notebooks/simple_examples/YEP24_PGK_XK.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sub cloning by restriction digestion and ligation: The construction of the YEp24PGK_XK vector\n",
    "\n",
    "The objective of this example is to document and simulate a cut and paste cloning from the literature using pydna.\n",
    "The example is the construction of the vector YEp24PGK_XK which is described on page 4250 in the publication below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"300\"\n",
       "            src=\"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC93154\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7f0bc8cfe790>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# NBVAL_SKIP\n",
    "from IPython.display import IFrame\n",
    "IFrame('http://www.ncbi.nlm.nih.gov/pmc/articles/PMC93154', width=\"100%\", height=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cloning strategy\n",
    "\n",
    "1. the [XKS1 gene](http://www.yeastgenome.org/locus/S000003426/overview) from _Saccharomyces cerevisiae_ is amplified by PCR using two primers called primer1 and primer3. The primers has tails which add restriction sites for BamHI to the ends of the PCR product. The sequences of both primers are available in the publication. \n",
    "\n",
    "2. The YEp24PGK plasmid is linearized with the restriction endonuclease [BglII](http://rebase.neb.com/rebase/enz/BglII.html).\n",
    "\n",
    "3. PCR product is digested with the restriction endonuclease [BamHI](http://rebase.neb.com/rebase/enz/BamHI.html).\n",
    "\n",
    "4. The two molecules are ligated together to form a circular product.\n",
    "\n",
    "The figure below shows an image outlining the strategy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 2,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.core.display import Image\n",
    "Image('figure1.png',width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The p1 and p3 primers sequences were given in Johansson et al. The primer sequences are read into [BioPython](http://biopython.org/) [SeqRecord](http://biopython.org/wiki/SeqRecord) objects. Primers are single stranded DNA molecules, so SeqRecords are adequate for describing them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pydna.parsers import parse_primers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "p1, p3 = parse_primers('''\n",
    ">primer1\n",
    "GCGGATCCTCTAGAATGGTTTGTTCAGTAATTCAG\n",
    "\n",
    ">primer3\n",
    "AGATCTGGATCCTTAGATGAGAGTCTTTTCCAG\n",
    "''')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The XKS1 gene sequence is dowloaded from [genbank](https://www.ncbi.nlm.nih.gov/nuccore/NC_001139.9?from=886073&to=887875&report=genbank&strand=true) like so:\n",
    "    \n",
    "1. Go to the [SGD page](http://www.yeastgenome.org/locus/S000003426/overview) of the XKS1 gene \n",
    "2. Entrez Gene link at the bottom of the page goes to the Genbank site for the gene\n",
    "3. Go to the NCBI Reference Sequences (RefSeq) section and click on the Genbank link\n",
    "4. The third line of the genbank file contains the accession entry: `ACCESSION   NC_001139 REGION: complement(886073..887875)`\n",
    "5. Copy and paste the text `NC_001139 REGION: complement(886073..887875)` as the argument for the pydna.Genbank class below.\n",
    "\n",
    "This is but one of many ways to establish sequences in pydna."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pydna.genbank import Genbank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gb = Genbank(\"bjornjobb@gmail.com\")\n",
    "xks1 = gb.nucleotide(\"NC_001139 REGION: complement(886073..887875)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The XKS1 gene has the expected size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<a href='https://www.ncbi.nlm.nih.gov/nuccore/NC_001139 ?from=886073&to=887875&strand=2' target='_blank'>NC_001139  886073-887875</a>"
      ],
      "text/plain": [
       "Gbank(NC_001139  886073-887875)(-1803)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xks1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The sequence starts with an `ATG` start codon and ends with a `TAA` stop codon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseq(-1803)\n",
       "ATGT..CTAA\n",
       "TACA..GATT"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xks1.seq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The convenience methods isorf can tell if the sequence is an open reading frame or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xks1.isorf()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The PCR product sequence is simulated from the primers and the template sequence using the pydna.pcr function. The pydna. Amplicon class offer greater control over the pcr parameters, but this is not needed here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pydna.amplify import pcr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "PCR_prod = pcr(p1, p3, xks1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We import restiction enzymes [BamHI](http://rebase.neb.com/rebase/enz/BamHI.html) and [BglII](http://rebase.neb.com/rebase/enz/BglII.html) from BioPython."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from Bio.Restriction import BamHI, BglII"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Digesting the PCR product yield three fragments, two short stuffer fragments and the insert that we would like to clone. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "stuffer1, insert, stuffer2 = PCR_prod.cut(BamHI)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The insert has the expected sticky ends."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseq(-1819)\n",
       "GATCCTCT..TAAG    \n",
       "    GAGA..ATTCCTAG"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "insert.seq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The YEp24PGK vector is available from [Genbank](https://www.ncbi.nlm.nih.gov/nuccore/KC562906)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "YEp24PGK = gb.nucleotide(\"KC562906\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The plasmid has the expected size (see Genbank link above)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<a href='https://www.ncbi.nlm.nih.gov/nuccore/KC562906?from=&to=&strand=1' target='_blank'>KC562906</a>"
      ],
      "text/plain": [
       "Gbank(KC562906)(o9637)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "YEp24PGK"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The YEp24PGK is linearized with the BglII enzyme. This method will make sure that the molecule is linearized i.e. the enzyme only cuts in one place."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "YEp24PGK_BglII = YEp24PGK.linearize(BglII)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The linear vector has the expected size and structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseqrecord(-9641)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "YEp24PGK_BglII"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The two fragments are ligated together and looped, which means that the far ends of both molecules ligate to form a circular product."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "YEp24PGK_XK = ( YEp24PGK_BglII + insert ).looped() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The resulting molecule i circular and has the expected size, 11452 bp."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseqrecord(o11452)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "YEp24PGK_XK"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<font face=monospace><a href='YEp24PGK_XK.txt' target='_blank'>YEp24PGK_XK.txt</a></font><br>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "YEp24PGK_XK.write(\"YEp24PGK_XK.txt\")"
   ]
  }
 ],
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