notebooks/pGreenLantern1/pGreenLantern1.ipynb

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    "# Assembly of the pGREEN LANTERN™-1 sequence\n",
    "\n",
    "pGreen Lantern-1 is a plasmid expressing humanized GFP from a [CMV](http://blog.addgene.org/plasmids-101-the-promoter-region) promoter. This plasmid can be used [monitor transfection](https://tools.thermofisher.com/Content/Focus/Focus%20Volume%2018%20Issue%202.pdf) of human cells for example.\n",
    "\n",
    "This plasmid was marketed by Gibco under the catalog number 10642. Gibco merged into Life Technologies which was later bought by Thermo Fisher Scientific and the plasmid is no longer available commercially.\n",
    "\n",
    "Unfortunately this means that the plasmid sequence is also unavailable.\n",
    "\n",
    "There was a [recent exchange](https://groups.google.com/forum/#!topic/bionet.molbio.methds-reagnts/_oeYALCz6_U) on the bionet.molbio.methds-reagnts newsgroup where the sequence was requested.\n",
    "\n",
    "One of the [posts](https://groups.google.com/forum/#!topic/bionet.molbio.methds-reagnts/b43z7j5_Qzo) by Dr. Barbara MacGregor, University of North Carolina contained a compilation that could be used in order to compile the sequence.\n",
    "\n",
    "The post by Dr. MacGregor lists three sources:\n",
    "\n",
    "1. <a id='1'></a> [Life Technologies Focus 96, Vol. 18, Number 2](https://tools.thermofisher.com/Content/Focus/Focus%20Volume%2018%20Issue%202.pdf)  \n",
    "\n",
    "2. <a id='2'></a>The original reference: [Zolotukhin et al. (1996) J. Virol. 70:4646-4654](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC190401) \n",
    "\n",
    "3. <a id='3'></a>The gfp sequence used deposited in GenBank under [U50963](https://www.ncbi.nlm.nih.gov/nuccore/1289497/) \n",
    "\n",
    "4. <a id='4'></a>[US6638732B1 Mutants of Green Fluorescent Protein](https://patents.google.com/patent/US6638732B1/en) \n",
    "\n",
    "The a reference to [#3](#3) is also made in [#2](#2) so this should be correct. Additionally there is a patent [#4](#4) where the pGreen Lantern-1 is mentioned.\n",
    "\n",
    "The original reference ([#2](#2)) can be seen below:"
   ]
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    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"500\"\n",
       "            src=\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC190401\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7f29085fa850>"
      ]
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     "execution_count": 1,
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     "output_type": "execute_result"
    }
   ],
   "source": [
    "# NBVAL_SKIP\n",
    "from IPython.display import IFrame\n",
    "IFrame('https://www.ncbi.nlm.nih.gov/pmc/articles/PMC190401', width=\"100%\", height=500)"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "The paragraph below was lifted from [#2](#2) and describes how the humanized gene(s) were made with a series of overlapping oligonucelotides. Two primers are described that were used to amplify the synthetic gene in order to clone it in the pBS vector. We can assume that the GFP sequence is identical to [#3](#3). The final product is the pBS_GFPH1 vector.\n",
    "\n",
    "\n",
    ">**Synthesis of the gfph cDNA.** The gfph cDNA was synthesized by assembling mutually priming synthetic oligonucleotides (Fig. 1). The gene was divided into eight segments of approximately equal length, and four pairs of oligonucleotides were synthesized, each pair consisting of two overlapping oligonucleotides with a short stretch of overlap (underlined in Fig. 1), one coding for the sense strand and the other coding for the antisense strand. After annealing and extension with Sequenase, pairs 1 and 2 were digested with EaeI, whereas pairs 3 and 4 were digested with BamHI. The digested products were then ligated in two separate reactions: pairs 1 and 2 and pairs 3 and 4. Ligation products of the desired length were purified on a 5% polyacrylamide gel under nondenaturing conditions. Both DNA fragments were then digested with EcoRII and ligated to each other. The final product was amplified by PCR, using a pair of oligonucleotides partially complementary to the gfph cDNA (boldface in the sequences presented below) and containing the restriction sites NotI, XbaI, and HindIII (underlined in the sequences presented below) for cloning. The sequence of the upstream primer, which included a Kozak consensus sequence (18), was 59-TGCTCTAGAGCG GCCGCCGCCACCATGAGCAAGGGCGAGGAACTG-39; the downstream primer sequence was 59-CGGAAGCTTGCGGCCGCTCACTTGTACAGCTCGTCCAT- 39. After digestion of the PCR product with XbaI and HindIII, the DNA fragment was cloned into pBS(1) (Stratagene) and sequenced. Several independent clones were isolated and sequenced. These clones had mutations in the coding sequence which presumably either occurred during PCR amplification or were present in the oligonucleotides. Portions of these clones were then spliced together to produce the final gfph gene that encoded a wild-type amino acid sequence. The resulting construct, designated pBS-GFPH1, contained the coding sequence for wild-type GFP. Two mutants were constructed in the pBS-GFPH background by site-directed PCR mutagenesis. One of these converted Ser-65 to Thr and was called pBS-GFPH2; the other converted Tyr-66 to His and was called pBSGFPHB.\n",
    "\n",
    "\n",
    "[pydna](https://github.com/BjornFJohansson/pydna) is used to describe the cloning process."
