Download Final Research Genetics

Melissa Peplinski and Jess Cosentino
I. Title: Analysis of Pseudo-nitzchia multiseries (Ps-n) gene expression of
phosphofructokinase (PFK) indicates a correlation between silicate levels in a
growth culture and extent of down regulation.
II. Abstract: An analysis of the expression of PFK in different growth environments
was done on growing cultures of Ps-n to provide insight into a relationship between
silicate levels and regulation of the gene. An initial sequence analysis of PFK was
generated to get a clear annotation of the gene. Primers were designed to target
sequences of cDNA during stationary and exponential growth phases of Ps-n.
Extractions of RNA and DNA from all cultures were done to test primers and
synthesize cDNA. PCR on each sample of DNA, RNA and cDNA showed strength of
primers and comparative sizes of each sample. Gel electrophoresis visualized the
results of all PCR reactions. Annealing curve analysis to optimize annealing
temperature for primers, as well as standard curve analysis to show efficiency and
reproducibility of the reactions indicated ideal conditions. Quantitative real timePCR was done to show gene expression of PFK, and presents information suggesting
that silicate plays a role in down regulation.
III. Introduction: Background and Significance:
i. Pseudo-nitzschia multiseries (Ps-n) is a marine diatom that produces a neurotoxin
called domoic acid (DA). The production of this toxin is minimal during the
exponential growth phase and increases during the stationary growth phase of the
diatom (Bates, 2006). The pennate diatom, Ps-n was responsible for poisoning
humans in the Prince Edward Island province of Canada, also known as “amnesic
shellfish poisoning.” Bates states that molluscan shellfish are the most common
vector for domoic acid transfer (2006). In response to this amnesic shellfish
poisoning, more in depth studies on the Ps-n, its genes, and the processes that
regulate domoic acid (DA) production have followed.
ii. Silicate Limitation: Early studies have consistently shown that silicate limitation
in the growth of the Ps-n leads to an increase in DA (Bates, 2006). Silicate limitation
may promote DA production by reducing the primary metabolic activity, leaving
more energy available and favoring the expression of genes involved in the
biosynthesis of this toxin (Pan, 1998). Also, in Si limitation, DNA synthesis and the
process of cell division are slowed presenting an ideal situation for DA production.
This experiment will show that as the severity of the Si limitation increases, there
will be a significant increase in DA production.
iii. To understand more about the mechanisms of DA production, more studies are
needed to explain the regulation of enzymes in the biosynthetic pathway. The
stopping of DNA synthesis by Si starvation is assumed to be caused by a decrease in
activity of the enzymes DNA polymerase(s), not because of a lack of energy or
precursors, (Pan, 1998). The decrease of DNA synthesis as a result of Si limitation
may arrest cells at a particular phase in the cell division cycle that is conducive to
DA production. The enzyme PPi-phosphofructokinase is an important piece of the
glycolysis pathway, the metabolic pathway responsible for ATP and NADPH, and the
down-regulation of this gene may suggest an alteration in energy metabolism
pathways in Ps-n cells as they transition from exponential growth to stationary
phase, (K.R. Boissonneault, 2004).
It is also important to note that the solutions used in this experiment will be nonaxenic, therefore containing bacteria. Studies show that bacteria plays an important
role in enhancing DA production by Ps-n; one hypothesis is that some bacteria
produce chelating agents (gluconic acid) that remove trace metals from use by Ps-n,
to counter this, Ps-n may produce its own chelator; domoic acid (Bates, 2006).
I am interested in PFK because it a key enzyme in glycolysis, and as an effect of
increased DA production, with a down regulation of PFK, the glycolic pathway must
be affected. In a silicate starved environment DA production will go up and we
would expect PFK to go down.
In articles written by Pan (1996 & 2006), and Bates (2006), it is clear that by
reducing the amount of Si present in the culture with Ps-n, DA production will
increase. I am very interested in the ways in which enzymes affect DA production as
well as their role in glycolysis and metabolic pathways. I hope that through this
experiment, by focusing on one enzyme, phosphofructokinase, we will be able to
better observe its direct relationship to Si limitation.
iv. The goal of this project is to determine if the enzyme phosphofructokinase is
down-regulated during Silicate limitation in Pseudo-nitzschia multiseries.
Aim 1: To test an increase in the down-regulation of the gene Phosphofructokinase
(PFK) in a Silicate limited environment compared to an f/2 environment.
Aim 2: To test an increase in domoic acid production in a silicate starved
environment when compared to an f/2 environment.
IV. Methods and Materials:
i. Bioinformatic/Sequence analysis;
To understand more about the gene PFK, BlastX was used to identify gene
sequences that were similar to that of PFK. BlastX is a tool that compares translated
DNA to known proteins of one gene to another to find similarities. I was able to find
three other closely related genes using this tool; PFP pyrophosphate dependent
phosphofructokinase, Phosphofructokinase, and Diphosphate-fructose-6-phosphate
1-phosphotransferase. I then used the ORF finder to observe any clear open reading
frames in my PFK sequence. I was able to find one clear ORF. I then blasted this clear
ORF against the conserved domain database and found that my gene was similar to
that of a PFK superfamily.
I then used BlastX to compare my PFK sequence against that of Thalassiosira
pseudonana. I was able to get one hit. I then used BlastX to compare my PFK
sequence against that of Phaeodactylum tricornutum. I was also able to get one hit.
