Team:Harvard/Template:NotebookData

== June 7th ==

Miniprep of pKD42 (lambda red)

The lambda red plasmid is needed to enable the recombination used to insert the selection/expression systems into our E. coli cultures.

Procedure: followed Qiagen Kit instructions, each student (8) using 1 mL cell suspension

Results: DNA reasonably pure (260/280 between 1.8 and 2) and between 25 and 50 ng/µL

== June 8th ==

PCR to connect ultramers into OZ052 (Zif268 F2 triplicate, GCCGATGTC)and OZ123 (Zif268 F2 triplicate, GAGTGGTTA):

OZ052:

• 3µL OZ052_F (10µM stock)
• 3µL OZ052_R (10µM stock)
• 5µL 10x Pfx amplification buffer
• 1.5µL dNTPs
• 1µL MgSO4
• 0.4µL DNA polymerase
• 36.1µL ddH2O

OZ123:

• 3µL OZ123_F (10µM stock)
• 3µL OZ123_R (10µM stock)
• 5µL 10x Pfx amplification buffer
• 1.5µL dNTPs
• 1µL MgSO4
• 0.4µL DNA polymerase
• 36.1µL ddH2O

Parameters:

• 1) 94⁰C for 5 min
• 2) 94⁰C for 15 sec
• 3) 60⁰C for 30 sec
• 4) 68⁰C for 1 min
• 5) Repeat 2-4 for 25 cycles
• 6) 68⁰C for 5 min
• 7) 4⁰C forever

== June 9th ==

• Created cell culture with selection construct (contains ZFB, His3, pyrF on plasmid) and reporter RFP (this will be used to test positive control ZFs, cells fluoresce green when ZF binds)
  • Picked colonies, grew in LB/amp liquid media until mid-log
    • 3 mL of LB, 1.5 µL of 2000x amp
  • Once mid-log reached, created glycerol stock, stored stock at -80⁰C.
    • 300 µL bacteria, 1200 µL 80% glycerol This should have been 1200 µL bacteria media, 300 µL 80% glycerol (Corrected 6/14/2011) (80% pure glycerol, 20% molecular grade water)
  • Spiked new tubes of media with 25 µL bacteria from the mid-log tube to leave overnight

NOTE: reporter RFP did not grow to mid-log by end of day, will let grow overnight to saturation and continue creating glycerol stock tomorrow.

• Plated selection strain from gel stab onto tet plate.

• Began primer design for creating the kan/selection construct fusion (see our primer spreadsheet for details).

Contents 1 June 9th - Bioinformatics 2 June 10th - Bioinformatics 2.1 Visualizations 2.2 Properties of amino acids 2.3 Gel images 3 June 13th - Bioinformatics 3.1 Today's Gel Images 4 June 14 - Bioinformatics 5 June 15th - Bioinformatics 6 June 16 - Bioinformatics

June 9th - Bioinformatics

Today we focused on reacquainting and familiarizing ourselves with Python. We completed the parsing (reading in) of the sequence and amino acid data so that it is easy to work with: by substituting each amino acid abbreviation (ex. A, N) with its numeric equivalent (ex. 1, 14), we can use a lot of nice math comparisons instead of messy letter/"string" comparisons.

After that, we worked on counting the number of times each amino acid appears in each of the 7 positions (unfortunately given by -1,1,2,3,5,6,7), and counting the number of times amino acids are next to each other (ex. ACTQRNF has AC, CT, TQ, etc pairings). Taken overall, we found that L is overwhelmingly in position 5.

Acid	-1	1	2	3	5	6	7
A	77	140	210	197	0	312	85
C	12	24	1	6	14	0	0
D	413	16	694	258	0	142	14
E	125	74	152	107	0	58	132
F	0	0	22	0	10	0	0
G	12	201	328	125	0	177	62
H	93	144	232	652	0	51	17
I	70	21	3	26	0	94	73
K	108	372	46	169	6	321	52
L	176	37	20	22	3325	75	55
M	36	54	5	28	0	31	10
N	23	150	129	940	0	182	61
P	3	298	77	7	0	36	8
Q	813	158	180	13	0	136	30
R	870	539	137	55	3	428	2517
S	99	970	859	278	0	140	12
T	243	134	223	350	0	834	83
V	166	26	27	115	0	341	146
W	19	0	13	0	0	0	0
Y	0	0	0	10	0	0	1

For pairings, we found patterns, but none as obvious as the L-in-position-5. Read this like a multiplication table: the intersection of L row and M column is how often that pairing was observed.

