAKg0K5cSPwAAgBwU6hI/AAC4H4g+Ez8AAAB+j5QTPwAAGKsy7BM/AACgUHpFFD8AAKBPb6AUPwAAIMIa/RQ/AAAg/YVbFT8AAGCSursVPwAACFLCHRY/AADwTKeBFj8AAIjWc+cWPwAA4IYyTxc/AAAAPe64Fz8AACAhsiQYPwAAGKeJkhg/AAC4kIACGT8AAHDwonQZPwAACCz96Bk/AABA/5tfGj8AAOh+jNgaPwAAqBvcUxs/AABYpZjRGz8AACBO0FEcPwAA8K2R1Bw/AAAAxutZHT8AAIgE7uEdPwAAiEiobB4/AAD45Sr6Hj8AALCphoofPwAADG/mDiA/AADApwdaID8AAHgosKYgPwAAlGDp9CA/AADoB71EIT8AAHghNZYhPwAARP5b6SE/AABMQDw+Ij8AAKTd4JQiPwAAuCNV7SI/AADAuqRHIz8AADip26MjPwAArFcGAiQ/AACslDFiJD8AANyYasQkPwAAQAu/KCU/AADIBT2PJT8AABwa8/clPwAAfFbwYiY/AAAYS0TQJj8AAIQP/z8nPwAAhEgxsic/AAAsLuwmKD8AADiSQZ4oPwAA3OZDGCk/AADgRQaVKT8AAAh4nBQqPwAAIP0alyo/AAAkFJccKz8AADTEJqUrPwAAyOXgMCw/AAB0LN2/LD8AAGgxNFItPwAARH7/5y0/AADAmFmBLj8AAPQOXh4vPwAATIQpvy8/AACw3+wxMD8AAETcRoYwPwAArtSy3DA/AACSjkE1MT8AACqBBJAxPwAAlt4N7TE/AAC2nXBMMj8AAKyEQK4yPwAAFjSSEjM/AAD2Mnt5Mz8AAGr7EeMzPwAARAhuTzQ/AACI46e+ND8AAOI12TA1PwAAQtccpjU/AACO4I4eNj8AAKq+TJo2PwAAwEZ1GTc/AAAwzCicNz8AAOg3iSI4PwAAqiG6rDg/AAAc6+A6OT8AAPDcJM05PwAAYEavYzo/AAACn6v+Oj8AAHSrR547PwAA1KSzQjw/AACWYyLsPD8AANKNyZo9PwAAcMnhTj4/AAC68qYIPz8AAHRXWMg/PwAArHscR0A/AAAR5UetQD8AAAYG1BZBPwAAocjog0E/AACOkLD0QT8AAP1sWGlCPwCAX08Q4kI/AIB2RwtfQz8AgGHFf+BDPwCAT+KnZkQ/AACtsMHxRD8AALCUD4JFPwAATabYF0Y/AIDJHWmzRj8AAEHMElVHPwCAuaEt/Uc/AACJQhisSD8AAC6uOGJJPwAA/fn8H0o/AIB4ItzlSj8AgJr2VrRLPwAA3CD5i0w/AAB+UlptTT8AgFiWH1lOPwCAbNH8T08/AABGPFspUD8AwPjBEbFQPwAAkdWXP1E/AEDb+m7VUT8AwAXYJXNSPwCACetZGVM/AEAuhbnIUz8AwCIaBoJUPwCAKPMWRlU/AICtWtwVVj8AQItZY/JWPwCAUyXa3Fc/AEAfZ5XWWD8AQKOMFuFZPwDA3mIT/lo/AMCES38vXD8AgOl1lnddPwAA7aPr2F4/AOAmlzwrYD8AIEEb2/lgPwAQv6JY2mE/ABBRBBnPYj8AUN0/8tpjPwCg3WtIAWU/ACA4QTJGZj8AwAmLqa5nPwBQ4j/MQGk/AGAhXDUEaz8A0HlBeAJtPwAwqlXPR28/ABDHRgzycD8AoNjaJXZyPwDIvXJaPnQ/AFR2Pztedj8AKGCiovF4PwD82jubIXw/ANY6fZwWgD8AVFMlVb2CPwAowwGEXYY/AF0VAR6fiz8AzePx7vWRP0DLfFW6epk/YP1conSSpT9kg04d81G/P9/6IHYAXvA/mY8kICXUBEAViEoTXQURQHiBR63PxBdAcqNEr2ejHkDE85swAtAiQBR/BiY+XSZACmj8Kn75KUBSCYBj66QtQPz3hDjcrzBA4H3Dug6VMkBQZjoUK4I0QJSw6GtQdzZAyfDG7Z50OEASPFOiN3o6QMqRkVY8iDxA2viTjc+ePkB+v+E7Cl9AQGSm4XYXc0FAkvvTtqGLQkBS6d2Mu6hDQOp+Kdx3ykRAyBsv2unwRUCCj0MPJRxHQHr0WFc9TEhAYu3l4kaBSUCBruo3VrtKQMfBDTOA+ktA3ifMCNo+TUA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\",\"dtype\":\"float64\",\"shape\":[1001]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1001]}},\"selected\":{\"id\":\"5778\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"5777\",\"type\":\"UnionRenderers\"}},\"id\":\"5746\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"5743\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"5798\",\"type\":\"Selection\"},{\"attributes\":{\"ticker\":null},\"id\":\"5727\",\"type\":\"LogTickFormatter\"},{\"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\":\"5712\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"label\":{\"value\":\"100.0\"},\"renderers\":[{\"id\":\"5783\",\"type\":\"GlyphRenderer\"}]},\"id\":\"5799\",\"type\":\"LegendItem\"},{\"attributes\":{\"line_color\":\"#9ecae1\",\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"5763\",\"type\":\"Line\"},{\"attributes\":{\"items\":[{\"id\":\"5731\",\"type\":\"LegendItem\"},{\"id\":\"5745\",\"type\":\"LegendItem\"},{\"id\":\"5761\",\"type\":\"LegendItem\"},{\"id\":\"5779\",\"type\":\"LegendItem\"},{\"id\":\"5799\",\"type\":\"LegendItem\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"BTvals = np.logspace(-1, 3, 5)\n", "\n", "# Decide on your color palette\n", "colors = bokeh.palettes.Blues9[3:8][::-1]\n", "\n", "p = bokeh.plotting.figure(width=450, height=300,\n", " x_axis_label='A_T', y_axis_label='A', \n", " x_axis_type=\"log\", y_axis_type=\"log\",\n", " title = \"A vs. A_T for different values of B_T, in strong binding regime, Kd<<1\",\n", " x_range=[AT.min(), AT.max()])\n", "\n", "# Loop through colors and BT values (nditer not necessary)\n", "A = np.zeros((BTvals.size, AT.size))\n", "p.circle(0, 0, size=0.00000001, color= \"#ffffff\", legend=\"B_T\")\n", "for i, (color, BT) in enumerate(zip(colors, BTvals)):\n", " A0 = 0.5 * (AT-BT-Kd+np.sqrt((AT-BT-Kd)**2+4*AT*Kd))\n", " A[i,:] = A0\n", " p.line(AT, A0, line_width=2, color=color, legend=str(BT))\n", " \n", "p.legend.location = \"bottom_right\"\n", "\n", "bokeh.io.show(p)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The key feature to notice here is that A goes through a very sharp transition from a low to a high value just as $A_T$ reaches $B_T$. \n", "\n", "Perhaps it is simpler to view this behavior on a linear axis:\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2019-05-13T17:30:55.825567Z", "start_time": "2019-05-13T17:30:55.746380Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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vs. A_T\"},\"id\":\"3662\",\"type\":\"Title\"},{\"attributes\":{\"callback\":null,\"end\":200.0},\"id\":\"3665\",\"type\":\"Range1d\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"3713\",\"type\":\"Line\"}],\"root_ids\":[\"3663\"]},\"title\":\"Bokeh Application\",\"version\":\"1.0.4\"}};\n", " var render_items = [{\"docid\":\"e0211d75-332a-4bdf-80b7-b4c3171f6ae4\",\"roots\":{\"3663\":\"9524bf1f-a5b6-4918-a9bd-b4f7f40d589c\"}}];\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": "3663" } }, "output_type": "display_data" } ], "source": [ "# array of A_total values\n", "AT = np.linspace(0, 200, 1001)\n", "Kd = 0.001 \n", "BTvals = 100*np.ones(1)\n", "\n", "colors = bokeh.palettes.Blues3[::]\n", "\n", "p = bokeh.plotting.figure(width=400, height=300,\n", " x_axis_label='A_T', y_axis_label='A', \n", " x_axis_type=\"linear\", y_axis_type=\"linear\",\n", " title = \"A vs. A_T\",\n", " x_range=[AT.min(), AT.max()])\n", "\n", "# Loop through colors and BT values (nditer not necessary)\n", "A = np.zeros((BTvals.size, AT.size))\n", "p.circle(0, 0, size=0.00000001, color= \"#ffffff\", legend=\"B_T\")\n", "for i, (color, BT) in enumerate(zip(colors, BTvals)):\n", " A0 = 0.5 * (AT-BT-Kd+np.sqrt((AT-BT-Kd)**2+4*AT*Kd))\n", " A[i,:] = A0\n", " p.line(AT, A0, line_width=2, color=color, legend=str(BT))\n", " \n", "p.legend.location = \"top_left\"\n", "\n", "bokeh.io.show(p)\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we see that $A$ is essentially 0 when $A_T < B_T$, and then increases linearly beyond that threshold, becoming approximately proportional to the difference $A_T-B_T$. This is called a **threshold-linear** relationship. \n", "\n", "So far, we have looked in the \"strong\" binding limit, $K_d<<1$. But any real system will have a finite rate of unbinding. It is therefore important to see how the system behaves across a range of $K_d$ values." ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2019-05-13T17:42:54.334265Z", "start_time": "2019-05-13T17:42:54.182109Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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IP2B7gCNcgog/oBDlbtbSiD/ABLlmciSJP2CXyME0d4k/QKikTiLLiT+g2DT0PyCKP8DXTbKSdoo/wPxLoh/Oij9gVLL36yaLP6BGzgD9gIs/wPtfJ1jciz9gqEfxAjmMP8DsNwEDl4w/AG9tF172jD+A4msSGleNPwCmwO88uY0/4CzLzMwcjj/AZIvnz4GOPyBLdp9M6I4/IOpQdklQjz+g9RERzbmPP4AgZRxvEpA/kCbK7cFIkD/QlcWG4n+QPyB95ITUt5A/IJ22mZvwkD8wpVWLOyqRP+Cm8DS4ZJE/wOVbhxWgkT8wK6WJV9yRP0DIrFmCGZI/0G/DLJpXkj8AFk1Qo5aSPyADaSqi1pI/4EqfOpsXkz+Q2ZMak1mTP+BLv36OnJM/UMctN5Lgkz+ADEQwoyWUPwD9inPGa5Q/QNOBKAGzlD/AS3eVWPuUPzABaiDSRJU/sEHwT3OPlT/QpCfMQduVP3CsrF9DKJY/ML+a+H12lj9QzZSp98WWP8D01qq2Fpc/QHxRW8Folz8Agc1BHryXPzC3Gw7UEJg/0J9NmulmmD+gnPnrZb6YP1BNijVQF5k/gKeZ169xmT/wPVhijM2ZP+AxAZftKpo/4E1baduJmj8Az0cBXuqaP6BmX7x9TJs/EAaeL0Owmz8ACR4ptxWcP4Bd47HifJw/0Eu3D8/lnD/wiBXHhVCdPxBGK50QvZ0/wPXomXkrnj8wiCcKy5ueP7Do4YEPDp8/oI2D3lGCnz+g9UxJnfifPwB855x+OKA/6Ok+vL51oD8AfK4QFbSgP6BCYtOH86A/IMwgah00oT84Oslo3HWhPxDa35LLuKE/CNcp3fH8oT+Ap1hvVkKiPzDYxaUAiaI/COM/E/jQoj/4w+iCRBqjP6gGJ/rtZKM/4A6quvywoz+oZYJEef6jP/DcTlhsTaQ/IGR/+d6dpD/gb65w2u+kP3DhEU5oQ6U/SGEEbJKYpT+AK6jxYu+lP5hUpFXkR6Y/KJj9YCGipj/YywsyJf6mPyAbjT/7W6c/EDvYW6+7pz9ozi64TR2oP7g9MejigKg/kFB15XvmqD9o30ATJk6pP9D/aULvt6k/mBZeteUjqj+gRFEkGJKqP8Ctl8GVAqs/gB8qPm51qz8YqVfOseqrPyi6pS5xYqw/MGfgqL3crD/gdlwZqVmtP/jgbPRF2a0/8GgNTKdbrj8oA8TV4OCuPwivuvAGaa8/0HETrC70rz8IC7zmNkGwP9ym82vtibA/KGRgiUbUsD/Y4IhITiCxP9C8kRwRbrE/OHcm5pu9sT/oi4T3+w6yP4heqRg/YrI/NG2ji3O3sj/YKwcRqA6zPyjPh+zrZ7M/9Cy06U7Dsz84tNdg4SC0P3RU/zu0gLQ/rP0h/NjitD/kK2y+YUe1PwS2rUFhrrU/nNPo6+oXtj+AAwHQEoS2P1QoiLPt8rY/CNanFJFktz/4YyQwE9m3P8zpdgeLULg/VNL6ZhDLuD/wKyvsu0i5P8hN6wunybk/kM7VGOxNuj/QIYxJptW6Pxh/AL/xYLs/9Payiuvvuz800dm0sYK8PxB7bEJjGb0/DG0HOyC0vT/Yip6uCVO+P3yP8rpB9r4/GCa9kOudvz/eK0O8FSXAP9iAimuTfcA/Vom1GILYwD8Osh6Y9TXBP0YRa1EClsE/JvanQL34wT82igv3O17CP4LwTpuUxsI/oBKY6d0xwz8mKekyL6DDP5QCDFygEcQ/2iHv20mGxD+MBGu5RP7EP2ZBZoiqecU/zLhPZpX4xT9YzOb1H3vGP559SlplAcc/2HdJMYGLxz+eYO6MjxnIPwRfReysq8g/kJNZM/ZByT9qPGuiiNzJP3Z4YcyBe8o/Yv98jP8eyz/Os1P7H8fLP6SfH2MBdMw/3K9uM8IlzT/0TUP0gNzNPwK/uDhcmM4/guBAkXJZzz8atsk+8Q/QP16hNC/lddA//SiQM6Te0D9nMrNHPUrRP3hAhUK/uNE/oqoKzzgq0j+tzaRluJ7SP+CSlkVMFtM/wkzdbgKR0z/DRW2c6A7UPzpw4D4MkNQ/Q3mkd3oU1T8jELQUQJzVP1GQ5YxpJ9Y/u2bX/AK21j8lkoAkGEjXP5ONaWW03dc/qNGPweJ22D+O+/ParRPZP6qP0PMftNk/KFB170JY2j+rPcFTIADbP2akM0vBq9s/ThKLpy5b3D8ix+fkcA7dP6QbZi2Qxd0/mIskXZSA3j8/d6gGhT/fP04tyrs0AeA/qAzRXqRk4D+qDOrVFMrgP1AY6G+JMeE/b/GrYwWb4T+eA+nSiwbiP8JW7cwfdOI/aXZnUcTj4j84mCVTfFXjP8LDybpKyeM/7TxvaTI/5D8w7j07NrfkP0oN6QlZMeU/tKsWr52t5T96WK4GByzmPw9lDfGXrOY/KcMfVVMv5z+0z1wiPLTnPyOxp1JVO+g/ZjwT7KHE6D/MlIkCJVDpPzj2V7nh3ek/4EifRNtt6j+8SKrqFADrP9IrKgWSlOs/KM9aAlYr7D8khQ9mZMTsP3ixqcrAX+0/jGf64W797T+aRxB2cp3uP9zW8mnPP+8/ko9Muonk7z8KcAK/0kXwP42lZXOTmvA/a2jKIInw8D9NYIb7tUfxP9UC/UUcoPE/9vvMUL758T/E1Ph6nlTyPyBQCzK/sPI/Fe038iIO8z86+HdGzGzzP2iPpMi9zPM/gPONIfot9D+ofhAJhJD0P5+OJ0Ze9PQ/u63+rotZ9T8UPgEpD8D1P67m6KjrJ/Y/5PvKMiSR9j/0GCXau/v2P5Aa6cG1Z/c/J6eIHBXV9z8+bQAs3UP4P9o840ERtPg/nBxlv7Ql+T9SeWYVy5j5P36Kf8RXDfo/GAUMXV6D+j9zMTd/4vr6P8Z4CNvnc/s/AntwMHLu+z+ovVZPhWr8PzgAqBcl6Pw/MENleVVn/T9JjLN0Guj9P9xw7Bl4av4/om+viXLu/j/fH/T0DXT/P9M8HZ1O+/8/MEkGahxCAED45xt+aIcAQEoiX8SNzQBAJMS/fo4UAUAnipn3bFwBQM1mwIErpQFACkGNeMzuAUBILes/UjkCQAYhZUS/hAJAzSE0+xXRAkAr703iWB4DQEYodICKbANAnuxDZa27A0B++EUpxAsEQFc8/23RXARAR+8B3teuBEBNHP8s2gEFQFaq2BfbVQVARN6zZN2qBUAWVwzj4wAGQNGDx2vxVwZAipJI4QiwBkD/2IQvLQkHQIy1GExhYwdA8uhcNqi+B0AgaHz3BBsIQGymiqJ6eAhANleaVAzXCEBup9Q0vTYJQE7ukHSQlwlA0tVsT4n5CUD3+WQLq1wKQGf/7fj4wApAACEOc3YmC0DWNHffJo0LQOwnoa4N9QtAaPHkWy5eDEC4/JdtjMgMQKkLKHUrNA1Ai483Dw+hDUB4errjOg8OQFCIE6ayfg5AigAyFXrvDkAY8K/7lGEPQJzc8C8H1Q9AbnggSuokEEB3UXqLAGAQQHRqRFnImxBA+rfhtkPYEEB8PeqtdBURQFzWO05dUxFAaT0Lrv+REUC+UvXpXdERQIigECV6ERJA8h7/iFZSEkDaNwBG9ZMSQDQKA5NY1hJA/+24rYIZE0DOOKjadV0TQMRDP2U0ohNA/rLnn8DnE0At/xnkHC4UQLRBcZJLdRRACkS/Ek+9FEB40iDUKQYVQBVTEk3eTxVAOaGE+26aFUBvLvJk3uUVQN9odBYvMhZAL2jZpGN/FkBW4bmsfs0WQM5hj9KCHBdARtPKwnJsF0DQR+sxUb0XQKoPldwgDxhABBmph+RhGEDWmlwAn7UYQPAKURxTChlAXmCsuQNgGUCXojG/s7YZQJrGWRxmDhpAKNpsyR1nGkBXfpvH3cAaQOOxGCGpGxtAkOwz6YJ3G0DFi3M8btQbQLCRr0BuMhxAaLcsJYaRHEBm07ciufEcQJeUwXsKUx1AYpN6fH21HUAOue96FRkeQCr/JtfVfR5A9IY8+8HjHkBoCoBb3UofQImnknYrsx9AcoPC6lcOIEBL7/oFt0MgQCBpGNy0eSBAsdimQVOwIEBqCqgQlOcgQF+uoyh5HyFA14e3bgRYIUAOzqfNN5EhQJy+7zUVyyFAVGLSnZ4FIkCyhGsB1kAiQNjewGK9fCJARHbTyVa5IkBRMLFEpPYiQIiahuenNCNAyOiwzGNzI0CAKdAU2rIjQBax2eYM8yNAdLwqcP4zJEDsS5vksHUkQJI2kX4muCRASncTf2H7JECBs90tZD8lQLr8c9kwhCVASc0218nJJUA0QXeDMRAmQIuLi0FqVyZALKnje3afJkCJUR6kWOgmQAgmHjMTMidAGCEfqah8J0AiRcyNG8gnQIKMVXBuFChA9hqG56NhKECusdqRvq8oQCVmmBXB/ihAFp3jIK5OKUDVSddpiJ8pQHBznK5S8SlArP+BtQ9EKkBAxRRNwpcqQKrlN0xt7CpA8m89khNCK0CwTP8GuJgrQHN0+Jpd8CtALnFeRwdJLED+KzsOuKIsQIAHh/py/SxAFEhDIDtZLUCmypScE7YtQE4L35X/Ey5AIHzfOwJzLkB+LcnHHtMuQMzIYHxYNC9AON4YprKWL0AUhy6bMPovQIYu491qLzBA4uMEuVJiMECuUCKZ0ZUwQMeZgT3pyTBAx0aYapv+MEAvmhrq6TMxQBUXC4vWaTFAKDXKIWOgMUAqQyaIkdcxQNF4a51jDzJAMjh0RttHMkDIf7lt+oAyQBmNYwPDujJA4rBa/Tb1MkA0VVhXWDAzQEw2+BIpbDNAZM7JN6uoM0Bk9WHT4OUzQMe0bPnLIzRArFC/w25iNEBDhmpSy6E0QIAAzcvj4TRAlwOmXLoiNUDUTyg4UWQ1QL08DZiqpjVArAyovMjpNUD4efnsrS02QPx9w3ZccjZAElOdrta3NkC8sQfwHv42QPVJgZ03RTdANXmbICONN0AYPg/q49U3QAlq0nF8HzhA5REtN+9pOEAiPs/APrU4QJfb5px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