I then took the Phaeo and Thal hits, and my original PFK sequence and aligned them
using the ClustalW interface.
ii. Primer design;
I reviewed the alignment, and looked for areas with the greatest similarities in all
three of the sequences. I was then able to hand-pick a set of primers to use in my
experiment. I also used the Oligoanalyzer (IDT) on the NCBI website to make sure
that my primers fit within specific parameters; melting temperature of 58-60
degrees Celsius, 18-24 bases in length each, 50-60% GS content, target sequence
length of 75-150 base pairs, should end in a C, G, CG or GC, and must be low in
hairpins, self-dimers and hetero-dimers. The original set of primers we chose were:
Forward Primer- GTG GCA TCC AAA CGA TTG CTT TCG
Reverse Primer- GTC CGA CGC CAA GAG AGT TTC AT
iii. Experimental set-up;
Nine polypropylene baffled flasks were used with the Ps-n culture CLNN21. Three of
the flasks contained CLNN21 in an f/2 culture. Three flasks contained CLNN21 in a
high Silicate culture. And three of the flasks contained CLNN21 in a Silicate limited
culture. The harvest for RNA happened twice during our experiment; once during
the exponential growth phase, and once during the stationary phase. Cell count and
domoic acid samples were taken six times throughout our experiment; every third
day starting with the day we inoculated our seawater. It is also important to note
that the cultures must be swirled three times a day. Also, the flasks were stored in
an incubator that is 16 degrees C and has continuous light.
0.45µm Filtered sterilized seawater was used from the UNH Experimental Dock in
Newcastle, NH. Nutrients added in F/2 concentrations (Guillard, 1962), except
silicate, which was added to each treatment as follows: High Silicate - 190µM, F/2
Silicate - 107µM and Low Silicate - 10µM.
Sampling:
Samples were taken on T0, T2, T3, T4, T5, T7, T9, T10 (RNA Harvests were on
T4/T10). T/4 date was February 19, 2010. T/10 date was February 25, 2010.
DA samples- 20ml of culture into a scintillation vial /froze at -20 degrees C.
Cell Count Samples- 4.75ml of sample preserved with 250µl of Formalin
(Formaldehyde /acetic acid). Cells counted using Sedgewick-Rafter technique.
The growth curve of all the plotted samples can be seen in Table 1.
iv. DNA Extraction;
In order to practice for RNA harvesting, and have DNA for primer testing in our
experiment, a DNA extraction from the PS-n culture CLNN16 was done. DNA
extraction protocol was followed using DNAzol to resuspend cells and then
centrifugation at 12,000g. The DNA was precipitated with 100% ethanol, and then
collected by centrifuging at 5,000g. The DNA pellet was washed and then
centrifuged at 5,000g, and then washed twice more with 75% ethanol.
Solubilization of the DNA was done and then diluted with TE and stored at -20
degrees Celsius. (Appendix 1)
v. RNA Extraction;
RNA was extracted from all of the 9 flasks. The RNA that we extracted (Flask #1 of
Silicate limited culture) was used to synthesize cDNA, as well as used in gel
electrophoresis. RNA extraction protocol was followed for each of the harvest;
therefore 2 different samples of RNA were taken. Trizol was used to resuspend cells
and centrifuged at 12,000g. After pooling of the aqueous phase, equal volume of
70% ethanol was added. RNA was transferred to a spin column and centrifuged at
12,000g. The RNA was buffered and centrifuged until RNA was dried and
transferred to a recovery tube. RNase-free water was added to spin column and
centrifuged at 12,000g. The RNA was separated into 3 tubes and stored at -80
degrees Celsius. (Appendix 2)
vi. UV Spectrophotometry
Samples of DNA and RNA from the extractions were used to get a measure of the
quantity and quality of product in each sample. Four samples of RNA and four
samples of DNA were spec’d. Protocol for UV Spectrophotometry was followed.
Spectrophotometry: Measure OD 260 and OD 280
OD 260 = 1 contains approximately 40 µg/ml RNA
OD 280 = 1 contains approximately 50 µg/ml DNA
OD260 : OD280 should be 1.8-2.0
vii. cDNA template synthesis from RNA
Unfortunately because the cell counts from our original experiment degraded, we
decided to use information from another experiment done by Brooks Henningsen
and Adam Labonte. (We became responsible for Hisi a 1 for harvest one and two).
Made 50µl cDNA reactions. Each contained: 10µl of iscript reaction mix (buffer,
dntps, Oligo dt primers, random hexamer primers), 2.5µl of Reverse Transcriptase,
85ng of RNA for each reaction: see table below. Reaction volume brought up to 50µl
with Rnase Free Water.
Harvest
1
Harvest
2
LoSiA
LoSiB
LoSiC
F/2A
F/2B
F/2C
HiSiA
HiSiB
HiSiC
LoSiA
LoSiB
LoSiC
F/2A
F/2B
F/2C
HiSiA
HiSiB
HiSiC
For HiSi A for harvest 1 on 2-19-2010, 17.5 µl of master mix, 3.1 µl of RNA and 29.4
µl of Rnase free water = 50 µl of solution.
For HiSi A for harvest 2 on 2-25-10, 17.5 µl of master mix, 1.2 µl of RNA and 31.3 µl
of Rnase free water = 50 µl of solution.
These two solutions were then put in to a Thermal Cycler at the following
conditions: 5 min at 25°C, 30min at 42°C, and then 5min at 85°C
The cDNA synthesis was done to measure the original amount of RNA in the
samples. We used this cDNA in PCR to test primers, and see if there was good
product.
viii. Primer Testing/RNA/ Genomic DNA/ cDNA testing/ PCR & Gel Electrophoresis
PCR reactions for my DNA and cDNA were used to test our primer sets. The original
DNA, control DNA and cDNA were all used in the reactions. The reactions that were
set up were are as follows,
Set-up:
cDNA 1- harvest 1, control primers
cDNA 2- harvest 2, control primers
control DNA- control primers
DNA- control primers
cDNA 1- harvest 1, new primers
cDNA 2- harvest 2, new primers
control DNA- new primers
DNA- new primers
The control primers we used were from PSN0100. Our new primers were also
designed from PSN0100.
For each of the PCR reactions, there was 16 µl of master mix, 1 µl of forward primer,
1 µl of reverse primer and 2 µl of template DNA or cDNA = 20 µl final volume
The PCR reaction conditions: 94°C, 2:00 min – Hot Start, 94°C, 0:30 sec – Denature,
61.1°C /59.7°C, 0:30 –Anneal, 72°C, 1:00 –Extend, Repeat Steps 2-4, 34 more times
– Cycle, 72°C, 10 min – Final Extension and 4°C, forever – Hold until recovery.
The PCR reactions were very helpful in figuring out if our newly designed primer
sets would work. Also, we wanted to make sure that there was product we could
work with in our cDNA. We were also able to compare the relative size of the cDNA
to the DNA to see if there were any introns present in the DNA (we were able to see
this in the Gel Electrophoresis).
RNA testing: PCR with RNA template
The purpose of doing PCR reactions on our extracted RNA was to test for genomic
contamination. We used the same control primers and new primers as we did in the
PCR on cDNA and DNA, as well as the same set up and reaction conditions.
RNA 1- from harvest 2-19-2010 (1), control primers
RNA 2-from harvest 2-25-2010 (2), control primers
RNA 1- harvest 1, new primers
RNA 2- harvest 2, new primers
Gel Electrophoresis
The purpose of agarose Gel Electrophoresis was to visualize the results of all the
PCR reactions. Gel Electrophoresis separates DNA and RNA molecules by size; this is
done by moving negatively charged nucleic acid molecules through an agarose
matrix with an electric field. The shorter (and smaller) the molecule the farther it
will move across the gel.
We first casted and prepared the gel. After it was completely solidified, we placed it
in the electrophoresis chamber. It was then covered with TAE buffer. The DNA
ladder was loaded into the first well, = 4 µl. I then skipped a well, and loaded my
solutions into the next 10 wells.
Set-up:
well 1 – DNA Ladder
well 2 – empty
well 3 – RNA 1A
well 4 - RNA 2A
well 5 - cDNA 1A
well 6 – cDNA 2A
well 7 – DNA, A
well 8 – Control DNA, A
well 9 – RNA 1B
well 10 – RNA 2B
well 11 – cDNA 1B
well 12 – cDNA 2B
Key: 1- harvest on 2-19-2010
2-harvest on 2-25-2010
A- Control Primer Set
B- New Primer Set (PSN0100)
In another Gel that I shared with classmates I had 2 more wells:
well 7 – DNA, B & well 8 Control DNA, B
My collaborator Jess’ Gel is on the top, and mine is on the bottom. We ran the Gel for
20 minutes at 130 volts. We then stained the Gel with Ethidium Bromide for 20
minutes. We then were able to look at our Gel through a UV box, and save it as a
picture (Picture 2&3).
ix. Gene Expression assay optimization:
1. Annealing Curve Analysis for Primers
Annealing curve analysis for primers was done to optimize the annealing
temperature and observe the PCR product. The qRT-PCR was done on a gradient
from 45 degrees Celsius to 65 degrees Celsius. On the well plate: primers, master
mix –SYBR green, Taq polymerase, buffers & dntps- template cDNA and water were
added in a volume total of 20 µl. The cycling protocol was followed; 95°C for
3minutes, 95°C for 10 seconds, Annealing Temp for 15 seconds, 72°C for 30 seconds.
A plate reading was taken after every cycle and repeated 39 times. Final extension at
72°C for 10 minutes. The qRT-PCR is used to quantify input nucleic acid by
measuring the number of cycles required to reach a set level of product. The SYBR
green binds to the DNA/cDNA and fluoresces.
2. Standard Curve Analysis
Standard Curve analysis was done to analyze the efficiency, specificity and
reproducibility of our overall reaction. The cDNA concentrations were done with a
serial dilution of Log 2. There were a total of 8 tubes for the serial dilution; the first
tube had 5 µl of cDNA. After the dilutions were done, they were put into an 8 well
plate as follows: 10 µl of SYBR master mix, 1 µl forward primer, 1 µl reverse primer,
6 µl of water and 2 µl of template cDNA. The cycle parameters were as follows; 95°C
for 3minutes, 95°C for 10 seconds, 61.6°C for 15 seconds, 72°C for 30 seconds, plate
read, repeat 39 more times, 72 °C for 10 minutes, Melt curve 65°C to 95°C:
increment 0.5°C for 5 seconds, plate read and then 4°C forever.
x. Gene Expression data analysis: Quantitative PCR
Quantitative PCR is done to compare expression between two data samples. The
control gene used was PSN0001; it has shown to be contiguously expressed in
previous experiments. The control gene was used to normalize the expressed gene.