'	A	C	D	E	F	G	H	I	K	L	M	N	P	Q	R	S	T	V	W	Y
A	10	0	99	55	0	29	122	20	32	332	2	59	55	63	255	87	24	43	0	0
C	0	0	15	0	0	3	0	0	0	5	0	0	6	0	31	6	14	0	0	0
D	99	15	94	92	0	39	62	6	84	342	15	120	55	42	277	290	87	21	0	8
E	55	0	92	42	0	34	77	1	38	141	2	39	4	29	134	28	90	26	0	1
F	0	0	0	0	0	0	0	10	0	0	0	22	4	0	2	4	6	0	0	0
G	29	3	39	34	0	38	56	0	14	126	1	95	28	47	119	125	38	7	0	0
H	122	0	62	77	0	56	118	9	103	498	4	88	24	26	87	159	70	2	0	0
I	20	0	6	1	10	0	9	6	8	95	3	5	17	3	62	16	17	4	0	0
K	32	0	84	38	0	14	103	8	84	386	24	44	19	102	269	163	113	22	1	0
L	332	5	342	141	0	126	498	95	386	174	32	686	16	112	362	276	875	360	0	8
M	2	0	15	2	0	1	4	3	24	32	0	7	2	11	39	14	3	1	0	0
N	59	0	120	39	22	95	88	5	44	686	7	8	36	28	120	254	84	34	1	0
P	55	6	55	4	4	28	24	17	19	16	2	36	0	3	29	150	21	13	11	0
Q	63	0	42	29	0	47	26	3	102	112	11	28	3	100	261	314	125	19	0	0
R	255	31	277	134	2	119	87	62	269	362	39	120	29	261	618	343	504	281	0	0
S	87	6	290	28	4	125	159	16	163	276	14	254	150	314	343	592	173	91	0	0
T	24	14	87	90	6	38	70	17	113	875	3	84	21	125	504	173	154	28	0	0
V	43	0	21	26	0	7	2	4	22	360	1	34	13	19	281	91	28	12	0	0
W	0	0	0	0	0	0	0	0	1	0	0	1	11	0	0	0	0	0	0	0
Y	0	0	8	1	0	0	0	0	0	8	0	0	0	0	0	0	0	0	0	0

Follow up work on this will be to convert this table to frequencies instead of values: values are less meaningful.

== June 10th ==

• What we learned today: don't put E. coli plates in the -20C freezer!

• Observed a well populated selection strain plate and placed it in the 4C refrigerator

• Took the selection construct culture and extracted the plasmid through miniprep
  • Observed 260/280 ratio of 1.90 and 1.88 through Nanodrop
  • Observed concentrations of 87.7 and 100.6 ng/µL through Nanodrop

• Made 10 new agar plates with LB and amp

June 10th - Bioinformatics

Visualizations

We spent the first few hours today making cool visualizations and graphs of the data we found on the 9th: heatmaps turned out to be an annoying limitation of Python, so a Python/R hybrid was used, and bar charts were made exclusively in Python. See the dropbox for our pretty (and hopefully informative compared to spreadsheets) charts/graphs.

File:Heatmap pairing.png A heatmap of the pairing data. The darker the blues indicate that the pairing occurs more often.

We then started work on TNN and GNN properties specifically (essentially repeating the June 9th work, but confined to smaller data sets). There are some differences between TNN and GNN: see graphs in dropbox. We decided that there was not enough data for fingers that bind to ANN and CNN triplets to perform significant analysis on it.

File:Gnn pairing heatmap.png A heatmap of the GNN pairing data.

File:Tnn pairing heatmap.png A heatmap of the TNN pairing data.

• Overall, similar color clusters are found in the heatmaps. In all cases, L and N are often placed consecutively on the helix. There are fewer clusters of high frequency when looking at TNN binders.

We then, using the theorized framework from a paper (2011 Persikov [http://iopscience.iop.org.ezp-prod1.hul.harvard.edu/1478-3975/8/3/035010/]), tried to match amino acid binding to each base pair to see if there was a pattern. See dropbox document .../bioinformatics/Binding Frequency for that data. There's a lot of it.