EvcDzigtg/0py/lxKH2T9AmmS/Z47aP5A8lwTomNs/mguJJZqm3D8uGMRBhbfdP8oPjNCwy94/iTzgmCTj3z/V1GhV9H7gP+4q+KwCDuE/4ERPnMGe4T/+ehGKNTHiPwberPhixeI/JDv1hE5b4z9PCPfk/PLjP7yE+eZyjOQ/luCocLUn5T/0eGJ+ycTlP1A2niK0Y+Y/kOpwhXoE5z+wOCTkIafnPwwb4ZCvS+g/fJNq8ijy6D9IbuaDk5rpP3RTstT0ROo/OqNDiFLx6j8s1BBWsp/rP742gwkaUOw/jCvwgY8C7T8K+piyGLftP3KTsKK7be4/uqNmbX4m7z+gafdBZ+HvP0Lv3zE+T/A/J+QqFeKu8D/erNGAog/xP+AJA7WCcfE/OFE4/IXU8T90vEerrzjyPwT8dyEDnvI/CfiUyIME8z94qgUVNWzzPzIA44Ua1fM/lLEPpTc/9D+lA1EHkKr0PypmaEwnF/U/9+ItHwGF9T+aVas1IfT1P/RhOFGLZPY/pCKXPkPW9j90iBHWTEn3Py5ll/urvfc/ExzdnmQz+D8M9Hq7eqr4P/IGDVnyIvk/UstTi8+c+T+pNFVyFhj6PztofjrLlPo/oAPGHPIS+z8P9M5ej5L7P5zbC1OnE/w/3APjWD6W/D+w3NLcWBr9P9QFl1j7n/0/lONNUyon/j/mvJ5h6q/+P3Rj4CVAOv8/7GRAUDDG/z8XY3XP3ykAQM4jGW95cQBAsJlcdOe5AEDOWs1TLAMBQMRfSolKTQFAmjoZmESYAUCck/sKHeQBQDbsRHTWMAJAsajwbXN+AkCnYLiZ9swCQBJ3KqFiHANAHfrANbpsA0DKy/gQAL4DQD0TafQ2EARA0ffaqWFjBEA0pmEDg7cEQKGgctudDAVAOVr+FLViBUC4Homby7kFQO5GRGPkEQZAoronaQJrBkAMwQuzKMUGQAsgw09aIAdATIs1V5p8B0DhY3rq69kHQJbJ8zNSOAhAGP5pZ9CXCEB6GyfCafgIQFoeE4shWglAQ0XQEvu8CUBTxdez+SAKQLzVltIghgpAjxKM3XPsCkBdOGVN9lMLQOQ4HaWrvAtAWqoacpcmDEDMkU5MvZEMQFqKU9Yg/gxAXEmNvcVrDUAugUi6r9oNQDgj24/iSg5A7ALFDGK8DkDa2dAKMi8PQLauNW9Wow9AFlBclWkMEEAoiucc1kcQQEqnYNLygxBAOrbmv8HAEEBsZaX1RP4QQD7q5ol+PBFA6B0mmXB7EUAJ0CBGHbsRQP5P6rmG+xFAOi3+I688EkC9L1O6mH4SQLOIbrlFwRJAXjx3ZLgEE0CYxUkF80gTQPzzi+z3jRNA7ATBccnTE0B2+F3zaRoUQIoi3tbbYRRAlfnXiCGqFECqIhJ9PfMUQGO8mC4yPRVA3ujSHwKIFUD2l5jar9MVQPiRSPA9IBZA7MPe+a5tFkAizgqYBbwWQILVRnNECxdA+pjuO25bF0Aqy1aqhawXQH+x5H6N/hdAUAkmgohRGEAuNOmEeaUYQK+rVWBj+hhA6L0E9khQGUA+kxowLacZQKh+XwET/xlA25hZZf1XGkCQp2Zg77EaQHxR1v/rDBtAWKAEWvZoG0A+0XSOEcYbQL107MVAJBxAQN+OMoeDHEAg6/gP6OMcQMoMXaNmRR1AVrqfOwaoHUAtJ3QxygseQEhVeee1cB5ASHxXyszWHkDxx91QEj4fQNhuIPyJph9AFJHLqxsIIEAG7J38jj0gQH341MCgcyBA1NwezlKqIEAaJZr/puEgQAri5TWfGSFAxPcxVz1SIUDQnE9Pg4shQBgKwg9zxSFAdFzPjw4AIkAjqJHMVzsiQP4+CMlQdyJAvikpjvuzIkBX1fIqWvEiQHv0fbRuLyNARZYPRjtuI0BmcisBwq0jQM9rpg0F7iNA+km5mQYvJEDlqRPayHAkQAkn7wlOsyRAZr0ia5j2JEC9ZDZGqjolQBzmduqFfyVAEOwJri3FJUCKTgLuowsmQL6adA7rUiZA+NeLegWbJkAFip6k9eMmQMbxQwa+LSdACI1pIGF4J0DX1Wh74cMnQHJCHadBEChATIb6OoRdKEBPFSPWq6soQJrpfh+7+ihA5ozSxbRKKUAOZtZ/m5spQPxLTgxy7SlAI14hMjtAKkDjI3LA+ZMqQDvzto6w6CpAIKDSfGI+K0C6dC1zEpUrQNFzzmLD7CtA7OV0RXhFLECCMrIdNJ8sQHsFBPf5+SxAZMLu5cxVLUDdRRgIsLItQKL2YoSmEC5AkSYJi7NvLkDxxLhV2s8uQNpiryceMS9AiIrWTYKTL0D+auAeCvcvQCxssn3cLTBAJVH/JslgMECsoLTFTJQwQDhuTxlpyDBAk1N75h/9MEASzSH3cjIxQDrDeRpkaDFAsEIXJfWeMUB/YvvwJ9YxQK1ZpF3+DTJAV8QdUHpGMkBAGRGznX8yQPJP1nZquTJAYriEkeLzMkBYBAT/By8zQJSDHcHcajNAzJKN32KnM0COPhVonOQzQCgajG6LIjRAxkvyDDJhNEDPzYJjkqA0QHTmxZiu4DRABtaj2YghNUCSvHdZI2M1QLa3IlKApTVA4DgfBKLoNUAclZS2iiw2QJbOarc8cTZAKJleW7q2NkDkmRX+Bf02QNPiMgIiRDdAUKtr0RCMN0ACRpzc1NQ3QLtU3ZtwHjhAYjuZjuZoOEA40qE7ObQ4QMVYRjFrADlAhqlpBX9NOUCZr5hVd5s5QMweIcdW6jlAVm8oByA6OkBoHcPK1Yo6QM0tDM963DpAGvg82REvO0CtN8W2nYI7QMNjYz0h1ztAw089S58sPECpFPnGGoM8QA5E1p+W2jxAOGbHzRUzPUBww4tRm4w9QPR5yTQq5z1ACuEnisVCPkCkOmptcJ8+QNSzigMu/T5AdLXVegFcP0CQhQUL7rs/QJgdr3p7DkBANgJlwo8/QEBk4PqGNXFAQPb3tnduo0BATvvdSDzWQEAL3cGzoAlBQKjJ0HadPUFAdk2kVTRyQUCgpxAZZ6dBQHJKNI833UFAsImHi6cTQkBFd+zmuEpCQDjvvn9tgkJA7dLkOce6QkCqdN7+x/NCQMgz171xLUNAA0q2a8ZnQ0DKyi8DyKJDQMfU1YR43kNAevYp99kaREA2xq5m7ldEQJiu+eW3lURAbu/EjTjUREAy1AF9chNFQEkg69hnU0VAOLIXzRqURUDAXY2LjdVFQBj+00zCF0ZAcsAIULtaRkAIqPHaep5GQK5LEToD40ZAH866wFYoR0BMESbJd25HQNAlhLRotUdAtvYT6yv9R0C4Mjfcw0VIQDpzh/4yj0hAUqLrz3vZSED8n63VoCRJQIQnkJykcElA9vXkuIm9SUD2MaPGUgtKQGQWfmkCWkpA2N/7TJupSkBQ/owkIPpKQFiLo6uTS0tAMwbLpfidS0DmVcDeUfFLQMASiiqiRUxAoheRZeyaTEBmXLl0M/FMQLAZe0V6SE1Aajf8zcOgTUB2BioNE/pNQPRG0wprVE5AYHvC186vTkDiidiNQQxPQF6sJ1DGaU9AvrAOS2DIT0DORCpaCRRQQHYYomVwRFBAhG5k7GZ1UEDaRMWX7qZQQLtqBRYJ2VBARhphGrgLUUBCvR5d/T5RQJbdnZvaclFAPEJmmFGnUUDUODcbZNxRQJwMF/ETElJAJqti7GJIUkCod93kUn9SQPZMwbfltlJAFK/ORx3vUkCyLF19+ydTQFPxa0aCYVNAgoiylrObU0C20rFnkdZTQG4sxbgdElRAVMgzj1pOVECaPEL2SYtUQIhERP/tyFRAeLauwUgHVUBirylbXEZVQPDzou8qhlVAT4hgqbbGVUDbfhO5AQhWQN7+6lUOSlZAb4Onvd6MVkCFU640ddBWQJozHQbUFFdA8lHeg/1ZV0CmbbwG9J9XQKI5d+655ldA+PvXoVEuWEBGasaOvXZYQC/EXSoAwFhAIiwC8RsKWUCDP3ZmE1VZQNzu8BXpoFlA15Yzkp/tWUBqWqB1OTtaQOi/UGK5iVpAfZAsAiLZWkC6+wAHdilbQMP/lyq4eltAvhbQLuvMW0CSKrTdESBcQJ7PkwkvdFxABscbjUXJXEA2ym5LWB9dQFifPjBqdl1AXHjlL37OXUA4nX9HlydeQDpiBX24gV5AQ2tl3+TcXkDsPJ+GHzlfQHQc3pNrll9AAD+UMcz0X0AWJctJIipgQK6Sm/trWmBA/g6y0USLYEB6r2B0rrxgQFBe45Cq7mBACGtu2TohYUBgRj0FYVRhQJ5podAeiGFAgGoR/XW8YUBkOzhRaPFhQPSYBJn3JmJAaKW4pSVdYkAesvlN9JNiQPo34G1ly2JAKv8H53oDY0CGdqCgNjxjQO87fYeadWNAJNUmjqivY0BymuusYupjQHjT8OHKJWRAogZEMeNhZED6e+ykrZ5kQOTz/Ews3GRAYJKlP2EaZUAw/0WZTlllQDq8f3z2mGVAw7FIElvZZUDn8f2JfhpmQKKzdhljXGZAHoYX/QqfZkDovOV3eOJmQNIVm9OtJmdAuZi5YK1rZ0Dasp92ebFnQBiNnHMU+GdA8p4EvYA/aEBKfka/wIdoQPXs/+3W0GhAoSQTxMUaaUD2YbzDj2VpQEyvp3Y3sWlAfvAGbr/9aUCeL6hCKktqQOwrDJV6mWpAvit9DbPoakD3ESZc1jhrQPa3KTnniWtAxoy6ZOjba0ARejKn3C5sQHgQK9HGgmxA//qVu6nXbEA8u9VHiC1tQNSu1l9lhG1AEl8o9kPcbUCaGxcGJzVuQPTgxZMRj25A8otIrAbqbkB0Wr5lCUZvQFm7bN8co29AqjbtIKIAcEAtd3VfQTBwQEMe/chtYHBAg3T8/yiRcEA6P8SrdMJwQKodjHhS9HBAsxCBF8QmcUDuLdQ+y1lxQPZ9yalpjXFAAQfHGKHBcUD4A2RRc/ZxQK5IeB7iK3JAvdMrUO9hckCIjga8nJhyQMk7AD3sz3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1Vg1Pa4W/k/oZ+Ho+Sm+T+4qgcl7/L5P4m04A/bP/o/kwZFAKuN+j84rSOaYdz6P45nP4kBLPs/6dpFgY18+z9WC+c9CM77P3YZ7YJ0IPw/DkdUHNVz/D9+QmPeLMj8P2G6w6V+Hf0/4jmbV81z/T8MT6ThG8v9P177RzptI/4/82+3YMR8/j/CFQZdJNf+P2TjQ0CQMv8/jACYJAuP/z+1uFstmOz/P7jemkOdJQBA9NwatHpVAEDeG/gH5oUAQGJrzePgtgBAOWwU8WzoAEDT/zPeixoBQDrjjl4/TQFAGHWSKomAAUCZp8X/arQBQIYe2KDm6AFAYXqx1f0dAkCf0IBrslMCQOVRzDQGigJAgB6BCfvAAkADSgPHkvgCQC8OPlDPMANA8C20jbJpA0DeiJBtPqMDQA3gtuN03QNAXszU6VcYBEA953J/6VMEQBUmBqorkARAdGkBdSDNBEADQOfxyQoFQEreWzgqSQVAiEs3ZkOIBUC5xJefF8gFQNVV9A6pCAZAUKov5flJBkBnFatZDIwGQK/SWarizgZA/H/UG38SB0DH0Gz541YHQBN8QZUTnAdAUWVSSBDiB0A4AZVy3CgIQN32CHt6cAhAD/7Mz+y4CEBu+zPmNQIJQFNb2jpYTAlAy6u7UVaXCUC+dki2MuMJQK1cfPvvLwpAS3H0u5B9CkAO2gWaF8wKQP6v1D+HGwtAJCVrX+JrC0Dt7tCyK70LQKH1IvxlDwxAQ0qrBZRiDEBGY/mhuLYMQG6h+qvWCw1ACh0TB/FhDUDjvDafCrkNQIaXAmkmEQ5AnJ/WYUdqDkC+nO+PcMQOQOdwgQKlHw9A+qvR0ed7D0DhbVIfPNkPQFrM3orSGxBAjymY9JJLEEBIbqPr4HsQQNhZnBO+rBBAUoj6FCzeEECs2R+dLBARQLoDZ17BQhFAN08yEOx1EUCwgPpurqkRQHPtXTwK3hFAUb0vPwETEkB0WYdDlUgSQDUJ0BrIfhJA+7zYm5u1EkAPCOSiEe0SQKhJuBEsJRNAHgawz+xdE0BPcMrJVZcTQC4kvPJo0RNA6RIAQygMFEAZoei4lUcUQOn3sFizgxRAXImOLIPAFEClyMJEB/4UQNkWrbdBPBVACeXcoTR7FUDeCyQm4roVQLRZqW1M+xVAmFf7p3U8FkAmRiMLYH4WQGpSuNMNwRZA4wPzRIEEF0Dw48CovEgXQL5f2E/CjRdA8eTMkZTTF0ADOiPNNRoYQNgSZmeoYRhAkOI6ze6pGEDP6nZyC/MYQJqJNNIAPRlAM8bobtGHGUAaHnnSf9MZQG6SUY4OIBpAyfZ6O4BtGkBDgrF617saQC2je/QWCxtAyxZBWUFbG0A1RWJhWawbQJniT81h/htAbtaiZV1RHEC+aTT7TqUcQNy8Nmc5+hxAw4VNix9QHUCoF6dRBKcdQAC1Fa3q/h1AViwpmdVXHkAwwUgayLEeQJZhzT3FDB9AnikcGtBoH0A/NcHO68UfQOlgRcINEiBA6E/SNrFBIEAf+9ni4XEgQAqs+WihoiBAi5ancPHTIEBVN0Gm0wUhQCDdGbtJOCFAxlyJZVVrIUAI8fpg+J4hQHFG/G000yFAuLNMUgsIIkByn+zYfj0iQDcTLdKQcyJADn2/E0OqIkB1n8V4l+EiQNCw4eGPGSNAgKpGNS5SI0BfyMhedIsjQBE57k9kxSNAAAAAAAAAJEArCRtsSTskQLpvQZdCdyRAoPdriu2zJEBIu5tUTPEkQHMN7AphLyVAM5CkyC1uJUBogUuvtK0lQLc9uOb37SVAIfolnfkuJkBItUYHvHAmQKlgVmBBsyZA8UIu6ov2JkB7k1jtnTonQBtQJLl5fydAkk25oyHFJ0CvgywKmAsoQG2VlFDfUihA/5Ue4vmaKEB1CyMx6uMoQIYvO7eyLSlAnm9W9VV4KUBkLNBz1sMpQOO5hcI2ECpAuqDseHldKkCVISk2oasqQBT7JKGw+ipAYXOmaKpKK0DnpWdDkZsrQGMWLvBn7StAkoniNTFALEC3JKnj75MsQHnU+dCm6CxAYPy43Vg+LUA5b1DyCJUtQKixyP+57C1AaYfi/25FLkCqzDD1Kp8uQKibMuvw+S5ACsBt9sNVL0BreIk0p7IvQMXDNOZOCDBAs8okd9U3MEDWcOzp6GcwQBwkK+CKmDBAQ0xWAL3JMEC5oMf1gPswQNKoy3DYLTFAFmewJsVgMUDqL9TRSJQxQGmstDFlyDFAjwn+Chz9MUB9VJonbzIyQC0EwVZgaDJAaLEGbfGeMkAb/WxEJNYyQPilcrz6DTNAmc0junZGM0Aebioomn8zQFgA3/ZmuTNAcVNZHN/zM0BmloGUBC80QDGUIWHZajRA1SL2iV+nNEBAxsAcmeQ0QEeHWS2IIjVAx//A1S5hNUAJnDI2j6A1QF8SN3Wr4DVAgBG3v4UhNkAoJg5JIGM2QPnYHUt9pTZAxwRhBp/oNkBeZv/Bhyw3QB9m4cs5cTdAhBzEeLe2N0C7kU0kA/03QGw5ITEfRDhAFqv0CA6MOEAQmKQc0tQ4QHX/SeRtHjlADKFP3+NoOUCar4eUNrQ5QNHDQZJoADpABBBhbnxNOkDc1XLGdJs6QGkexT9U6jpA57V9hx06O0BKa7FS04o7QOyUe1543DtAwdoVcA8vPEBaR/BUm4I8QPyfyeIe1zxA+QTI95wsPUAY25F6GIM9QKX+ZlqU2j1AhkE6jxMzPkCUNMsZmYw+QJM9wAMo5z5ASfrAX8NCP0An8pBJbp8/QL6WKuYr/T9AN0rtsf8tQEDsuS399V1AQM/GeHV6jkBASahDwI6/QED/7eSHNPFAQDf3onttI0FAVJXCTztWQUCF2ZW9n4lBQGoOi4OcvUFADN47ZTPyQUDlpHwrZidCQCbya6Q2XUJAFDaCo6aTQkCznqEBuMpCQMEjJp1sAkNA98H1WcY6Q0CQ5pAhx3NDQHwLI+NwrUNArYSTk8XnQ0Bwf5YtxyJEQPIzvrF3XkRA2kmMJtmaREBPcIOY7ddEQGcqORq3FUVAF9BnxDdURUCpxAC2cZNFQAXjPhRn00VA3CC5ChoURkDQaHXLjFVGQKWs+47Bl0ZA0S9plLraRkCDC4Qheh5HQDrszoICY0dAEgqdC1aoR0ASXCYWd+5HQKYHnANoNUhAYgw9PCt9SEBALWsvw8VIQKQXwFMyD0lAX8kiJ3tZSUDjNd0uoKRJQLMrsvej8ElAz3rzFYk9SkCQXJglUotKQEweVMoB2kpA1Q6tr5opS0AhsBOJH3pLQH4t+hGTy0tArxfsDfgdTEAEZ6ZIUXFMQNzEL5ahxUxA7Bzx0usaTUCud87jMnFNQC0eQLZ5yE1AgwhsQMMgTkCOlz+BEnpOQDSbiYBq1E5Ag6UUT84vT0ABrMEGQYxPQL/3osrF6U9A0LKL4y8kUECF+/IYCVRQQELaLCVwhFBAavGurGa1UED8Rc1Y7uZQQD+uyNcIGVFAQWvd3LdLUUCg7VEg/X5RQAXGhV/aslFAF8IAXVHnUUAJNoLgYxxSQJpzELcTUlJAyW4Is2KIUkAgkS2sUr9SQLa7uX/l9lJAvnhtEB0vU0D+XKBG+2dTQAOaURCCoVNASME4YbPbU0AkudYykRZUQOLjhoQdUlRA53mQW1qOVEAMFzjDSctUQC180cztCFVAKoXRj0hHVUBpVOApXIZVQPiz674qxlVAUK05ebYGVkANWHuJAUhWQKbg3yYOilZAT8cnj97MVkALWLgGdRBXQFJcr9jTVFdAUgf3Vv2ZV0AEHVra899XQCBVmMK5JlhAdvp6dlFuWEBVx+ljvbZYQAAAAAAAAFlAdsshxxtKWUChyxE9E5VZQID1Bu3o4FlAIarCaZ8tWkDXEKdNOXtaQD+0zTq5yVpAwmEe2yEZW0AkTWbgdWlbQKp4bwS4ultAkmIYCesMXEDM+Gu4EWBcQLbTueQutFxAYriuaEUJXUAiZG0nWF9dQPagpwxqtl1Am6S3DH4OXkDJurkkl2deQH87plq4wV5ASs5rveQcX0Be+wllH3lfQI8LrHJr1l9AwxtiCGYaYEAulJM5IkpgQHTkk+tremBA/bTZwUSrYEDsHLdkrtxgQBgIaIGqDmFAq8cgyjpBYUADzhz2YHRhQACWrcEeqGFA87ZJ7nXcYUDLJJxCaBFiQLydk4r3RmJAhEVylyV9YkAEb90/9LNiQJyU7V9l62JA8H8+2XojY0BPof+SNlxjQAeYBHqalWNAQ+vVgKjPY0C29MGfYgpkQGD97dTKRWRAC41nJOOBZEAd7TWYrb5kQE3fa0As/GRA7Yg5M2E6ZUANk/6MTnllQNuAXHD2uGVA5DtJBlv5ZUCD1yF+fjpmQPKLvQ1jfGZAlumA8Qq/ZkAyRXFseAJnQMhdSMitRmdAaDyIVa2LZ0B2T49redFnQP/ArGgUGGhApgk1soBfaEBtwJa0wKdoQEaob+PW8GhA+fuhucU6aUBE+Wm5j4VpQJKrc2w30WlA0PfwY78dakAZ6a84KmtqQLk/MYt6uWpAC0O/A7MIa0D21oRS1lhrQNjVpC/nqWtAuq9RW+j7a0BAT+Wd3E5sQAFG+cfGomxA9j9/sqn3bECnv9k+iE1tQKUj9VZlpG1AKfZg7UP8bUC+h2n9JlVuQNLVMYsRr25AHb7NowYKb0Bcf1xdCWZvQE+JI9ccw29AwM3UHKIQcEBiGmlbQUBwQAOq/MRtcHBApcUH/CihcED9MtundNJwQLWRrnRSBHFAE+OuE8Q2cUAUPQ07y2lxQLioDaZpnXFAmCwWFaHRcUD9A75NcwZyQBsD3RriO3JA6iibTO9xckAsX4C4nKhyQPlohDns33JA4gAfsN8Xc0B8JlgCeVBzQG6c2Bu6iXNAWZf67aTDc0A3ntpvO/5zQL6caJ5/OXRAYSh5fHN1dECI+NYSGbJ0QGGSVHBy73RAfyneqYEtdUAEtYvaSGx1QKk6syPKq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j8w7Anvo4vaP6BdQ61R5do/FDZwFUVA2z9k26cTg5zbP8S3+KYQ+ts/EkWj4fJY3D/gJFXpLrncP0g9ZPfJGt0/atQJWcl93T8Ao51vMuLdPyrX0LAKSN4/oP/oplev3j942PrwHhjfPx7xJENmgt8/yiTKZjPu3z9q7mUdxi3gP9sK4lk7ZeA/Y48fbnyd4D9IhnpqjNbgPzBrgWpuEOE/U4sRlSVL4T90M3MctYbhP3CndT4gw+E/59+KRGoA4j/ICeODlj7iP2jEh12ofeI/Dxp3PqO94j/YL76fiv7iP96okwZiQOM/0rlxBC2D4z9Q6S8378bjPxJ6HEmsC+Q/5XsV8WdR5D98gKHyJZjkP8TxBx7q3+Q/3QZpULgo5T/gVdVzlHLlP/X/ZH+CveU/lHZOd4YJ5j+r1/xspFbmP/TfJX/gpOY/O3Lf2T705j+/srS2w0TnP+C2ulxzluc/MMikIFLp5z/TO9hkZD3oP3Lef5mukug/AvaePDXp6D9e2iPa/EDpP6gm+gsKmuk/Y4UcemH06T8gGqbaB1DqPyeL4/EBreo/0K5jklQL6z8O4AedBGvrP67+EwEXzOs/hB8+vJAu7D+48b3adpLsP5jeW3fO9+w/Jep/u5xe7T8sWkDf5sbtPwcrcCmyMO4/8Fit7wOc7j8HBm+W4QjvP0GEE5FQd+8/TEzuYVbn7z/e9CpNfCzwPyXzWG0eZvA/cF5EaZSg8D9770Yg4dvwPyDrV3kHGPE/gEYTYwpV8T815MDT7JLxP7bvW8mx0fE/+FyaSVwR8j+3kfRh71HyP9s+rSduk/I/WG/Zt9vV8j8S02g3OxnzP5tLLtOPXfM/WMHov9yi8z/nRkw6JenzP0SRC4dsMPQ/ycrh8rV49D+sx5zSBML0P6ShJ4NcDPU/fMGVacBX9T9FXC7zM6T1P9lqeJW68fU/DiFHzldA9j8O68YjD5D2P072iiTk4PY/XUybZ9oy9z+EhIOM9YX3PzISYjs52vc/SDX4JKkv+D9YkboCSYb4PzZx4pYc3vg/LLt/rCc3+T+zmosXbpH5P+zj+7Tz7Pk/hTXXarxJ+j9I3EkozKf6P8p8u+UmB/s/MoblpNBn+z8fcupwzcn7PwnUbV4hLfw/aTuti9CR/D8V65kg3/f8P5Ro805RX/0/++RiUivI/T/EgZdwcTL+P+lyY/knnv4/UgDaRlML/z8XZ26993n/PzWcE8wZ6v8/gngu9t4tAEBqzU9RdGcAQIiOCj/PoQBAcUt/DPLcAEAWemQM3xgBQJ4AGZeYVQFA7jC3CiGTAUAcNSjLetEBQL7sN0KoEAJAojqp36tQAkCUwkoZiJECQHIWDGs/0wJAKFITV9QVA0DEJdNlSVkDQE5NISahnQNALnVNLd7iA0DBijgXAykEQAZ4bIYScARA/Ek0JA+4BEBSwLSg+wAFQABGBbPaSgVAiFFJGa+VBUCMLMqYe+EFQCghEf5CLgZAwgwCHQh8BkAAV/bQzcoGQKFM2PyWGgdAntw+i2ZrB0Bct4luP70HQObO/aAkEAhAQzfiJBlkCECnZp0EILkIQCrU0lI8DwlAv/SAKnFmCUCYlR+vwb4JQKqTvgwxGApAOu8keMJyCkB9O/Auec4KQFhptHdYKwtAae0bomOJC0BRQAgHnugLQHW5sggLSQxAjMPNEq6qDEBPa6aaig0NQHZHRh+kcQ1AfLqVKf7WDUCSjX5MnD0OQJblDiWCpQ5AKJGcWrMOD0CxsOieM3kPQBS4Q64G5Q9Ae+XYJxgpEEB4uYcqWmAQQGhYm01LmBBAhzQShe3QEEDUFY/KQgoRQE4sbB1NRBFAXFDOgg5/EUAMcrgFiboRQCY3H7e+9hFA9sj8rbEzEkCa0WQHZHESQKCpmObXrxJAQrYbdQ/vEkDj+MfiDC8TQPbP4mXSbxNALuoxO2KxE0AybBCmvvMTQMJJhPDpNhRAd9JTa+Z6FEAMcxtutr8UQJCrY1dcBRVAiDu3jNpLFUAihLl6M5MVQK8hPZVp2xVAmLxaV38kFkAmE4hDd24WQDE8r+NTuRZA9iNGyRcFF0CiQ2aNxVEXQESU5NBfnxdAe75pPOntF0DxhoqAZD0YQBh54FXUjRhApNAifTvfGEAIoz+/nDEZQGBJde36hBlADAxs4VjZGUCsEFB9uS4aQLeL66sfhRpATDbBYI7cGkBgCSeYCDUbQB0/YVeRjhtA3Zu9rCvpG0Aa/66v2kQcQNs96YChoRxAT0d9SoP/HEAKlfU/g14dQGzncp6kvh1ArE/JrOofHkA9iJ27WIIeQDidgiXy5R5AKuUXT7pKH0DlSyentLAfQCj4YVPyCyBAFYu06CZAIECytoza+XQgQMhXP/VsqiBAjsqECoLgIECLEYnxOhchQKUp/IaZTiFAmosirZ+GIUC62+VLT78hQF7I5VCq+CFA+xeJr7IyIkAO5w5ham0iQNYWoGTTqCJARO1gv+/kIkAS54J8wSEjQEy8Vq1KXyNAOJheaY2dI0AMhWDOi9wjQH0MeQBIHCRAWw0uKsRcJEBGx4F8Ap4kQOYcBi8F4CRAug3wf84iJUC0Zyu0YGYlQMKxbhe+qiVAqU9P/OjvJUBG4FW84zUmQJLWEriwfCZAYE4zV1LEJkCGHZYIywwnQBEiYUIdVidAos4WgkugJ0A89atMWOsnQKzRnS5GNyhAAFQIvBeEKEBXrLyQz9EoQC4YWFBwIClAhvJapvxvKUBGB0BGd8ApQDArlOviESpAohgOWkJkKkBvkqZdmLcqQFjNsMrnCytAaiHzfTNhK0CcA8BcfrcrQPJID1XLDixArrOXXR1nLEACzOh1d8AsQG4EhabcGi1AWiv8AFB2LUBEKgag1NItQCYUnqdtMC5APIMdRR6PLkCuR1iv6e4uQNhnuCbTTy9AEXNa9d2xL0AwFJW3hgowQLm4/3iyPDBAtNnd8nNvMED8ujPezKIwQFAxKPm+1jBAEs4TB0wLMUD4N5DQdUAxQAyxhyM+djFAwspE06asMUBaSIK4seMxQFowe7FgGzJAfQ37obVTMkD6X25zsowyQDw/8xRZxjJAAC1qe6sAM0ArGoehqzszQDme4odbdzNAgGELNb2zM0Aou5e10vAzQDeDNxyeLjRArBnGgSFtNEDIolwFX6w0QIp5ZMxY7DRA2NipAhEtNUDcu27aiW41QJr2fYzFsDVA5oY+WMbzNUDMHseDjjc2QMDo8VsgfDZAtIZwNH7BNkA4TOBnqgc3QMO03lenTjdAihYebXeWN0D7knoXHd83QBhFD86aKDhA1K5LD/NyOEDIZQlhKL44QJsAolA9CjlAEUUFczRXOUAwmM9kEKU5QLmwYMrT8zlAU43yT4FDOkCArrCpG5Q6QLmVz5Ol5TpACIqk0iE4O0B+o70yk4s7QLwd+oj83ztAuPKismA1PEClvoOVwos8QHrtAyAl4zxAiTNASYs7PUBVUSQR+JQ9QBwkhYBu7z1AdAM7qfFKPkCMbTymhKc+QDoCuZsqBT9AQ840t+ZjP0B656MvvMM/QJQtwyJXEkBAdjeCIWBDQEDfmgW++nRAQL68NKcop0BAUn32kOvZQEBEA0A0RQ1BQLOyI083QUFAolDgpMN1QUBuU/D966pBQIpgGSiy4EFAYvh79hcXQkB2UKNBH05CQOhclefJhUJAPAnjyxm+QkBwobjXEPdCQL5r7vmwMENAgHMZJ/xqQ0AghpxZ9KVDQERiuZGb4UNA/hmi1fMdRECEqIox/1pEQEq8ure/mERAnLWfgDfXREDU2t6qaBZFQFLCZ1tVVkVAcvOGvf+WRUBrvvgCathFQFJM/GOWGkZAcudmH4ddRkAmfbd6PqFGQEhZKsK+5UZAVhzNSAorR0Ch7JJoI3FHQK7jaIIMuEdA3rdK/sf/R0Ceo1dLWEhIQFqK59+/kUhAfFygOQHcSECXuovdHidJQNvYLFgbc0lAhqOWPfm/SUDIJIIpuw1KQHgtZb9jXEpApkCJqvWrSkBawyKec/xKQORwaFXgTUtAHBWrkz6gS0CfjG0kkfNLQHkMfdvaR0xAnLEJlR6dTECFWb81X/NMQDrE3qqfSk1ABwFX6uKiTUB2Jt/yK/xNQNBWEMx9Vk5AkBGAhtuxTkD70to7SA5PQIIC/w7Ha09AZDEYLFvKT0DdVF3kAxVQQLan/xFoRVBA4OlPw1t2UEBUnomh4KdQQEhg1Vr42VBA5ntXoqQMUUBNsj4w5z9RQEYp08HBc1FAeIeFGTaoUUAzPf7+Rd1RQLT6LD/zElJAHFRYrD9JUkD+ky0eLYBSQKq80HG9t1JACLnsifLvUkBWvcNOzihTQK7YP65SYlNAdbcDnIGcU0Cil3sRXddTQCZv7g3nElRAYEWPliFPVEDYv462DoxUQCDjLH+wyVRAMAjLBwkIVUBDB/5tGkdVQFmYoNXmhlVAWOrlaHDHVUAhcWxYuQhWQLPrUNvDSlZAaqJBL5KNVkB63pGYJtFWQPyaTWKDFVdAmnBN3qpaV0AKvEpln6BXQHUA9FZj51dAO4YBGvkuWEDINkocY3dYQH622NKjwFhA7rwAur0KWUB4rHRVs1VZQPBpWzCHoVlAEHVm3TvuWUAiQuj20ztaQIDW6h5SilpAmKdG/7jZWkDuvblJCypbQMsc/7dLe1tAMG/mC33NW0AO+2sPoiBcQIvb0JS9dFxAyIKzdtLJXED0hCiY4x9dQEKs0+Tzdl1AfVcBUQbPXUDSI8DZHSheQKji+oQ9gl5ActySYWjdXkBUYXqHoTlfQK2ozxfsll9A3f/3PEv1X0A2pV0VYSpgQHjpLw+qWmBAbzdjL4KLYEDIekMe67xgQOyFBonm7mBAbKLaIXYhYUCmTPWfm1RhQOoaor9YiGFALtFRQq+8YUAQoanuoPFhQESXkpAvJ2JArjZJ+VxdYkDMQW3/KpRiQNiyEX+by2JAaePMWbADY0Cn48h2a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"Kdvals = np.logspace(-3, 1, 5)\n", "\n", "# Decide on your color palette\n", "colors = bokeh.palettes.Blues9[3:8][::-1]\n", "\n", "p = bokeh.plotting.figure(width=400, height=300,\n", " x_axis_label='A_T', y_axis_label='A', \n", " x_axis_type=\"log\", y_axis_type=\"log\",\n", " title = \"A vs. A_T for different values of Kd, B_T=1\",\n", " x_range=[AT.min(), AT.max()])\n", "\n", "\n", "# Loop through colors and BT values (nditer not necessary)\n", "A = np.zeros((Kdvals.size, AT.size))\n", "p.circle(0, 0, size=0.00000001, color= \"#ffffff\", legend=\"K_d\")\n", "for i, (color, Kd) in enumerate(zip(colors, Kdvals)):\n", " A0 = 0.5 * (AT-BT-Kd+np.sqrt((AT-BT-Kd)**2+4*AT*Kd))\n", " A[i,:] = A0\n", " p.line(AT, A0, line_width=2, color=color, legend=str(Kd))\n", " \n", "p.legend.location = \"bottom_right\"\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On a linear scale, zooming in around the transition point, we can see that weaker binding \"softens\" the transition from flat to linear behavior:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2019-05-13T17:30:56.147843Z", "start_time": "2019-05-13T17:30:55.960097Z" } }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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Application\",\"version\":\"1.0.4\"}};\n", " var render_items = [{\"docid\":\"cb7f98cd-ab12-4fd8-9a67-f359d3de5ba8\",\"roots\":{\"4359\":\"ba3fde11-5e0d-4259-9169-8070a6ec1d86\"}}];\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": "4359" } }, "output_type": "display_data" } ], "source": [ "# array of A_total values\n", "AT = np.linspace(50, 150, 1001)\n", "Kdvals = np.array([0.01, 0.1,0.5,1])\n", "BT = 100\n", "\n", "colors = bokeh.palettes.Blues8[::]\n", "\n", "p = bokeh.plotting.figure(width=400, height=300,\n", " x_axis_label='A_T', y_axis_label='A', \n", " x_axis_type=\"linear\", y_axis_type=\"linear\",\n", " title = \"A vs. A_T for different K_d values\",\n", " x_range=[AT.min(), AT.max()])\n", "\n", "# Loop through colors and BT values (nditer not necessary)\n", "A = np.zeros((Kdvals.size, AT.size))\n", "p.circle(0, 0, size=0.00000001, color= \"#ffffff\", legend=\"Kd\")\n", "for i, (color, Kd) in enumerate(zip(colors, Kdvals)):\n", " A0 = 0.5 * (AT-BT-Kd+np.sqrt((AT-BT-Kd)**2+4*AT*Kd))\n", " A[i,:] = A0\n", " p.line(AT, A0, line_width=2, color=color, legend=str(Kd))\n", " \n", "p.legend.location = \"top_left\"\n", "\n", "bokeh.io.show(p)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Ultrasensitivity in threshold-linear response functions\n", "\n", "Threshold-linear responses differ qualitatively from what we had with a Hill function. Unlike the sigmoidal, or \"S-shaped,\" Hill function, which saturates at a maximum \"ceiling,\" the threshold-linear function increases without bound, maintaining a constant slope as input values increase.