Goals for March

Experimental Work

  • buy pipette tips to finish Matt George’s CS activity experiment
  • buy camera for flourescent scope
  • order 1 more CS kit
  • keep testing flourescent scope
  • optimize CS protocol for reducing pipette tips
  • Run BSA and CS on 72 of Matt’s samples
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Functional Annotation of P. Generosa transcriptome part 3

First Step: take merged data from geoduck transcriptomes and upload to R

countMatrix<-read.table(file="https://raw.githubusercontent.com/sr320/nb-2022/main/P_generosa/analyses/kallisto-0207.isoform.counts.matrix", header=TRUE, sep = '\t')
names(countMatrix)[1]<-"target_id"
head(countMatrix)

Second Step: take blast data and load

#load blast data, see blasting .sh file to see code (in GItHub)
blast_data<-read.table(file="https://gannet.fish.washington.edu/gigas/Panopea-generosa-uniprot_blastx.tab")
names(blast_data)[1]<-"target_id" #renamed to match countMATRIX data
names(blast_data)[2]<-"identifiers" #renamed to search in uniprot swiss prot

Third Step: merge blast data with geoduck transcriptome data

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CS script

Get Standardized protein concentration (ug/mL)

protein_test<-read.csv(file="/Users/oliviacattau/Documents/data/BSA_Nov22_mantle+gill.csv")
A<-protein_test$Absorbance...570..1.0s...A.
protein<-(A*2500)-1700 #from GLM standard equation
protein_test<-cbind(protein_test, protein)
protein_test<-protein_test[protein_test$protein >= 0,]
M1= subset(protein_test, protein_test$label=='M_1')
M2= subset(protein_test, protein_test$label=='M_2')
G1= subset(protein_test, protein_test$label=='G_1')
G2= subset(protein_test, protein_test$label=='G_2')
M_1<-mean(M1$protein)
M_2<-mean(M2$protein)
G_1<-mean(G1$protein)
G_2<-mean(G2$protein)
protein_list<-c(M_1, M_2, G_1, G_2)
tissue_label<-c("mantle_1", "mantle_2", "gill_1", "gill_2")
protein_content<-as.table(cbind(tissue_label, protein_list))
print(protein_content)

CS activity (nmol/min/uL)

CS_Nov22<-read.csv(file="/Users/oliviacattau/Documents/data/CS_Nov22.csv")
CS_Nov22<-CS_Nov22[!(CS_Nov22$Well=="B06" | CS_Nov22$Well=="B03"),]
A<-CS_Nov22$Absorbance...405..0.1s...A.
blank=subset(CS_Nov22, CS_Nov22$label==0)
zero<-mean(blank$A)
new_A<-A-0.0664 #subtract blank well
CS_Nov22<-cbind(CS_Nov22, new_A)
M1= subset(CS_Nov22, CS_Nov22$label=='m1')
M2= subset(CS_Nov22, CS_Nov22$label=='m2')
G1= subset(CS_Nov22, CS_Nov22$label=='g1')
G2= subset(CS_Nov22, CS_Nov22$label=='g2')
CS_tissue<-rbind(M1, M2, G1, G2)
#plot data
library(ggplot2)
GSH<-ggplot(data=CS_tissue)+geom_point(aes(x=as.factor(Time), y=new_A, color=label))+theme_bw()
GSH
time_0<-subset(CS_tissue,CS_tissue$Repeat==1)
time_30<-subset(CS_tissue, CS_tissue$Repeat==30)
time_0$delta<-time_30$new_A-time_0$new_A #delta OD to get GSH
standard_CS<-read.csv(file="/Users/oliviacattau/Documents/data/standard_curve_small.csv")
cs_model<-lm(standard_CS$New_A~(standard_CS$GSH.well))
summary(cs_model)
cs_equation<-paste("y=",coef(cs_model)[[1]], "+", coef(cs_model)[[2]], "*x")
cs_equation
time_0$nmol<-0.0753742256190483 + 0.0465124174107143*delta #equation from GSH standard curve
standard_cs_plot<-ggplot(data=standard_CS,(aes(x=New_A, y=GSH.well)))+geom_point()+geom_smooth(method="lm", se=FALSE, formula = y ~x)+xlab("OD")+ylab("GSH")+theme_bw()+stat_regline_equation(label.x=1, label.y=8)
standard_cs_plot
#get CS activity
B<-21*delta-0.73
V<-50 #uL
D<-1
time<-27 #min
SampleCSactivity<-B/(time*V)*D
time_0$CSactivity<-SampleCSactivity #(nmol/min/uL)