   ]
  },
  {
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   "execution_count": 2,
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   "outputs": [],
   "source": [
    "from pydna.genbank import Genbank\n",
    "from pydna.parsers import parse_primers\n",
    "from pydna.amplify import pcr\n",
    "from pydna.readers import read\n",
    "from pydna.gel     import gel"
   ]
  },
  {
   "cell_type": "markdown",
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     "id": "6c1c1d63-1f5f-48b4-bf7c-19ce8e4e3cdb"
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   "source": [
    "we get the gfp gene from Genbank according to #2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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   "outputs": [],
   "source": [
    "gb = Genbank(\"bjornjobb@gmail.com\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
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   },
   "outputs": [],
   "source": [
    "humanized_gfp_gene = gb.nucleotide('U50963')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "id": "5337a332-63ab-43d1-bbb8-cbfec6189434"
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   },
   "source": [
    "The upstream and downstream primers were described in #2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
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     "id": "40739163-2162-4d14-9f44-755d3897edd1"
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   },
   "outputs": [],
   "source": [
    "up, dp = parse_primers('''\n",
    ">upstream_primer\n",
    "TGCTCTAGAGCGGCCGCCGCCACCATGAGCAAGGGCGAGGAACTG\n",
    ">downstream_primer\n",
    "CGGAAGCTTGCGGCCGCTCACTTGTACAGCTCGTCCAT''')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:03.895821Z",
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     "id": "1ca41e0e-a851-455d-91af-83040f3cd669"
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   },
   "outputs": [],
   "source": [
    "humanized_gfp_product = pcr(up, dp, humanized_gfp_gene)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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   "outputs": [
    {
     "data": {
      "text/html": [
       "Amplicon(758)"
      ],
      "text/plain": [
       "Amplicon(758)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "humanized_gfp_product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                        5ATGAGCAAGGGCGAGGAACTG...ATGGACGAGCTGTACAAGTGA3\n",
       "                                                 |||||||||||||||||||||\n",
       "                                                3TACCTGCTCGACATGTTCACTCGCCGGCGTTCGAAGGC5\n",
       "5TGCTCTAGAGCGGCCGCCGCCACCATGAGCAAGGGCGAGGAACTG3\n",
       "                         |||||||||||||||||||||\n",
       "                        3TACTCGTTCCCGCTCCTTGAC...TACCTGCTCGACATGTTCACT5"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "humanized_gfp_product.figure()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "9548115d-b452-4fbe-b059-78427e28b463"
    }
   },
   "source": [
    "The PCR product contain the entire GFP coding sequence as expected. The PCR product was digested with [XbaI](http://rebase.neb.com/rebase/enz/XbaI.html) and [HindIII](http://rebase.neb.com/rebase/enz/HindIII.html).\n",
    "\n",
    "We import the restriction enzymes from [BioPython](http://biopython.org/wiki/Biopython):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
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    },
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     "id": "50497459-f847-4f8f-b733-c9a4f165680d"
    }
   },
   "outputs": [],
   "source": [
    "from Bio.Restriction import XbaI, HindIII"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:03.935400Z",
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    },
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     "id": "00975e7b-111f-4e34-9477-1ec385db80c9"
    }
   },
   "outputs": [],
   "source": [