\n", "\n", "Despite these differences, we can still quantify the sensitivity of this response. A simple way to define sensitivity is the fold change in output for a given fold change in input, evaluated at a particular operating point. The plots below show this sensitivity, $S=\\frac{d log A}{d log A_T}$ plotted for varying $A_T$, and for different values of $K_d$. Note the peak in $S$ right around the transition, whose strength grows with tighter binding (lower $K_d$). " ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2019-05-13T17:44:55.961701Z", "start_time": "2019-05-13T17:44:55.593375Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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\",\"dtype\":\"float64\",\"shape\":[1001]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1001]}},\"selected\":{\"id\":\"7887\",\"type\":\"Selection\"},\"selection_poli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\",\"dtype\":\"float64\",\"shape\":[999]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[999]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[999]}},\"sel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IPp83GQEECxMuCT8K0QQGCgo7ijyxBA3eO3v4vpEECCmEcHqQcRQGYGJe77JRFA4UzL04REEUBDj18YRGMRQIMjshw6ghFAHcM/QmehEUD6vTLry8ARQJovZHpo4BFASTZdUz0AEkCFLFjaSiASQKDkQXSRQBJAdea6hhFhEkB8rxh4y4ESQPb0Zq+/ohJAauholO7DEkBMfpqPWOUSQBW3MQr+BhNAd+ofbt8oE0D6FBMm/UoTQNgnd51XbRNAUFt3QO+PE0Aog/97xLITQLRlvb3X1RNAGxUidCn5E0AsS2MOuhwUQHzHfPyJQBRACbAxr5lkFEA19A2Y6YgUQGiyZyl6rRRAAaBg1kvSFEDjc+cSX/cUQG5TuVO0HBVAKkJjDkxCFUDdk0O5JmgVQD5hi8tEjhVAS/8/vaa0FUAheTwHTdsVQJwMMyM4AhZAeamui2gpFkA3cxS83lAWQJBFpTCbeBZAzTt/Zp6gFkCtOp/b6MgWQCF94g578RZAryMIgFUaF0DFxrKveEMXQLcLah/lbBdAnzycUZuWF0D54p/Jm8AXQE9ltQvn6hdAjacInX0VGEBfrrIDYEAYQFxFu8aOaxhASKgabgqXGEArL7uC08IYQGv9eo7q7hhA4LMtHFAbGUAHJp63BEgZQBwSkO0IdRlAXNzBS12iGUBVTe5gAtAZQD5Tzrz4/RlAocYa8EAsGkDzMY6M21oaQHuc5iTJiRpAT1jnTAq5GkCt01qZn+gaQG5tFKCJGBtAzUzy98hIG0BgPN84XnkbQIyI1PtJqhtAH+Hb2ozbG0BcPhFxJw0cQE3JpFoaPxxArcfcNGZxHEAIixeeC6QcQG9jzTUL1xxAhJWSnGUKHUAxVBl0Gz4dQL+9M18tch1AhNzVAZymHUAUqxcBaNsdQDAcNwOSEB5AJCaarxpGHkDr0dCuAnweQNpNl6pKsh5AMATYTfPoHkAtta1E/R8fQP+UZTxpVx9AdG2B4zePH0Bfw7npaccfQAAAAAAAACBAC09AbH0cIEB0rVKTLTkgQJi1i88QViBA/9ngeydzIECvg+nzcZAgQLEy4JPwrSBAYKCjuKPLIEDd47e/i+kgQIKYRwepByFAYwYl7vslIUDeTMvThEQhQEaPXxhEYyFAhiOyHDqCIUAdwz9CZ6EhQPq9MuvLwCFAmi9kemjgIUBJNl1TPQAiQIUsWNpKICJAneRBdJFAIkBy5rqGEWEiQH+vGHjLgSJA+fRmr7+iIkBq6GiU7sMiQEx+mo9Y5SJAFbcxCv4GI0B36h9u3ygjQPYUEyb9SiNA1Sd3nVdtI0BTW3dA748jQCyD/3vEsiNAtGW9vdfVI0AbFSJ0KfkjQCxLYw66HCRAfMd8/IlAJEAFsDGvmWQkQDH0DZjpiCRAbLJnKXqtJEAFoGDWS9IkQONz5xJf9yRAblO5U7QcJUAqQmMOTEIlQN2TQ7kmaCVAPmGLy0SOJUBH/z+9prQlQB15PAdN2yVAoAwzIzgCJkB9qa6LaCkmQDdzFLzeUCZAkEWlMJt4JkDNO39mnqAmQK06n9voyCZAHX3iDnvxJkCrIwiAVRonQMnGsq94QydAuwtqH+VsJ0CfPJxRm5YnQPnin8mbwCdAT2W1C+fqJ0CNpwidfRUoQFuusgNgQChAV0W7xo5rKEBNqBpuCpcoQC8vu4LTwihAa/16juruKEDgsy0cUBspQAcmnrcESClAHBKQ7Qh1KUBc3MFLXaIpQFBN7mAC0ClAQ1POvPj9KUCmxhrwQCwqQPcxjozbWipAe5zmJMmJKkBPWOdMCrkqQK3TWpmf6CpAbm0UoIkYK0DITPL3yEgrQFs83zheeStAkYjU+0mqK0Ak4dvajNsrQFw+EXEnDSxATcmkWho/LECtx9w0ZnEsQAiLF54LpCxAamPNNQvXLEB/lZKcZQotQDZUGXQbPi1AxL0zXy1yLUCE3NUBnKYtQBSrFwFo2y1AMBw3A5IQLkAkJpqvGkYuQObR0K4CfC5A1E2XqkqyLkA1BNhN8+guQDK1rUT9Hy9ABJVlPGlXL0B0bYHjN48vQF/Duelpxy9AAAAAAAAAMEALT0BsfRwwQHStUpMtOTBAmLWLzxBWMED/2eB7J3MwQK+D6fNxkDBAsTLgk/CtMEBgoKO4o8swQN3jt7+L6TBAgphHB6kHMUBjBiXu+yUxQN5My9OERDFARo9fGERjMUCGI7IcOoIxQB3DP0JnoTFA+r0y68vAMUCaL2R6aOAxQEk2XVM9ADJAhSxY2kogMkCd5EF0kUAyQHjmuoYRYTJAf68YeMuBMkD59Gavv6IyQGroaJTuwzJATH6aj1jlMkAVtzEK/gYzQHfqH27fKDNA9hQTJv1KM0DVJ3edV20zQFNbd0DvjzNALIP/e8SyM0C0Zb2919UzQBsVInQp+TNALEtjDrocNEB8x3z8iUA0QAWwMa+ZZDRAMfQNmOmINEBssmcpeq00QAWgYNZL0jRA43PnEl/3NEBuU7lTtBw1QCpCYw5MQjVA3ZNDuSZoNUA+YYvLRI41QEf/P72mtDVAJXk8B03bNUCgDDMjOAI2QH2protoKTZAN3MUvN5QNkCQRaUwm3g2QM07f2aeoDZArTqf2+jINkAdfeIOe/E2QKsjCIBVGjdAycayr3hDN0C7C2of5Ww3QJ88nFGbljdA+eKfyZvAN0BPZbUL5+o3QI2nCJ19FThAW66yA2BAOEBXRbvGjms4QE2oGm4KlzhALy+7gtPCOEBr/XqO6u44QOCzLRxQGzlAByaetwRIOUAcEpDtCHU5QFzcwUtdojlAUE3uYALQOUBDU868+P05QKbGGvBALDpA9zGOjNtaOkB7nOYkyYk6QE9Y50wKuTpArdNamZ/oOkBubRSgiRg7QMhM8vfISDtAWzzfOF55O0CRiNT7Sao7QCTh29qM2ztAXD4RcScNPEBNyaRaGj88QK3H3DRmcTxACIsXngukPEBqY801C9c8QH+VkpxlCj1ANlQZdBs+PUDEvTNfLXI9QITc1QGcpj1AFKsXAWjbPUAwHDcDkhA+QCQmmq8aRj5A5tHQrgJ8PkDUTZeqSrI+QDUE2E3z6D5AMrWtRP0fP0AElWU8aVc/QHRtgeM3jz9A\",\"dtype\":\"float64\",\"shape\":[999]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[999]},\"y\":{\"__ndarray__\":\"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"Kdvals = np.array([0.00001, 0.0001, 0.001,0.01,0.1])\n", "BT = 1\n", "\n", "# Color palettes:\n", "colors = bokeh.palettes.Blues9[:][::]\n", "scolors = bokeh.palettes.Oranges9[:][::]\n", "\n", "pA = bokeh.plotting.figure(width=400, height=200,\n", " x_axis_label='A_T', y_axis_label='A', \n", " x_axis_type=\"log\", y_axis_type=\"log\",\n", " title = \"A vs A_T for several K_d\",\n", " x_range=[AT.min(), AT.max()])\n", "\n", "pS = bokeh.plotting.figure(width=400, height=200,\n", " x_axis_label='A_T', y_axis_label='S', \n", " x_axis_type=\"log\", y_axis_type=\"log\",\n", " title = \"Sensitivity vs. A_T for several K_d\",\n", " x_range=[AT.min(), AT.max()])\n", "\n", "# Loop through colors and BT values (nditer not necessary)\n", "A = np.zeros((Kdvals.size, AT.size)) # store A values\n", "S = np.zeros((Kdvals.size, AT.size-1)) #sensitivities are derivatives, so there is one fewer of them\n", "foldstep = AT[1]/AT[0]\n", "pA.circle(0, 0, size=0.00000001, color= \"#ffffff\", legend=\"Kd\")\n", "pS.circle(0, 0, size=0.00000001, color= \"#ffffff\", legend=\"Kd\")\n", "for i, (color, scolor, Kd) in