Properties of amino acids

We then worked on finding properties of the each position (hydrophobic/phillic, non/polar):

Hydrophilic vs Hydrophobic

Position	Very Phobic	Hydrophobic	Neutral	Hydrophillic
6	285	85	204	2782
5	542	312	1334	1169
4	3334	14	0	9
3	191	203	1417	1536
2	91	211	1819	1236
1	138	164	1604	1451
-1	468	90	1257	1542

Polar vs Nonpolar

Position	Polar	Nonpolar
6	2917	440
5	2290	1067
4	9	3348
3	2830	527
2	2652	705
1	2555	802
-1	2784	573

Follow up work here is to check more properties, and maybe try individual pairings (ex. phobic-philic, polar-phillic).

== June 13th ==

The control zinc fingers OZ052 and OZ123 were amplified with overhanging primers to allow its insertion into the Wolfe plasmid:

Overhang PCR for ultramers: the template was the product of the ultramer PCR (see 6/8/11), and several concentrations were used

In all the tubes:

• 5 µL Pfx amplification buffer
• 1.5 µL dNTPs
• 1 µL MgSO4
• 0.4 µL polymerase
• 38.1 µL ddH2O
• 1.5 µL OZ052_up and 1.5 µL OZ052_down OR 1.5 µL OZ123_up and 1.5 µL OZ123_down

In OZ052 (1) and OZ123 (1):

• 1 µL of ultramer PCR product

In OZ052 (1:10) and OZ123 (1:10):

• 1 µL of a 1 in 10 dilution of ultramer PCR product

In OZ052 (1:100) and OZ123 (1:100):

• 1 µL of a 1 in 100 dilution of ultramer PCR product

Parameters:

• 94⁰C for 5 min
• 94⁰C for 15 sec
• 55⁰C for 30 sec
• 68⁰C for 30 sec
• Repeat steps 2-4 for 25 cycles
• 68⁰C for 5 min
• 4⁰C forever

Gel to verify proper amplification (1% agarose gel, 10 µL 1 kb ladder, 120 V):

The OZ052 lanes (1-3) had bands at the proper length (328 bp) at all three concentrations, although there were several fainter bands likely from side products. Only the undiluted OZ123 lane showed any bands, and from the faint band at 328 and the stronger band around 250 it appears that the PCR did not work well, and the majority of the product was the ultramer from the first PCR.

PCR around vector: the template used was the Wolfe selection construct plasmid miniprepped 6/10/11 (100.6 ng/µL stock) Reagents the same as above except:

• 1.5 µL of Wolfe_F and 1.5 µL of Wolfe_R primers to each tube
• plasmid tube (1 ng) given 1 ng of template (1 µL of a 1 in 100 dilution)
• plasmid tube (10 ng) given 10 ng of template (1 µL of a 1 in 10 dilution)

Parameters same as above except:

• elongation (step 4) 5 minutes (vector approximately 5 kb)

Gel to verify proper amplification (1% agarose, 10 µL 1 kb ladder, 170V)

There were no bands of the correct size in the lanes. The only band that appeared was a faint, short band in one lane that likely was a primer. Since the DNA ladder worked, the problem likely was not with the electrophoresis but with the PCR reaction, perhaps due to issues with the primers.

Gel images

June 13th - Bioinformatics

Today we started work on a program to statistically generate possible sequences.

The four functions needed to do this are:

• generate(matrix, pseudocounts (lambda), dependency tuples)

takes a matrix of zinc-finger AA position counts, a list of dependent amino acid pairs, and a pseudocount multiplier and generates a list of potential amino acid sequences weighted by independent and dependent probabilities

• add_pseudo(dependent matrix row,independent matrix row)

given a matrix row of dependent counts (i.e. how many times 'a' occurs at position n when 'b' is set to some AA at position m) and a row of independent matrix counts (how many times 'a' occurs at n regardless of b's AA) return an adjusted matrix row, based on the dependent matrix row, that has pseudocounts added to the values that are empty in the dependent matrix row but filled in the independent matrix row.