In the 9 plates that we used, there were 2 solutions in each. For example in plate 1
on the left was f/2 A harvest 1 and on the right was Hi Si B harvest 2. Each solution
had three replicates; each well contained 0.75 µl of cDNA, and 9.25 µl of master mix
that included forward and reverse primers, SYBR green and water. There were a
total of 54 reactions for our primer set.
We lost all the data from plate 2; it included F/2 A harvest 1 and Low Si C Harvest 2.
We ended up only using 8 plates for our gene expression data. The cycle parameters
for the qPCR were the same as stated above for standard curve analysis.
V. Results:
i. Final Gene Annotation based on sequence analysis
After doing my initial blastx with PSN0100, my top three hits were all in the
category of phosphofructokinase. When I blasted the results of the ORF I found that
the conserved domain was also a PFK superfamily, and that the similar gene that
was found through blastp was pyrophosphate dependent phosphofructokinase.
When I did blastx against the Thal, I received one hit with significant alignments,
PFK2. When I did a blastx against the Phaeo, I received one hit with significant
alignments, Pyrophosphate dependent phosphofructokinase.
Therefore I would describe my gene as a Phosphofructokinase.
ii. Primer Sequences
The primers we decided would work best for the experiment were:
Forward Primer, highlighted yellow- CGA GGT GGC ATC CAA ACG ATT GC
Reverse Primer, highlighted green- GCA GCC TGT GTA TTG GTA TCG TCG
These primers were ordered from Integrated DNA technologies.
Forward Primer: Tm = 61.1 degrees Celsius
GC content = 56.5%
Reverse Primer: Tm = 59.7 degrees Celsius
GC content = 54.1%
iii. Alignment with Primers highlighted
CLUSTAL 2.0.12 multiple sequence alignment
PhaeoHit_estExt_Phatr1_ua_kg.C
TCCGAGCCTGACAAGCATCTTCTCCATTCGTTGCTTCTTGGTTTGAGAGA 50
ThalHit_estExt_fgenesh1_pg.C_c
-------------------------------------------------PSN0100
-------------------------TCATGGCGCATTGTGCTGGAAGTGA 25
PhaeoHit_estExt_Phatr1_ua_kg.C
100
ThalHit_estExt_fgenesh1_pg.C_c
PSN0100
CTGACACTTCCCATATTCAAACGTATATCTATCTATACACGTACCGACAG
PhaeoHit_estExt_Phatr1_ua_kg.C
150
ThalHit_estExt_fgenesh1_pg.C_c
PSN0100
125
TAAGACTACGACAACCTCAATCGACATCCACTCCTTCCTCTTTCCACCAT
PhaeoHit_estExt_Phatr1_ua_kg.C
200
ThalHit_estExt_fgenesh1_pg.C_c
PSN0100
161
GAGTCACCAAGCCAATGTACTGAAAGGCACGCACGTGAACGTCGCCATGA
-------------------------------------------------GTATTACGAAGTAATTTTTTGATATCGGTCTTTTCTCAATATCTAAGCAA 75
-------------------------------------------------AAAATCTACAATGGCTTCCAACGACTCAAGCGCCTACGTTCTCTCCCACT
------------------------ATGT-CGCACATGAACGTTGCCATGA 25
CATCCATTG--------------AGGGAAAGCACGTCAATGTCGGGATGA
*
PhaeoHit_estExt_Phatr1_ua_kg.C
250
ThalHit_estExt_fgenesh1_pg.C_c
**** * ** ** *
****
TGACTTCCGGAGGCCTCGCGCCCTGCCTGTCGTCCAGTATTGCGCAACTC
TGACCTCGGGAGGGTTGGCTCCATGTCTTTCCTCCTCCGTCGCCTACCTC 75
PSN0100
211
TGACCTCGGGTGGTCTCGCCCCTTGCCTTTCATCGTCGATCGCACAGCTT
**** ** ** **
PhaeoHit_estExt_Phatr1_ua_kg.C
300
ThalHit_estExt_fgenesh1_pg.C_c
125
PSN0100
261
TCGAAGTATTGGATTCAAGCATTGGCGGATGGGAAAATTTCAGGTTTAAC
***
**
***
** **
*** *
* ** **
* **
TTGTTGTCCC--CGAATCCGAATGG-GGGAACA-TGGAAAAGTTGAACTT
*
*
*
*
***
*
* *
***
GGTGGGAGGATCGCCCATTGGAAATTCGCGCGTCAAGCTGACGAACGTTG
GGTGGGAGT----CCTATTGGAAACTCTCGTGTCAAGCTCACCAACGTGA
CTTGGGAGGAAGTCCTATCGGTAATAGTCGAGTGAAGCTAACAAACCTGG
** ** ** **
** ** ***** ** *** *
CCGACTGCATTAAGAAGGGATACGTCCAACACGGCAGCACGCCCTTGGAA
AAGATTGCATGGCCCGTGGATTCGTGAAGGAAGGAGAGACTCCTCTCGAA
CAGATTGCGAAAAGAGAGGGTTCATCAAGCCTGGAGAAAATCCGCTCGAG
** * * *
*
**
*
**
* **
GTAGCTTCGCAGCAGCTCATCAAGGACCAAGTCCACGTCGTTCATACGAT
GTTGCTGCTCAACAACTCATCAAAGACAACATCAATGTCATTCACACCAT
GTGGCATCCAAACGATTGCTTTCGGATAACATTCACGTTTTGCACACAAT
*
* *
*
*
**
*
*
* **
* ** ** **
TGGCGGAGACGACACCAACACACAAGCTGCTACCCTTTCCGACTACCTGT
TGGAGGAGACGATACCAACACCCAAGCTGCCGAGTTGTCCAAGTACATTC
TGGTGGCGACGATACCAATACACAGGCTGCGGTTCTCTCAAAGTATCTTA
* **
* **
*
TGGAAAAGCACAATGGCAAAGTCGCCGTCATCGGTATGCCCAAGACCATC
TTGAAAAGCACGGAGGAAAGGTTGTCGTCGTTGGTATGCCAAAGACCATT
TGGACGAGCACAATGGAAGTGTCATCGTTATTGGCATGCCAAAGACTATC
* **
PhaeoHit_estExt_Phatr1_ua_kg.C
696
*
CCGTGATTTCTCCTGATATTTATGATGATTGTGCTTGTCTTCATGAGTTG
*** ** ***** ***** ** ** *****
PhaeoHit_estExt_Phatr1_ua_kg.C
646
ThalHit_estExt_fgenesh1_pg.C_c
471
PSN0100
607
*
TCGTCATTCC--CGAACATCAATGG-GATT-CACTCGACTCTCTGAATAC
** **
PhaeoHit_estExt_Phatr1_ua_kg.C
596
ThalHit_estExt_fgenesh1_pg.C_c
421
PSN0100
557
** ** **
TCTTCGCATGTATGTTGATGGTTATTCGGGAGTCTTGACAGGTCACTCAT
** ***
PhaeoHit_estExt_Phatr1_ua_kg.C
546
ThalHit_estExt_fgenesh1_pg.C_c
371
PSN0100
507
** ** *
TATCCGCATGTACTTTGATGGGTACAAGGGAGTTCTCACTGGAGATTCGA
******
PhaeoHit_estExt_Phatr1_ua_kg.C
496
ThalHit_estExt_fgenesh1_pg.C_c
321
PSN0100
457
* *
GCTCCGCATGTACCTTGGCGGGTACAAAGGAATGGTTACGGGAGATTCCA
**
PhaeoHit_estExt_Phatr1_ua_kg.C
446
ThalHit_estExt_fgenesh1_pg.C_c
271
PSN0100
407
* **
ATTGAGTTTTGGGCGCAGGCGTTGAAGGAAGGAAAGATCTCCGGCTTATC
* ********
PhaeoHit_estExt_Phatr1_ua_kg.C
396
ThalHit_estExt_fgenesh1_pg.C_c
225
PSN0100
357
* **
GCGCGCTGCTGGGTCCAGTCCTACCGCGAAGGAACCATCTCCGGTCTTAC
*
PhaeoHit_estExt_Phatr1_ua_kg.C
350
ThalHit_estExt_fgenesh1_pg.C_c
175
PSN0100
311
* ** ** ** ** ** **
*****
** *
**
***
* ** ***** ***** **
GACAACGATGTTTATCCTATTGTCCAGACCTTCGGAGCCGACACAGCTGC
ThalHit_estExt_fgenesh1_pg.C_c
521
PSN0100
657
GATAACGATGTTGTTCCCATCGTTCAGACTTTTGGAGCTGATACTGCCGC
GATAATGATGTCGTCCCTATTGCCCAAACTTTTGGTGCTGATACGGCCGC
** ** *****
PhaeoHit_estExt_Phatr1_ua_kg.C
746
ThalHit_estExt_fgenesh1_pg.C_c
571
PSN0100
707
** ** *
CGTACAGGGGGCACGATTTTTCGAGAACGTTGTCAATGAATGCACTGCCA
TGAACAGGGAGCCATCTTCTTTAAAAACGTCGTGAGTGAAAGTTCTGCCA
TCATCAAGGAGCAATCTTCTTTCAGAATGTTGTCAACGAATCGACTGCTA
** ** **
PhaeoHit_estExt_Phatr1_ua_kg.C
796
ThalHit_estExt_fgenesh1_pg.C_c
621
PSN0100
757
**** *
** * ** ***
***** ** ** *
** **
CTTACGGCCGCTACGGCACAGAAGTACCGCGACATTCTCAATGCC-CAAG
CTCACTGCTGCCACAGCGAGGAAGTACAGAGATTCCATTAAGGCTACCAA
TTGACGGCCAAGACCGCCAAATGCTATCGCGAT-CTTTTGGCCAAGCAAA
** **
**
* **
*
* *
ACTTGCCCGTCGGCTCGGACTTGCCCTTCCACCGCAAGTCTGCCCGCGAT
GTTTGT---TGGACCTGGATTCAC--TACTACCTCTA--CTTCTCGTGAC
ATTTAC---CCAGTTCTCTTTTCCCGAGCAACCAAAA---TTCTCGCGAT
*
*
* ***
*
* * ** **
ATTCACGCCATTTGGATTCCCGAACTCAAGCTAGACTTGGTCGCCGAGTC
ATTCACGCTGTTTGGATTCCTGAGGTGAACGTTAACATTGCTGAGGAAGG
GTGCATGCCATTTGGATTCCGGAACTGGAATTGGACCTGGTCGCTGAAGG
* ** **
PhaeoHit_estExt_Phatr1_ua_kg.C
995
ThalHit_estExt_fgenesh1_pg.C_c
814
PSN0100
913
***
ATCCTCGCATGCTTGTTTTACACGAGGTCATGGGTCGGGACTGCGGCTAT
**
PhaeoHit_estExt_Phatr1_ua_kg.C
945
ThalHit_estExt_fgenesh1_pg.C_c
764
PSN0100
900
* ** ** ** *
ACCCTCGTATGCTCATTATTCATGAGGTTATGGGACGTGACTCGGGATAC
* ** **
PhaeoHit_estExt_Phatr1_ua_kg.C
895
ThalHit_estExt_fgenesh1_pg.C_c
714
PSN0100
850
** **
ATCCTCGCATGCTTATTCTCCACGAGTGTATGGGACGCGATTCGGGATAC
* ***** *****
PhaeoHit_estExt_Phatr1_ua_kg.C
845
ThalHit_estExt_fgenesh1_pg.C_c
671
PSN0100
806
** ** ** ** ** ** ** ** **
********** **
*
*
*
** * *
*
**
GGCGCGTTTGAAGAAAGTCATGGACGAAGTCGGTTGCGTCAACATCTTTT
TGAACGTTTGAAGAAGGTTATGGATGATCATGGTTGTGTCAATGTCTTCC
AGCTCGTCTGAAG------------------------------------*