enumerate(zip(colors, scolors, Kdvals)):\n", " A0 = 0.5 * (AT-BT-Kd+np.sqrt((AT-BT-Kd)**2+4*AT*Kd))\n", " A[i,:] = A0\n", " pA.line(AT, A0, line_width=2, color=color,legend=str(Kd))\n", "\n", " # define Sensitivity, S, as dlog(A)/dlog(AT)=AT/A*dA/d(AT)\n", " S0 = AT[0:-2]/A[i,0:-2]*(A[i,1:-1]-A[i,0:-2])/(AT[1:-1]-AT[0:-2])\n", " pS.line(AT[0:-2],S0,line_width=2,color=scolor,legend=str(Kd))\n", "\n", "pA.legend.location = \"bottom_right\"\n", "pS.legend.location = \"bottom_right\"\n", "\n", "bokeh.io.show(bokeh.layouts.gridplot([pA, pS], ncols=1))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Incorporating production and degradation\n", "\n", "So far, we considered a static pool of $A$ and $B$, but in a cell, both proteins undergo continuous synthesis and degradation/dilution. Representing these dynamics explicitly leads to similar ultrasensitive responses, but now in terms of the protein production and degradation rates (see Buchler and Louis):\n", "\n", "\\begin{align}\n", "\\frac{dA}{dt}&=\\beta_A - k_{on} A B + k_{\\it{off}} C - \\gamma_A A \\\\\n", "\\frac{dB}{dt}&=\\beta_B - k_{on} A B + k_{\\it{off}} C - \\gamma_B B \\\\\n", "\\frac{dC}{dt}&= k_{on} A B - k_\\it{off} C - \\gamma_C C \\\\\n", "\\end{align}\n", "\n", "(Here, we assume a distinct decay rate for $C$, but could alternatively consider degradation of its $A$ and $B$ constituents at their normal rates)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Demonstrating titration synthetically\n", "\n", "Simple models like the ones above can help us think about what behaviors we should expect in a system. But how do we know if they accurately describe the real behavior of a complex molecular system in the even more complex milieu of the living cell?\n", "\n", "To find out, Buchler and Cross used a synthetic biology approach to test whether this simple scheme could indeed generate the predicted ultrasensitivity. \n", "\n", "They engineered yeast cells to express a transcription factor, a stoichiometric inhibitor of that factor, and a target reporter gene to readout the level of the transcription factor. As an activator they used the mammalian bZip family activator CEBP/$\\alpha$. As the inhibitor they used a previously identified dominant negative mutant that binds to CEBP/$\\alpha$ with a tight $K_d \\approx 0.04 nM$. As a reporter they used a yellow fluorescent protein. To vary the relative levels of the activator and inhibitor, they expressed them from promoters of different strengths. As a control, they also constructed yeast strains without the inhibitor.\n", "\n", "The scheme is shown here:\n", "\n", "
\n", "
\n", "\n", "As shown below (left), the activator generated a dose-dependent increase in the fluorescent protein. (The noticeable decrease at the highest levels is attributed to the interesting effect of transcriptional \"squelching\"--see paper for details). \n", "\n", "Adding the inhibitor (middle panel) produced the predicted threshold-linear response.\n", "\n", "Finally, expressing the inhibitor from promoters of different strengths (right) showed corresponding shifts in the threshold position, as expected based on their independently measured expression levels (not shown). \n", "\n", "
\n", "
\n", "\n", "The conclusions so far: \n", "\n", "* Tight binding can produce ultrasensitivity through molecular titration.\n", "\n", "* Molecular titration is a real effect that can be reconstituted and quantitatively predicted in living cells. \n", "\n", "We now turn to biological contexts in which molecular titration appears." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## small RNA regulation can generate ultrasensitive responses through molecular titration\n", "\n", "One of the most stunning discoveries of the last several decades is the pervasive and diverse roles that small RNA molecules play in regulating gene expression, from bacteria to mammalian cells.\n", "\n", "micro RNA (miRNA) represents a major class of regulatory RNA molecules in eukaryotes. Individual miRNAs typically target hundreds of genes. Conversely, most protein-coding genes are miRNA targets. miRNAs can be highly expressed (as much as 50,000 copies per cell). \n", "\n", "Many miRNAs exhibit strong sequence conservation across species, suggesting selection for function. \n", "\n", "However, at the cell population average level, they sometimes appear to generate relatively weak repression. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To more quantitatively understand how miRNA regulation operates, Mukherji et al developed a system to analyze miRNA regulation at the level of single cells (Mukherji, S., et al, Nat. Methods, 2011). \n", "\n", "The key idea of the design is to express two distinguishable fluorescent proteins, one of which is regulated by a specific miRNA, with the other serving as an unregulated internal control. \n", "\n", "
\n", "
\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "ExecuteTime": { "end_time": "2019-05-13T04:37:27.429007Z", "start_time": "2019-05-13T04:37:27.420939Z" } }, "source": [ "They transfected variants of this construct with (N=1) or without (N=0) a binding site for the miR-20 miRNA:\n", "\n", "
\n", "\n", "As you can see here, without the binding site, the two colors appear to be proportional to each other, as you would expect. But with the binding site, mCherry expression is differentially suppressed at lower YFP levels.\n", "\n", "This can be seen more clearly in a scatter plot of the two colors:\n", "\n", "