    "stuffer, gene_fragment, stuffer = humanized_gfp_product.cut(XbaI, HindIII)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseqrecord(-750)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gene_fragment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "4df77524-c380-4bc5-ad04-537fe99c2334"
    }
   },
   "source": [
    "The gene fragment has the expected size and sticky ends:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:03.953879Z",
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    },
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     "id": "55619171-33c2-4596-9c7a-4e976df77daa"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseq(-750)\n",
       "CTAGAGCG..CGCA    \n",
       "    TCGC..GCGTTCGA"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gene_fragment.seq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "a5356241-3a21-4cf8-914e-2209a254b0b7"
    }
   },
   "source": [
    "The pBS(+) plasmid is also known as [BlueScribe](https://www.snapgene.com/resources/plasmid_files/basic_cloning_vectors/pBS(+) which is available from Genbank under L08783."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:03.963258Z",
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    },
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     "id": "c97210ea-c66a-4a42-b2cc-e9a975e14644"
    }
   },
   "outputs": [],
   "source": [
    "pBSplus = gb.nucleotide(\"L08783\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:05.264452Z",
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    },
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     "id": "964cb20f-1904-4ede-bfe5-b30554dc88de"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Dseqrecord(-28), Dseqrecord(-3184))"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stuffer, pBS_lin = pBSplus.cut(XbaI, HindIII)\n",
    "stuffer, pBS_lin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "4ba73f9e-8ec2-4c1a-bc87-990c13de2999"
    }
   },
   "source": [
    "A small 28 bp stuffer fragment is lost upon digestion:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:05.273132Z",
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    },
    "nbpresent": {
     "id": "f28ee000-0c13-487e-8ad1-338c9a435914"
    }
   },
   "outputs": [],
   "source": [
    "pBS_GFPH1 = (pBS_lin+gene_fragment).looped()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "19e2cac1-420a-40f3-a52f-fbaef27ed7e4"
    }
   },
   "source": [
    "The pBS_GFPH1 plasmid is 3926 bp long"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:05.280472Z",
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     "id": "3ee33903-2f38-49e9-b57f-06f98c54a25a"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseqrecord(o3926)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pBS_GFPH1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "id": "71e695ba-b8ee-4cd2-8234-06ffa06024e5"
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   },
   "source": [
    "The second paragraph in the Materials section in [#2](#2) is harder to follow. The first part describes the construction of a vector with wild type GFP which is substituted for the humanized GFP in the end.\n",
    "\n",
    "Plasmids referenced are:\n",
    "1. TU#65\n",
    "2. [pCMVb](https://plasmid.med.harvard.edu/PlasmidRepository/file/sequence/pCMVbeta.txt)\n",
    "3. [pRc/CMV](https://www.addgene.org/vector-database/3907/)\n",
    "4. pTRBR\n",
    "\n",
    "The TU#65 plasmid is described in:\n",
    "\n",
    "Chalfie, M., Y. Tu, G. Euskirchen, W. W. Ward, and D. C. Prasher. 1994.\n",
    "Green fluorescent protein as a marker for gene expression. Science 263:802–\n",
    "805.\n",
    "\n",
    "The paper above says very little about the construction or sequence of the TU#65.\n",
    "\n",
    "The pTRBR plasmid is described in:\n",
    "\n",
    "Ryan, J. H., Zolotukhin, S., and Muzyczka, N. (1996) Sequence requirements for binding of Rep68 to the adeno-associated virus terminal repeats. J. Virol. 70, 1542–1553.\n",
    "\n",
    "The construction of pTRBR has more details, but refer to sequences in older papers.\n",
    "\n",
    "Another problem is that the sequences for PCR primers described below were not given in the publication. This makes is almost impossible to follow the cloning strategy without additional information.\n",
    "\n",
    "What we can say for sure is that the NotI cassette in pBS_GFPH1 containing the humanized GFP is identical to the one in the final pGreen Lantern-1 sequence (see last emphasized text in paragraph below).\n",
    "\n",
    "\n",
    ">**Construction of rAAV vector plasmids.** Briefly, the gfp10 sequence was subcloned into the NotI site of **pCMVb** (Clontech) after digestion of the parent plasmid TU#65 (4) with AgeI and EcoRI, filling in the ends with Klenow DNA polymerase, and adding NotI linkers. \n",
    "\n",
    ">The resulting plasmid, designated **pCMV green**, was then used as a template to amplify in a PCR the transcription cassette containing the cytomegalovirus (CMV) promoter, the simian virus 40 (SV40) intron, the gfp10 cDNA, and the SV40 polyadenylation signal. \n",
    "\n",
    ">The upstream PCR primer complementary to the CMV promoter also included an overhang that contained the BglII, EcoRI, and KpnI sites. \n",
    "\n",
    ">The downstream PCR primer,complementary to the polyadenylation signal, included a SalI site overhang. \n",
    "\n",
    ">The polyadenylation signal of the bovine growth hormone gene was amplified in another PCR using plasmid **pRc/CMV** (Invitrogen) as the template. \n",
    "\n",
    ">The upstream primer in this reaction contained a SalI site overhang, and the downstream primer contained a BglII site. After purification of the PCR products on a 1% agarose gel, the respective fragments were digested with SalI and ligated to each other via the exposed SalI ends. \n",
    "\n",
    ">The ligation product was gel purified and digested with BglII. The 160-bp BglII-PstI fragment, containing the AAV terminal repeat, was isolated by gel purification from plasmid **pTRBR**(1) (30). \n",
    "\n",
    ">This fragment had been subcloned into pTRBR(1) from the previously described plasmid dl3-94 (26). It was then ligated to both ends of the BglII-digested cassette, containing the CMV promoter, SV40 intron, gfp10 cDNA, SV40 poly (A) site, and bovine growth hormone poly(A) site. The ligation product was then cut with PstI and subcloned into plasmid pBS(1) (Stratagene), which had been modified by converting the PvuII sites at positions 766 and 1148 into PstI sites by adding PstI linkers and deleting the internal 382-bp fragment, containing the polylinker region. The resulting plasmid was designated pTRgreen. The neomycin resistance gene (neo) cassette, driven by the herpes simplex virus thymidine kinase gene promoter and the enhancer from polyomavirus, was obtained from plasmid pMClneo (Stratagene) by cutting the plasmid with XhoI, filling in the ends with Klenow DNA polymerase, adding SalI linkers, and digesting with SalI. The DNA fragment containing the neo cassette was gel purified and subcloned into the SalI site of pTRgreen. The resulting construct, pTRBS-UF (UF for user friendly), is depicted in Fig. 2. **To construct pTRBS-UF1, pTRBS-UF2, or pTRBSUFB, we substituted the NotI fragment of pBS-GFPH1 (wild type), pBS-GFPH2 (Thr-65), or pBS-GFPHB (His-66), respectively, for the NotI fragment of pTRBS-UF** (Fig. 2). Any DNA fragment that had undergone PCR amplification was sequenced to confirm the identity of the original sequence."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "b79d87bb-aefd-4fea-9388-09b47a15c806"
    }
   },
   "source": [
    "## 2nd attempt\n",
    "\n",
    "A google search for pGreen Lantern-1 sequence revealed that there is a plasmid deposited at Addgene where the depositors claim that the backbone in pGreen Lantern-1.\n",
    "\n",
    "This plasmid is called [pGL-MLKif3B](https://www.addgene.org/13744/).\n",
    "\n",
    "The construction of this vector is described in:\n",
    "\n",
    "Ginkel, L. M., and Wordeman, L. (2000) Expression and partial characterization of kinesin-related proteins in differentiating and adult skeletal muscle. Mol. Biol. Cell 11, 4143–4158. [here](https://www.ncbi.nlm.nih.gov/pubmed/11102514)\n",
    "\n",
    "The paragraph below was lifted from Ginkel et al.:\n",
    "\n",
    ">***Expression Constructs***The GFP-KIF3B-motorless deletion construct (GFP-KIF3B-ML) was made by modifying GFP-MCAK (Maneyet al., 1998) in pOPRSVI-CAT (Stratagene). Briefly, by using aNdeI site inserted at the junction  of  the  GFP  and  MCAK  coding  regions  by  site-directed  mutagenesis  (QuikChange  site-directed  mutagenesis  kit;  Stratagene), MCAK  was  removed  by NdeI-XhoI  digestion.  Before  making  the GFP-KIF3B-ML,  a  GFP-KIF3B-tail  construct  was  made.  The NdeI/XhoI  fragment  of  KIF3B  used  to  make  the  bacterial  expression construct was inserted into NdeI-XhoI sites of the prepared vector. To make GFP-KIF3B-ML, the incorporated NdeI site was removed and  replaced  with  an  AvrII  site  (QuikChange  site-directed  mutagenesis kit; Stratagene). The fragment of KIF3B corresponding to the coiled-coil plus part of the tail domain (nucleotides 1154 –1888,amino  acids  364 – 609)  was  generated  by  PCR  from  the  isolatedpBluescript II-KIF3B. AvrII and BbsI sites, incorporated into the 59and 39PCR primers, respectively, were used to insert the fragment into  the  AvrII  site  at  the  GFP  junction  and  the  unique  BbsI  site within the tail domain. **The resulting GFP-KIF3B-ML coding region was  removed  from  pOPRSVICAT  with NotI  and  inserted  into pGREEN-LANTERN-1  (Life  Technologies,  Rockville,  MD)  due  to increased expression in C2C12 cells.**\n",
    "\n",
    "The important part is the final one wich indicate that we can recreate the pGreen Lantern-1 sequence by removing the NotI insert and replacing it with the original insert. \n",
    "\n",
    "We know that the NotI insert of pGreen Lantern-1 is the same as for the pBS_GFPH1 vector wich we have. \n",
    "\n",
    "We will use this alternative shortcut to try to recreate the sequence:\n",
    "\n",
    "The pGL-MLKif3B plasmid is difficult to read programatically, here we use the requests and the lxml libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:05.290333Z",
     "iopub.status.busy": "2021-10-31T13:27:05.289427Z",
     "iopub.status.idle": "2021-10-31T13:27:06.758804Z",
     "shell.execute_reply": "2021-10-31T13:27:06.757808Z"
    },
    "nbpresent": {
     "id": "4ac29d5b-42f5-4bd2-b9a9-acb9b2cad9fc"
    }
   },
   "outputs": [],
   "source": [
    "import requests\n",
    "from lxml import html\n",
    "r = requests.get('https://www.addgene.org/13744/sequences/')\n",
    "tree = html.fromstring(r.text)\n",
    "rawdata_addgene_full_sequence = tree.xpath(\".//*[@id='depositor-full']\")\n",
    "pGL_MLKif3B = read( rawdata_addgene_full_sequence[0].text_content() ).looped()\n",
    "rawdata_addgene_partial_sequence = tree.xpath(\".//*[@id='addgene-partial']\")\n",
    "pGL_MLKif3B_partial = read( rawdata_addgene_partial_sequence[0].text_content() )\n",
    "assert len(pGL_MLKif3B) == 6210"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "46e2956d-03b3-4afa-a50f-eebdf742d946"
    }
   },
   "source": [
    "The sequence seems to have the correct size:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.766631Z",
     "iopub.status.busy": "2021-10-31T13:27:06.765959Z",
     "iopub.status.idle": "2021-10-31T13:27:06.770539Z",
     "shell.execute_reply": "2021-10-31T13:27:06.770073Z"
    },
    "nbpresent": {
     "id": "f6d6b4eb-3546-4c3b-8da2-966fda9b294f"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseqrecord(o6210)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pGL_MLKif3B"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "cc063655-187d-4c9d-9809-3d4030f9757f"
    }
   },
   "source": [
    "We cut out the NotI fragment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.773748Z",
     "iopub.status.busy": "2021-10-31T13:27:06.772590Z",
     "iopub.status.idle": "2021-10-31T13:27:06.778695Z",
     "shell.execute_reply": "2021-10-31T13:27:06.779242Z"
    },
    "nbpresent": {
     "id": "b3edca1b-1e2c-4e73-8d90-55b4b73a16b4"
    }
   },
   "outputs": [],
   "source": [
    "from Bio.Restriction import NotI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.794628Z",
     "iopub.status.busy": "2021-10-31T13:27:06.793804Z",
     "iopub.status.idle": "2021-10-31T13:27:06.805219Z",
     "shell.execute_reply": "2021-10-31T13:27:06.806428Z"
    },
    "nbpresent": {
     "id": "c7879227-5378-45b0-9f5f-3151dffea4c4"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Dseqrecord(-4304), Dseqrecord(-1914))"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Kif3b_GFP, pGL_backbone = pGL_MLKif3B.cut(NotI)\n",
    "Kif3b_GFP, pGL_backbone"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "10d7dfa0-6458-40fd-9ac7-068204759730"
    }
   },
   "source": [
    "The remaining backbone sequence is 4304 bp."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "d2edfbf2-5cb6-45c8-ac4c-7ebbe3e3743a"
    }
   },
   "source": [
    "We cut out the NotI GFP cassette from pBS_GFPH1 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.828160Z",
     "iopub.status.busy": "2021-10-31T13:27:06.825903Z",
     "iopub.status.idle": "2021-10-31T13:27:06.832097Z",
     "shell.execute_reply": "2021-10-31T13:27:06.831632Z"
    },
    "nbpresent": {
     "id": "cad9558e-3c7f-456a-8420-54d4c0b12f57"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Dseqrecord(-3198), Dseqrecord(-736))"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "humanized_gfp_NotI_frag, pBS_bb = pBS_GFPH1.cut(NotI)\n",
    "humanized_gfp_NotI_frag, pBS_bb "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "d7e07939-df77-4090-a2cb-c62713554157"
    }
   },
   "source": [
    "Then we combine the backbone from pGL_MLKif3B (4304) with the insert from pBS_GFPH1 (736)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.838239Z",
     "iopub.status.busy": "2021-10-31T13:27:06.837542Z",
     "iopub.status.idle": "2021-10-31T13:27:06.839808Z",
     "shell.execute_reply": "2021-10-31T13:27:06.839383Z"
    },
    "nbpresent": {
     "id": "d8c5e241-72d7-46d8-aadb-c0bbfdbd5e22"
    }
   },
   "outputs": [],
   "source": [
    "pGreenLantern1 = (pGL_backbone + humanized_gfp_NotI_frag).looped()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "fc3cf0a7-9329-4505-b9cb-2c7f9d7b533d"
    }
   },
   "source": [
    "the sequence seems to have roughly the correct size (5kb):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.844161Z",
     "iopub.status.busy": "2021-10-31T13:27:06.842849Z",
     "iopub.status.idle": "2021-10-31T13:27:06.849732Z",
     "shell.execute_reply": "2021-10-31T13:27:06.850242Z"
    },
    "nbpresent": {
     "id": "0dd80b5b-22d7-4993-b083-e87601923c5e"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dseqrecord(o5104)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pGreenLantern1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.855902Z",
     "iopub.status.busy": "2021-10-31T13:27:06.855241Z",
     "iopub.status.idle": "2021-10-31T13:27:06.857817Z",
     "shell.execute_reply": "2021-10-31T13:27:06.859741Z"
    },
    "nbpresent": {
     "id": "da18dddb-ae40-4ac1-9bd5-f74cffa2fe40"
    }
   },
   "outputs": [],
   "source": [
    "pGreenLantern1.locus=\"pGreenLantern1\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "fc4d5779-4b00-4c8f-a1e8-1f36f2dafc52"
    }
   },
   "source": [
    "The candidate for the pGreenLantern1 sequence can be downloaded from the link below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.867253Z",
     "iopub.status.busy": "2021-10-31T13:27:06.866186Z",
     "iopub.status.idle": "2021-10-31T13:27:06.883371Z",
     "shell.execute_reply": "2021-10-31T13:27:06.884538Z"
    },
    "nbpresent": {
     "id": "a91b0b99-3583-493f-b723-cf07793ff561"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<font face=monospace><a href='pGreenLantern1.gb' target='_blank'>pGreenLantern1.gb</a></font><br>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pGreenLantern1.write(\"pGreenLantern1.gb\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "19ea49e8-c297-45e5-8230-8b01e0040950"
    }
   },
   "source": [
    "The plasmid map below is from the patent ([#4](#4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:06.910775Z",
     "iopub.status.busy": "2021-10-31T13:27:06.909599Z",
     "iopub.status.idle": "2021-10-31T13:27:07.533891Z",
     "shell.execute_reply": "2021-10-31T13:27:07.532682Z"
    },
    "nbpresent": {
     "id": "0a4f4ae5-ae1b-4825-abcc-7fa10cd02c40"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 26,
     "metadata": {
      "image/png": {
       "width": 300
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(\"https://patentimages.storage.googleapis.com/US6638732B1/US06638732-20031028-D00005.png\", width=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "92a382d6-4b70-4800-a236-343319ada027"
    }
   },
   "source": [
    "The map below was made with [plasmapper](http://wishart.biology.ualberta.ca/PlasMapper/) and it corresponds roughly to the map from the patent above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:07.548400Z",
     "iopub.status.busy": "2021-10-31T13:27:07.547112Z",
     "iopub.status.idle": "2021-10-31T13:27:07.562071Z",
     "shell.execute_reply": "2021-10-31T13:27:07.560909Z"
    },
    "nbpresent": {
     "id": "df5f01f9-8928-4f28-85e9-a97315d9babf"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 27,
     "metadata": {
      "image/png": {
       "width": 600
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(\"plasMap203_1479761881670.png\", width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "57e6f104-a876-4ed7-8c2a-defd14359933"
    }
   },
   "source": [
    "## Check sequence by restriction digest\n",
    "\n",
    "If the actual plasmid is available, the sequence assembled here can be compared \n",
    "by restriction analysis to the acutal vector.\n",
    "\n",
    "[NdeI](http://rebase.neb.com/rebase/enz/NdeI.html) cuts the sequence three times prodcing fragments that are easy to distinguish by gel. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:07.572071Z",
     "iopub.status.busy": "2021-10-31T13:27:07.571481Z",
     "iopub.status.idle": "2021-10-31T13:27:07.577282Z",
     "shell.execute_reply": "2021-10-31T13:27:07.577934Z"
    },
    "nbpresent": {
     "id": "e3d5f7c8-45d6-4cd4-975a-027aeacda163"
    }
   },
   "outputs": [],
   "source": [
    "from Bio.Restriction import NdeI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:07.593737Z",
     "iopub.status.busy": "2021-10-31T13:27:07.592820Z",
     "iopub.status.idle": "2021-10-31T13:27:07.597973Z",
     "shell.execute_reply": "2021-10-31T13:27:07.597307Z"
    },
    "nbpresent": {
     "id": "2d8b408d-f6b8-46c9-8bcd-8eda659a6994"
    }
   },
   "outputs": [],
   "source": [
    "fragments = pGreenLantern1.cut(NdeI)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:07.612012Z",
     "iopub.status.busy": "2021-10-31T13:27:07.610546Z",
     "iopub.status.idle": "2021-10-31T13:27:07.621419Z",
     "shell.execute_reply": "2021-10-31T13:27:07.619387Z"
    },
    "nbpresent": {
     "id": "f2fcf386-6a57-4614-97c2-da8f1d0a4a08"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Dseqrecord(-976), Dseqrecord(-4132))"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fragments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:07.630471Z",
     "iopub.status.busy": "2021-10-31T13:27:07.629756Z",
     "iopub.status.idle": "2021-10-31T13:27:07.634215Z",
     "shell.execute_reply": "2021-10-31T13:27:07.633393Z"
    },
    "nbpresent": {
     "id": "82a1f9a1-6c41-4665-8661-291b727fb5ac"
    }
   },
   "outputs": [],
   "source": [
    "from pydna.ladders import PennStateLadder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-10-31T13:27:07.648493Z",
     "iopub.status.busy": "2021-10-31T13:27:07.647611Z",
     "iopub.status.idle": "2021-10-31T13:27:07.702833Z",
     "shell.execute_reply": "2021-10-31T13:27:07.702069Z"
    }
   },
   "outputs": [
    {
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# NBVAL_SKIP\n",
    "display(gel([PennStateLadder, fragments]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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