• generate_indep(matrix)

randomly pick an amino acid, given a matrix row, from a weighted random distribution based on the values in the row

• generate_dep(indep_row, dep_row, lambda)

add pseudo counts (call add_pseudo) and generate a dependent random call for a position (using generate_indep on the adjusted matrix)

We finished generate_indep, generate_dep, and add_pseudo today, along with creating a 140x140 matrix of needed values.

== June 14 ==

• Made four LB-based media solutions, and later created glycerol stocks from these and placed in -80⁰C freezer
  • Selection strain (ΔHis3ΔPyrFΔrpoZ) in 3 mL LB and 3µL of 1000x Tet solution stock
  • Selection strain (ΔHis3ΔPyrFΔrpoZ) in 3 mL of LB only solution stock (control)
  • Kan cassette (pZE22G) in 3 mL of LB solution stock and 3 µL of kanamycin solution stock
  • Lambda Red (pKD42) in 3 mL of LB and 3 µL Amp solution stock
    • For all of these stocks, we tried to grow all to mid-log and then place them in 1,200 µL of culture and 300 µL of 80 % glycerol solution (This is the correct protocol for creating a glycerol stock; refer to June 9th)
    • We were only able to get the kan cassette to mid-log and created glycerol stock of the kan cassette
    • Observations included contamination of a pKD46 liquid culture, and we are leaving Lambda Red and both solutions with the selection strain for overnight growth
• Ran 1% gel (150V) with the rest of the OZ123 and OZ052 overhang PCR samples
  • Used better ladder today, less the 1 kb ladder
  • Bands followed the same pattern as the gel run on 6/13/11
• Used gel extraction to obtain the correct OZ123 and OZ052 PCR product from the gel
  • Used Qiagen quick gel extraction kit
  • OZ052 (from undiluted lane): 7.0 ng/µL, 260/280=2.42 (Note: this sample had a strange yellow substance in the column--may have been contaminated)
  • OZ052 (from undiluted lane): 12.0 ng/µL, 260/280=2.02
  • OZ052 (from 1:10 dilution): 10.8 ng/µL, 260/280=2.04
  • OZ052 (from 1:10 dilution): 15.2 ng/µL, 260/280=1.82
  • OZ052 (from 1:100 dilution): 20.6 ng/µL, 260/280=2.17
  • OZ123 (from undiluted lane): 6.3 ng/µL, 260/280=2.17
• PCR the backbone fragment of the plasmid using Wolfe_R and Wolfe_L primers and a lower annealing temperature than before due to the lower melting point of Wolfe_L
  • Reagents:
    • 22µL Invitrogen Platinum PCR supermix
    • 1µL template from a 1 in 100 dilution (1 ng)
    • 1µL Wolfe_F and 1µL Wolfe_R
  • 94°C for 30 s
  • 94°C for 30 s
  • 53°C for 30 s
  • 70°C for 5 min
    • Previous three steps repeat 30 times
  • 70°C for 5 min
  • 4°C forever
• Performed a restriction enzyme digestion on the selection construct plasmid using EcoRI to test for presence/absence of inserted selection construct
  • 1µL EcoR1
  • 1µL buffer 4
  • 2µL backbone plasmid
  • 6µL ddH2O
  • Incubate at 37 degrees for 90 min
  • There is only one EcoR1 site (GAATTC) in the plasmid, so we should see 1 band at about 5kb
• Ran a gel (1%, 170 V) on the backbone fragment (Wolfe primers) PCR product and restriction digestion result
  • Observations: the EcoR1 digest produced the expected band of around 5kb. The backbone did produce a 5kb band but also had a secondary smaller product, perhaps due to one of the primers annealing to a sequence that is a close match to its target.
• Began gradient PCR on the selection strain backbone with Wolfe_R and Wolfe_F primers because of the large difference in melting temperatures between the two
  • Set the annealing temperatures within the PCR to go from 50-57 C and ran with 5 minute extension phases at 70 C
  • Ran overnight

Today's Gel Images

June 14 - Bioinformatics

We finished writing the generate function, and now have a working sequence generator. We also began more in-depth research into the 2011 work by Persikov which deals with how the zinc finger binds to DNA. He predicts several relations which we should be able to test.

Persikov sent us his SVM code (used to calculate the probability of a sequence binding to given DNA), so we also worked on adapting this to use when narrowing our sequences to those most likely to work.

• There are four canonical amino acid-base interactions involved in zinc finger interactions.
  • Amino acids in positions -1, 3, and 6 on the helix are known to interact with the 3 bases of the triplet. In addition, the amino acid in position 2 interacts with the upstream base of the complementary strand (Klug 2010).
  • In addition, Persikov (2011) has proposed novel interactions between these four amino acids based on his analysis of zinc finger binding data upto 2005.
  • Persikov uses the information between these four amino acid-base interactions in his SVM, to determine whether a finger would be a good binder to a particular DNA sequence.
• In order to use his program, we need to convert the helices that are created by the generator into a format the SVM accepts.
  • The SVM only considers the four canonical interactions. It assigns a numerical value to each possible amino acid-base combination. The program that converts our data into a format the SVM accepts creates a string with these numerical values based on Persikov's key. (See this page for more details on this program.)

Brandon learned basic Python today. Justin created a JavaScript program that recognizes potential binding sites from a given sequence.

Name: Mark Kopelman

Concentration: Human Evolutionary Biology

Team Affiliation:
Team TolC and Web Design

Other Hobbies:
Winning

Favourite YouTube Video:
http://www.youtube.com/watch?v=WGoi1MSGu64

Way to Pass Time While Waiting for PCR:
...Run another PCR, duh.

==June 15th==

Gradient PCR: 5µL of each PCR product were run on a 1% gel. No bands appeared: the PCR appears to not have worked.

Selection construct: bacteria containing the selection construct (plasmid containing ZF, omega subunit, ZFB, His3, URA3, etc.) was made into a glycerol stock (see 6/14 and 6/9), miniprepped, and used for PCR:

• Miniprep: used Qiagen kit
  • 82.5ng/µL, 260/280=1.99
  • 91.1ng/µL, 260/280=2.01
  • 77.9ng/µL, 260/280=1.98
• PCR:
  • PCR used to amplify section of plasmid containing zinc finger binding site, weak promoter, His3, and URA3 (with homology to join it to kan cassette)
  • Reagents
  • zinc finger binding site and weak promoter, selection construct plasmid:
    • 1µL ZFB-wp-f (5µM) (made by 1:20 dilution of 100µM stock)
    • 1µL ZFB-wp-hisura-r (5µM) (made by 1:20 dilution of 100µM stock)
    • 1µL selection construct (1:100 dilution of overnight culture)
    • 22.5µL of invitrogen's Platinum PCR SuperMix
  • PCR used to amplify the kan cassette
  • Reagents
  • KAN cassette, pZE22g plasmid:
    • 1µL hisura-kan-f (5µM) (made by 1:20 dilution of 100µM stock)
    • 1µL kan-r (5µM) (made by 1:20 dilution of 100µM stock)
    • 1µL pZE22g (1:100 dilution of glycerol stock culture)
    • 22.5µL of invitrogen's Platinum PCR SuperMix
  • Parameters:
• 1) 94°C for 2 min (denature template, activate enzyme)
• 2) 94°C for 30 sec (denature)
• 3) 53°C for 30 sec (anneal)
• 4) 72°C for 2 min (extend)
• 5) Repeat 2-4 for 25 cycles total
• 6) 72⁰C for 5 min
• 7) 4°C forever

PCR Purification:

• Used the Qiagen PCR purification kit and instructions in order to purify the Kan cassette and selections construct PCR products
  • Nanodrop the purification results and observed 3 ng/µL for Kan cassette and 29.8 ng/µL for ZFB-wp-His3: purification did not work well, especially for the kan

Selection strain (ΔHis3ΔPyrFΔrpoZ):

• saturated overnight culture was inoculated again: 3mL LB, 3µL tet, 30µL of overnight culture, at 37C until mid-log
• glycerol stock
• For transformation tomorrow we grew up pKD42 in 3 mL of LB, 1.5 µL of ampicillin(2000x) and one colony at 30 C
  • Also grew up more of the selection strain so it will be ready for electroporation transformation

Gel

• Ran gel with Kan cassette and selection construct (Binding site, His3, and URA3)
  • Observations successful and image below
  • Used 1 kb plus ladder

PCR Overlap

• since the purification was not very successful, we used 3µL saved from the original PCR product
• Procedure
  • 25µL of 2x Phusion Master Mix
  • 1 µL of ZFB-wp-HisURA-R (100µM)
  • 1µL of HisURA-Kan-F (100µM)
  • 21 µL of water
  • 1 µL Kan template and 1 µL of ZFB-wp-His3-URA3
    • 4 tubes
      • Both undiluted
      • Both 1:10 dilution
      • Both 1:100 dilution
      • Both 1:1000 dilution
• Protocol
  • 98 C for 30 s
  • 98 C for 10 s
  • 53 C for 30 s
  • 72 C for 3 min
  • Repeat steps 2-4 for 24 more cycles
  • 72 C for 5 min
  • 4 C 4EVA!!!

June 15th - Bioinformatics

• We continued research into Persikov's and others' work on binding.

• We worked on using the OPEN data to test Persikov's binding-predicting program: SVM

• Justin continued work on a sequence-finding program, the most up to date version can be found in the Dropbox under code/zfsitefinder.html.
• Justin and Will found 10 candidate sequences across 4 diseases that hopefully should encompass a good amount of diversity in terms of expanding the ZF library. These sequences can be found in the table below, with more details here. The most up to date version can be found in the Dropbox under sequences/Target Loci Sequences.

Disease	Target Range	Binding Site Location	Bottom Finger	Top Finger	Bottom AA (F3 to F1)	Top AA (F3 to F1)
Colorblindness	chrX:153,403,001-153,407,000	370	GTATTTGTT	GGGCCTGCT	N/A	N/A
Colorblindness	chrX:153,403,001-153,407,000	3627	GCTGGCTGG	GCGGTAATG	EGSGLKR.EAHHLSR.#######	RRDDLTR.QRSSLVR.#######
Cystic Fibrosis	chr7:117,074,084-117,089,556	14767	GCAGGTGAT	AAAGAGCCC	QNGTLGR.EAHHLSR.#######	N/A
Familial Hypercholesterolemia	chr19:11,175,000-11,195,000	14001	GGCTGAGAC	GGAGTCCTG	ESGHLKR.QREHLTT.#######	QTTHLSR.DHSSLKR.#######
Tay-Sachs	chr15:72,674,944-72,688,031	5888	GTCTGGTCA	TCAAACTCC	DRSSLRR.RREHLTI.#######	N/A
Pancreatic Cancer	chr7:117,074,084-117,089,556	1739	GATCAAGCT	GTTTCAGTG	N/A	N/A

• We collected 15 alternative zinc finger backbones (different from zif268 backbone) and their corresponding base sequences. Many of these were from Persikov 2011 and all binding sequences were confirmed on the Protein Data Bank website at http://www.pdb.org/pdb/home/home.do. The zinc finger PDB ID's and related links are:

PDB ID	Binding Sequence	Link
1F2I	ATGGGCGCGCCCAT	[http://www.pdb.org/pdb/explore/explore.do?structureId=1F2I]
1G2D	GACGCTATAAAAGGAG	[http://www.pdb.org/pdb/explore/explore.do?structureId=1G2D]
1G2F	TCCTTTTATAGCGTCC	[http://www.pdb.org/pdb/explore/explore.do?structureId=1G2F]
1MEY	ATGAGGCAGAACT	[http://www.pdb.org/pdb/explore/explore.do?structureId=1MEY]
1TF6	ACGGGCCTGGTTAGTACCTGGATGGGAGACC	[http://www.pdb.org/pdb/explore/explore.do?structureId=1TF6]
1UBD	AGGGTCTCCATTTTGAAGCG	[http://www.pdb.org/pdb/explore/explore.do?structureId=1UBD]
1TF6	ACGGGCCTGGTTAGTACCTGGATGGGAGACC	[http://www.pdb.org/pdb/explore/explore.do?structureId=1TF6]
1YUI	GCCGAGAGTAC	[http://www.pdb.org/pdb/explore/explore.do?structureId=1YUI]
2DRP	CTAATAAGGATAACGTCCG	[http://www.pdb.org/pdb/explore/explore.do?structureId=2DRP]
2GLI	TTTCGTCTTGGGTGGTCCACG	[http://www.pdb.org/pdb/explore/explore.do?structureId=2GLI]
2I13	CAGATGTAGGGAAAAGCCCGGG	[http://www.pdb.org/pdb/explore/explore.do?structureId=2I13]
2KMK	CATAAATCACTGCCTA	[http://www.pdb.org/pdb/explore/explore.do?structureId=2KMK]
2PRT	CGCGGGGGCGTCTG	[http://www.pdb.org/pdb/explore/explore.do?structureId=2PRT]
2WBS	GAGGCGC	[http://www.pdb.org/pdb/explore/explore.do?structureId=2WBS]
2WBU	GAGGCGTGGC	[http://www.pdb.org/pdb/explore/explore.do?structureId=2WBU]

==June 16th==

• So there was totally a crazy bee hive outside today!!