\n", "\n", "Here, the YFP x-axis is analogous to our $A_T$, above, while the mCherry y-axis is analogous to $A$. \n", "\n", "\n", "\n", "The authors go on to explore how increasing the number of binding sites can modulate the threshold for repression. The results broadly fit the behavior expected from the molecular titration model. \n", "\n", "These results could help reconcile the very different types of effects one sees for miRNAs in different contexts. Sometimes they appear to provide strong, switch-like effects, as with fate-controlling miRNAs in C. elegans. On the other hand, in many other contexts, they appear to exert much weaker \"fine-tuning\" effects on their targets. When miRNAs are unsaturated, they can have a relatively strong effect on their target expression levels, essentially keeping them \"off.\" On the other hand, when targets are expressed highly enough, the relative effects of the miRNA on their expression can become much weaker.\n", "\n", "\n", "\n", "Returning to the question posed earlier, we now see that a remarkably simple way to create a threshold within a regulatory step is to insert a constitutive, inhibitory miRNA:\n", "\n", "
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that in addition to its general regulatory abilities and thresholding effects, miRNA regulation can also reduce noise in target gene expression. See [Schmiedel et al, \"MicroRNA control of protein\n", "expression noise,\" *Science* (2015)](https://science.sciencemag.org/content/sci/348/6230/128.full.pdf).\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Molecular titration in antibiotic persistence\n", "\n", "Antibiotic persistence is a phenomenon, which we already discussed, in which a small percentage of non-resistant cells survive antibiotic treatment. Once re-grown, the descendants of these cells behave the same as the original culture from which they were obtained, with the same small percentage surviving antibiotic treatment.\n", "\n", "Nathalie Balaban and colleagues have used a variety of elegant approaches to analyze antibiotic persistence at the level of single cells. In [Rotem et al, \"Regulation of phenotypic variability by a threshold- based mechanism underlies bacterial persistence,\" PNAS (2010)](https://www.pnas.org/content/pnas/107/28/12541.full.pdf) they analyze the role of the hipAB toxin-antitoxin system in generating persisters. \n", "\n", "The model for persistence described here combines three major concepts from the course so far: negative autoregulation, stochastic noise in gene expression, and, now, molecular titration.\n", "\n", "In this system, a protein \"toxin\", hipA, is neutralized by the anti-toxin hipB. The proteins are co-expressed in a single operon, and form a tight complex, which represses their own expression:\n", "\n", "
\n", "\n", "\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In a separate set of experiments, they tagged hipA with a red fluorecent protein, and used time-lapse movies to correlate the growth behavior of individual cells with their HipA protein levels.\n", "\n", "As shown in these panels, there appeared to be a threshold relationship, in which growth arrest occurred when HipA (as measured by its fluorescent protein tag) exceeded a threshold concentration:\n", "\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A simple model based on molecular titration, feedback, and noise can explain the key experimental features observed here. The model contains just a few reactions:\n", "\n", "Production of HipA: $ P \\rightarrow P+A $ \n", "\n", "Production of HipB: $ P \\rightarrow P+B $\n", "\n", "HipAB complex formation: $ A + B \\leftrightarrow C $\n", "\n", "Binding and unbinding of to DNA: $ P + C \\leftrightarrow P_C $\n", "\n", "Degradation and dilution of all protein species: $ A,B,C \\rightarrow \\emptyset $ \n", "\n", "Here $A$ and $B$ denote the HipA and HipB proteins, respectively, and $C$ represents the HipA-HipB complex. $P$ and $P_C$ represent the free and bound state of the hipAB promoter. \n", "\n", "They simulated the model stochastically, with the assumption that free $A$ exceeding a threshold causes persistence. In this model, varying the expression level of the antitoxin, HipB, systematically shifted the threshold for persistence, a behavior that also occurred experimentally:\n", "\n", "
\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Molecular titration generates \"walkie-talkie\" behaviors in the Notch signaling pathway\n", "\n", "
\n", "
See slides
\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Beyond pairwise titration\n", "\n", "Today we talked about molecular titration arising from interactions between protein pairs. However, proteins often form more complex, and even combinatorial, networks of homo- and hetero-dimerizing components. One example occurs in the control of cell death (apoptosis) by Bcl2-family proteins, a process that naturally should be performed in an all-or-none way. Another example that we will discuss soon involves the formation of signaling complexes in promiscuous ligand-receptor systems. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusions\n", "\n", "Today we have seen that molecular titration provides a simple but powerful way to generate ultrasensitive responses across different types of molecular systems:\n", "\n", "* The general principle of molecular titration: formation of a tight complex between two species makes the concentration of a \"free\" protein species depend in a threshold-linear manner on its total level or rate of production.\n", "\n", "* Molecular titration could explain key features of miRNA based regulation.\n", "\n", "* Molecular titration appears to underlie the generation of bacterial persisters through toxin-antitoxin systems.\n", "\n", "* Molecular titration between co-expressed, mutually inhibitory ligands and receptors can generate exclusive send-or-receive signaling states in the Notch signaling pathway.\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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()) " } }, "position": { "height": "337.6666564941406px", "left": "586px", "right": "20px", "top": "120px", "width": "320.6666564941406px" }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }