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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