Glycerol Stock pKD42

• Grew up pKD42 in 30 C and once reached mid-log created glycerol stock and placed in -80 refrigerator

Overlap PCR gel

• Ran gel to test if overlap PCR that ran through the night worked, and it did not
  • Used PCR product without purification which gives good explanation for why it didn't work

• PCR: Since the PCR done the previous day (6/15) we made a back up PCR using phusion mastermix (Finnzyme)
  • PCR used to amplify section of plasmid containing zinc finger binding site, weak promoter, His3, and URA3 (with homology to join it to kan cassette)
  • Reagents
  • zinc finger binding site and weak promoter, selection construct plasmid:
    • 1µL ZFB-wp-f (100µM) (taken directly from the primer tube)
    • 1µL ZFB-wp-hisura-r (100µM) (taken directly from the primer tube)
    • 2µL selection construct (1:100 dilution of overnight culture)
    • 25µL Phusion High-Fidelity PCR Master Mix
    • 21µL distilled water (for total volume of 50µL)
  • PCR used to amplify the kan cassette
  • Reagents
  • KAN cassette, pZE22g plasmid:
    • 1µL hisura-kan-f (100µM) (taken directly from the primer tube)
    • 1µL kan-r (100µM) (taken directly from the primer tube)
    • 2µL pZE22g (1:100 dilution of glycerol stock culture)
    • 25µL of Phusion High-Fidelity PCR Master Mix
    • 21µL distilled water (for total volume of 50µL)
  • Parameters:
    • 1) 94°C for 2 min (denature template, activate enzyme)
    • 2) 94°C for 30 sec (denature)
    • 3) 53°C for 30 sec (anneal)
    • 4) 72°C for 2 min (extend)
    • 5) Repeat 2-4 for 25 cycles total
    • 6) 72⁰C for 5 min
    • 7) 4°C forever
• Ran PCR product on a gel: bands of the correct size were observed, though the kan band was much fainter than the ZFB-wp-his3

• Repeat PCR (to get a higher concentration of the Kan cassette and ZFB-wp-his3 constructs)
  • same as the above backup PCR (since it was successful), but to a 4x total volume of 200µL, compared to 50µL
  • PCR products were run on a gel: the correct bands were observed--see image below ("second gel")
  • PCR product purification: followed Qiagen kit instructions. Strangely, the conc. was 64.6 ng/µL for Kan, purity 2.09 (260/280) and for ZFB-wp-his3, the conc. was 23.7ng/µL and the purity was 1.92 (260/280).

Overlap PCR: used the kan cassette (64.6 ng/µL) and ZFB-wp-his3-ura3 (23.7 ng/µL) purified above

• 1 µL of kan and 1 µL of ZFB-wp-his3-ura in each tube according to the following conditions:
  • two tubes: undiluted
  • two tubes: both diluted 1 in 10
  • two tubes: both diluted 1 in 100
• 12.5µL Phusion master mix
• 8 µL ddH2O
• primers: 1.25 µL ZFB-wp-hisura_r (10 µM) and 1.25 µL hisura-kan_f (10 µM)
  • we tried two different reaction types: one added the primers as usual before starting the PCR reaction, the other added the primers after 10 PCR cycles (allowing the polymerase to first use the overlapping kan and ZFB to elongate, and then the primers)
• Parameters for PCR starting with primers:
  • (PCR machine 5, program name EXT3KB in IGEM folder)
  • 1) 98°C for 1 min (denature template, activate enzyme)
  • 2) 98°C for 15 sec (denature)
  • 3) 65°C for 15 sec (anneal)
  • 4) 72°C for 2 min (extend)
  • 5) Repeat 2-4 for 30 cycles total
  • 6) 72⁰C for 5 min
  • 7) 4°C forever
• Parameters for PCR starting without primers:
  • 1) 98C for 1 min
  • 2) 98C for 15 sec
  • 3) 65C for 15 sec
  • 4) 72C for 1 min
  • 5) back to step 2 for 10 cycles (PCR paused after 10 and primers added)
  • 6) 98C for 15 sec
  • 7) 65C for 15 sec
  • 8) 72C for 2 min
  • 9) back to step 6 for 20 cycles
  • 10) 72C for 5 min
  • 11) 4C forever

Transformation

• Used the selection strain (ΔHis3ΔPyrFΔrpoZ) cells at mid-log and attempted to place lambda red (pKD42) plasmid into the cell
• Procedure
  • Keep on ice through out whole procedure before use of the electroporation machine
  • Spin 1.5 mL of mid-log cells at 4 C for 1 minute at 18000 rcf (we created two tubes through the following steps)
  • Discard supernatant and resuspend with 1 mL of cold water
  • Spin again and repeat for a second water wash
    • With each wash, try to get as much supernatant out as possible(even use pipette) because don't want salts to interfere with the electrical pulse
  • Resuspend pellet with 50 µL of cold water
  • Add 1 ng of pKD42 to one of the tubes and 45 ng of pKD 42 to the other
  • Take all of the liquid in each tube and place in two separate cuvettes for electroporation
    • Make sure the electroporation machine is on the right setting (for the cuvettes we used today it was "Ec2")
    • Wipe off all water on the side of the cuvette
  • Have 1 mL of LB in hand and after pulsing, immediately put LB in cuvette
  • Transfer to culture tube and place in 30 C for 2 hours
  • Make 4 LB/amp plates and spread E. coli using glass beads:
    • Plate 1: 10 µL of 1 ng culture
    • Plate 2: take 700 µL of 1 ng culture, spin down and remove supernatant, resuspend in about 30 µL of LB and plate
    • Plate 3: 10 µL of 45 ng culture
    • Plate 4: take 700 µL of 45 ng culture, spin down and remove supernatant, resuspend in about 30 µL of LB and plate
  • Grow overnight at 30 C

PCR to confirm knockouts of selection strain

• this PCR was to confirm that the ΔHis3ΔPyrFΔrpoZ was indeed a knockout for the His3, PyrF, and rpoZ genes
• each primer set was used for two conditions: wild-type (we used a pKD42 culture) and knockout (ΔHis3ΔPyrFΔrpoZ culture, left over from transformation)
• 1 µL of either wt or ko template, diluted 1:20
• 12.5 µL Phusion master mix
• 1.25 µL of each 10µM primer:
  • test for His3:
    • 1)His3_F, His3_R
    • 2)His3_F, His3_internalR
  • test for PyrF:
    • 3)PyrF_F, PyrF_R
    • 4)PyrF_F, PyrF_internalR
  • test for rpoZ:
    • 5)rpoZ_F, rpoZ_R
    • 6)rpoZ_F, rpoZ_internalR
  • test for Zeocin (there are two primer sets because we don't know what orientation the Zeocin gene is in)
    • 7)Zeocin_R, rpoZ_F
    • 8)Zeocin_R, rpoZ_R
• ddH2O up to 25 µL
• Parameters:
  • 98 C for 5 min
  • 98 C for 10 sec
  • 65 C for 25 sec
  • 72 C for 45 sec
  • cycle 30 times
  • 72 C for 5 min
  • 4 C forever
• Results: ran PCR products out on 1% gel (see below). There were some nonspecific bands, but the PyrF and rpoZ genes do appear to be knocked out in the selection strain. His3, however, looks like it's still present--we'll test again to confirm.

June 16 - Bioinformatics

• Research Targets

1. Clinically relevant targets
2. Existing ZFs that bind under-represented triplets

Updating our programs

• Many of our current programs currently look at overall data or data based on specific DNA triplets (for example: 'GAT' or 'AAA'). However, in order to more easily understand some of the patterns that occur in the datasets, we want to examine broader subsets of data. For example, do different patterns appear when looking at fingers that bind to 'GNN' triplets versus 'NGN' triplets (where 'N' represents any of the 4 bases)?
  • We added the capability for our programs to accept inputs with the variable 'N' by using regular expressions.
    • We can now create lists of the zinc fingers that bind to any triplet, and create interaction matrices and frequency tables for any triplet input.