*** *****
PhaeoHit_estExt_Phatr1_ua_kg.C
1045
ThalHit_estExt_fgenesh1_pg.C_c
864
PSN0100
TCGGCGAGGGCACGGGCGTGCAGGAAATCGTCGCGGACATGGAGGCCAAC
PhaeoHit_estExt_Phatr1_ua_kg.C
1095
ThalHit_estExt_fgenesh1_pg.C_c
914
PSN0100
GGTGAAGCCGTGCCGCGCGATGCCTTTGGACACGTCACGTTGGCTAAAAT
PhaeoHit_estExt_Phatr1_ua_kg.C
1145
TCAGTGAGGGTGCTGGAGTGAAAGACATCGTTGCTGAGATGGAGGCCAAG
--------------------------------------------------
GGAGAGGAAGTTCCCCGTGATGCTTTTGGACATGTTAGTCTTGCAAAGAT
-------------------------------------------------CAATCCCGGACAGTACTTCTCCCAACACTTGGCGGACAATATTGGTGCCG
ThalHit_estExt_fgenesh1_pg.C_c
964
PSN0100
CAATCCTGGATTGTACTTCTCTAAGAATCTTGCCACTGCCGTCGGAGCCG
PhaeoHit_estExt_Phatr1_ua_kg.C
1195
ThalHit_estExt_fgenesh1_pg.C_c
1014
PSN0100
AAAAGACCATTGTGCAAAAGTCGGGATACTTTGCCCGTTCCGCCGCGGCC
PhaeoHit_estExt_Phatr1_ua_kg.C
1245
ThalHit_estExt_fgenesh1_pg.C_c
1064
PSN0100
AACGATTTCGATCGCCAACTCATCGGGGCCTGTGCCGAGGCTGGCGTCGC
PhaeoHit_estExt_Phatr1_ua_kg.C
1295
ThalHit_estExt_fgenesh1_pg.C_c
1114
PSN0100
CGCCGCTATTGACGGACATTCCGGATGCATGGGACAGGATGAAGACAAAC
PhaeoHit_estExt_Phatr1_ua_kg.C
1345
ThalHit_estExt_fgenesh1_pg.C_c
1164
PSN0100
CCAACACGCCCATTCGAGCGATTGAATTCAGTCGCATCAAGGGTGGCAAA
--------------------------------------------------
AGAAGACTCTTGTGCAGAAATCCGGATACTTTGCTCGTTCGGCTGCTTCG
--------------------------------------------------
AACGCCTTCGACCGCAAGTTGATCCGTGACTGTGCTGAGAAGGGAGTGGA
--------------------------------------------------
GAGTGCCATTGCTGGTGTTTCTGGATGCATGGGACAAGATGAGGCGAAGG
--------------------------------------------------
AGGGTACACCAATCAGAGCCATTGAGTTTGAGAGGATCAAGGGAGGAAAG
--------------------------------------------------
PhaeoHit_estExt_Phatr1_ua_kg.C
1395
ThalHit_estExt_fgenesh1_pg.C_c
1214
PSN0100
CCCTTTGATATTTCTCAGGAATGGTTCCAACAAATGCTCAAGGAAATTGG
PhaeoHit_estExt_Phatr1_ua_kg.C
1444
ThalHit_estExt_fgenesh1_pg.C_c
1263
PSN0100
ACAAGTGTAAAAAGGCGTGTATTCA-TCTTGCCCCGCTCCTTGATTGGAC
PhaeoHit_estExt_Phatr1_ua_kg.C
1493
ThalHit_estExt_fgenesh1_pg.C_c
1304
PSN0100
ATGGTGGTCAACTCGT-TGAAAAATATCTTCTATATTCAGAGACTTTGCC
PhaeoHit_estExt_Phatr1_ua_kg.C
1543
ThalHit_estExt_fgenesh1_pg.C_c
PSN0100
GTGTAAACAGTCGTTTCCGTACGTGATCCTTTCTTCCTTTAGCTTTACTA
PhaeoHit_estExt_Phatr1_ua_kg.C
ThalHit_estExt_fgenesh1_pg.C_c
PSN0100
AACGTCCGTAGGTAAAAAAAAGTTGTAGGTGCTGA 1578
---------------------------------------------------------------------
CCATTCAACCCTGAGCAGGCTTGGTTCCAGGAAATGCTCAAGGAGATTGG
--------------------------------------------------
ACAAGCCTAGATTGTTGATTATTGGGTGTTGCCGTAGTA-TTCTTTGTCA
--------------------------------------------------
GTAGTATCTAATCCAAATAGCGAATGAGAGAAGTGTTCGGC----------------------------------------------------------
---------------------------------------------------------------------------------------------------
iv. Primer/RNA/DNA/cDNA Testing results
When I used the control primers (wells 3-8) it was easy to see that the RNA was the
same size as the DNA, so there was genomic contamination. The cDNA was smaller
than the DNA; there may have been introns in the DNA. The control primers seemed
to work well; the darker single bands are evidence of this. The results from my new
primers (wells 9-12, and 7&8 on other Gel) were not as clear; the bands were much
lighter and hard to distinguish. There are different reasons that this could have
happened. The annealing temperature for the primers could have been too low or
there could have been non-specific priming or primer dimers. It was obvious that
the cDNA did have product when we used both the control and new primers.
Unfortunately though, the primers we designed did not work very well.
v. Annealing Temp analysis data
Based on the Tm for our designed primers we expected the best annealing
temperature to be close to 61.1 °C because our forward primer has a higher GC
content than the reverse. The best annealing temperature based on our melting
curve analysis was 61.6°C. This was the best annealing temperature because in well
C on our plate, that had the annealing temperature of 61.6°C on the gradient, we got
one product, the most product and the least primer dimers. This was visualized in
the melting curve analysis. The annealing temp analysis with melting curve can be
seen in table 4.
vi. Standard Curve analysis data
In standard curve analysis the Ct values of the eight serial dilutions were plotted on
a graph. We expected the Ct value to increase by 1 for every 1:2 dilution, with an
expected slope of -1. Our efficiency was 112.3%, and the R² value was 0.9916. The
graph and figures can be seen in Table 5. Because the R² value was very close to 1,
there wasn’t much scatter around the data. The slope was -0.9207, which is close to
-1. The error in efficiency might have to do with the qPCR reaction itself not being
optimized. I don’t believe that the error came from pipeting.
vii. Gene Expression data
Well
F06
F12
F12
F12
F06
F12
SYBR
SYBR
SYBR
SYBR
SYBR
SYBR
Unkn
Unkn
Unkn
Unkn
Unkn
Unkn
cDNA
F/2C (1)
HiSiC (1)
LoSiC (1)
F/2C (2)
HiSiC (2)
LowSiB(2)
Ave.
Gene
C(t)
Stdev
% Error harvest
cDNA
PSN0100(bmh) 22.4733 0.13614 0.60577
1 F/2C
PSN0100(bmh)
25.49 0.38691 1.51789
1 HiSiC
PSN0100(bmh) 20.9067 0.44377 2.12263
1 LoSiC
PSN0100(bmh) 24.0333 0.14572 0.60631
2 F/2C
PSN0100(bmh)
20.29 0.0755 0.3721
2 HiSiC
PSN0100(bmh)
34.76 0.13748 0.3955
2 LowSiB(2)
F/2C
HiSiC
LoSiC
F/2C
HiSiC
LowSiB(2)
PSNOOO1
20.30
21.92
17.46
18.56
17.35
28.04
Ave. Delta
%
Ct
Stdev
Stdev
2.38
1.31 55.13
3.14
0.80 25.58
3.08
0.42 13.65
4.52
1.34 29.60
3.60
0.76 20.97
6.21
0.73 11.69
Harvest 1
vs. 2
0.23
0.72
0.11
Hi vs.
F/2
Hi vs.
Lo
1.69
F/2 vs.
Lo
0.61
1.04
0.31
0.53
0.16
To normalize the gene PSN0100, we subtracted the average Ct value of PSN0001
from the average Ct value of PSN0100 to get the Average Delta Ct. The average delta
Ct was used to calculate the fold change values between different samples. The fold
change indicates how much more or less the gene is regulated between two
samples.
Harvest 1 was exponential growth and harvest 2 was stationary growth.
Lo Si
f/2
Hi Si
Harvest
1
Harvest
2
H1
vs.H2
9.09
4.3
(1.38)
Hi Si vs.
F/2
Hi Si vs.
Lo Si
F/2 vs.
Lo Si
(1.7)
(1.04)
(1.6)
(1.89)
6.1
3.23
In stationary growth, in a Low silicate environment, where domoic acid growth is
high, PFK is down regulated the most compared with f/2 and high silicate during
stationary growth. In harvest 2 Low silicate is down regulated 6.1 times more than it
is in high silicate harvest 2. Also when compared to F/2 in harvest 2, Low silicate is
down regulated 3.23 times more. And finally, when Hi Silicate in harvest 2 is
compared to F/2 in harvest 2, F/2 is down regulated 1.89 more times (this number
is not very significant < 3 but helps our analysis). In harvest 1, where Ps-n is in
exponential growth, and high amounts of Domoic acid are not being produced, the
down regulation of PFK is very similar across all treatments. Also, this further
supports the idea that harvest 1 is indeed still in exponential growth.
VI. Discussion
The gene expression data supports our hypothesis that there is an increase in down
regulation of PFK in a silicate starved environment when compared to an F/2
environment. In a growth environment with low silicate, and high domoic acid
production, PFK was the most down regulated. Assuming that domoic acid
production correlated with the Si-limited culture based on other studies, PFK could
be used as marker of domoic acid production. In order to further support this,
another experiment done with different limitations in cultures should be done. For
instance, setting up an experiment with copper toxic and limited cultures would
determine if PFK is in fact a marker of domoic acid production, or if it is correlated
with just a silicate limited environment.
IV. Bibliography
Bates SS, Trainer VL (2006). The Ecology of Harmful Diatoms, Ecological Studies
189: 81-93
Boissonneault, KR 2004 Gene discovery and expression profiling in the toxinproducing marine diatom,
Pseudo-nitzschia multiseries (Hasle) Hasle. PhD Thesis, Massachusetts Inst Technol,
Cambridge,
MA, USA, 181 pp
Guillard RRL, Ryther GH (1962). Studies of marine planktonic
diatoms I. Cyclotella nana Hustedt, and Detonula confervcea
(Cleve) Gran. Can J Microbiol 8:229–239.
Maldonado, Maria T, Hughes, M.P., Eden, R., and Wells, M.L. The Effect of Fe and Cu
on Growth and Domoic Acid Production by Pseudo-nitzschia multiseries and Pseudonitzschia australis. Limnology and Oceanography, Vol. 47, No. 2 (Mar., 2002), pp.
515-526 ,American Society of Limnology and Oceanography
Pan Y,Bates SS,Cembella AD (1998). Environmental stress and domoic acid
production by Pseudo-nitzschia: a physiological perspective. Natural Toxins 6:127–
135
Pan Y, Subba Rao DV, Mann KH, Brown RG, Pocklington R (1996a).
Effects of silicate limitation on production of domoic acid, a neurotoxin, by the
diatom Pseudo-nitzschia multiseries (Hasle). I. Batch culture studies. Mar Ecol Prog
Ser 131:225–233.
VIII. Acknowledgements: Brooks Henningsen, Adam LaBonte, Mallory Chaput, Jess
Consentino, Andrew Fryslie, Victoria Giron, Kristen Lamarre, Melissa Peplinski,
Liam O’Donnell, Tim Ryan, Matt Sebas, Bill Bedrin, Dylan Jackson,
Rebecca Mailhot, Molly Maloney, Scott Roberts, Elise Starowicz, David Tardif, Matt
Terry, Casey Van Vliet, Nate Weaver, Kate Worthen, Katie Rose Boissonneault
Appendix
1. Plant DNAzol: The plants DNAzol procedure is based on the use of a novel
guanidine-detergent lysing solution which hydrolyzes RNA and allows selective
precipitation of DNA from the lysate. The plant DNAzol protocol is fast and permits
efficient isolation of genomic DNA from a variety of plant tissues. In the plant
DNAzol procedure, plant samples are homogenized, and genomic DNA is extracted
from the homogenate with plant DNAzol. Following extraction, plant debris is
removed by centrifugation and DNA is precipitated from the supernatant with
ethanol. The resulting DNA pellet is washed with ethanol and solubilized in water or
TE (Tris-EDTA buffer). The entire procedure should be completed in ~60 minutes
and the isolated DNA can be used for Southern Analysis, dot blot hybridization,
molecular cloning, PCR, molecular mapping, and other biology and biotechnology
applications (KRB, 2010).
2. Trizol: Trizol is a ready-to-use reagent for the isolation of total RNA from cells and
tissues. The reagent, a mono-phasic solution of phenol and guanidine
isothiocyanate, is an improvement to the single-step RNA isolation method
developed by Chomczynski and Sacchi (1). During sample homogenization or lysis,
Trizol reagent maintains the integrity of the RNA, while disrupting cells and
dissolving cell components. Addition of chloroform followed by centrifugation,
separates the solution into and aqueous phase and an organic phase. RNA remains
exclusively in the aqueous phase. After transfer of the aqueous phase, the RNA is
recovered by precipitation with isopropyl alcohol (or ethanol) (KRB, 2010).
1. Chomczynski, P., and Sacchi, N. (1987) Anal. Biochem. 162, 156.
Tables and Pictures
1. Growth Curve
Silicate Experiment Growth Curves
1000000
Cells/ml
100000
10000
Low Si
1000
F/2
100
Hi Si
0
2
4
6
8
10
12
Days
(Harvests were on days 4 and 10)
The above values are the averages of the three replicates for each treatment
(standard deviations are absent).
2. Gel Electrophoresis Picture 1, Jess and Melissa
3. Gel Electrophoresis Picture 2, Group
4. Annealing Temperature Analysis with Melting Curve
(Double Click to see whole document).
5. Standard Curve Analysis Figures and Graph
Relative cDNA concentration
1.00000
0.50000
Log2 (Relative cDNA concentration)
0.00000
-1.00000
Ct values, Column 5
21.86
22.69
0.25000
0.12500
0.06250
0.03125
0.01563
0.00781
-2.00000
-3.00000
-4.00000
-5.00000
-6.00000
-7.00000
23.4
24.13
25.11
26.22
27.1
28.41
Standard Curve Analysis, Column 5
y = -0.9207x + 21.643
30
29
28
27
26
25
24
23
22
21
20
R² = 0.9916
Efficiency = (2(-1/slope) -1)*100 = 112.3%
0.00
-1.00
-2.00
-3.00
-4.00
-5.00
-6.00
-7.00
Log2 (Relative cDNA Concentration)
Ct value