|tissue_label| OD (delta A)| GSH nmol| CSactivity (nmol/min/uL)| protein (ug/mL)| protein (ug/uL)| relative CS activity (nmol/min/ug)| |—|—|—|—|—|—|—| |mantle_1| 0.116| 1.706| 1.26E-03| 493.89| 0.493888889| 2.56E-03| |mantle_2| 0.527| 10.337| 7.66E-03| 89.17| 0.089166667| 8.59E-02| |gill_1| 0.216| 3.806| 2.82E-03| below range| NA| NA| |gill_2| 0.08| 0.95| 7.04E-04| 445.83| 0.445833333| 1.58E-03|

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Lab work Mondays

Check to see if BioRad bovine serum albumin (BSA) Protocol works with oyster tissue

link to BSA protocol

if it does, use the results from the assay run to calculate total protein concentration per sample (ug/mL)

I am going to want to use various dillutions of the samples so I can get the protein concentration in the linear range (<2000 ug/mL)

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Citrate Synthase test 2

CS Test #2

Ran the sample curve, background control and positive control for the CS kit on the spec in FTR. At 405um instead of 412um, the sample curve was uneffected by the slight change in wavelength. Monday I will run another test with oyster tissue to test the enzyme at 25C with the old machine.

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Citrate Synthase test

Citrate-Synthase (CS) Test Run #1 Today Matt George and I attempted to test out our CS protocol using the Varioscan spectrophotometer. The original settings on the machine was 1000 meaurements without any breaks, but at 25 seconds a measurement, that would mean the Variscan would have been running for 12.5 hours so I had to kill the scripts which deleted the data. I re-ran the machine 57 minutes later (20 minutes past the ideal time) with the new settings (30 measurements with 2 second breaks=12.5 minutes of samples) and captured the very end of the absorbance curve with the absorbance spectrum centered at 412um. Results from the first test run can be found here

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updates

The worst happened yesterday,

my precious Prius way violated at Safeway and they took my baby! (By baby I mean my Macbook air that I had since college) and my smartphone. For the last 48 hours I have been without a phone and I realized how I rely on my phone to authenticate my identity. I cannot log into my apple ID without a 2-factor authorization which is problem because without my phone I cannot restore my new laptop to it’s time machine back-up. Thankfully, I have an external hard drive that has all my college work on it but I didn’t back it up since I started at UW this spring. All my work is on GitHub but my computer is empty which means that I am starting over from scratch with Jupyter Notebook. Maybe it will be a good exercise going through installing homebrew and kallisto again, so I know how it works intuatively. I have been stuggling with understanding where the computer stores my files so this should be a good opportunity to “clean up” my work.

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Goals for August

August 2021 goals

-finish procedure for Citrate-Synthase Assay, start testing samples when the kit arrives -plan for next experiment with Steven on oyster breeding -catch up on all coding homework -watch the rest of the OLYMPICS for inspiration -think about TA positions for next school year -think about what classes I want to register for in the Autumn

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Last Day at Pt Whitney

End of an ERA

Today was the last day (Monday July 26th 2021) at Point Whitney working with Matt George (mngeorge@uw.edu) on oyster disections for his pacific oyster triploid temperature stress experiment.

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death becomes geoducks

Updates on Geoduck Project

On July 15th I went to the hatchery at Pt Whitney to check mortality for Matt George’s maturation control project. While I was there I also checked on the seasonal fertility of my geoducks -Results: I re-labeled the remaining 6 animals with with F or M (circled) to indicade Male or Female, and then I assigned them a letter A,B,C,D,E,F (underlined). In the case of animal F, it was a male so I gave it a number #6. -Fertility: I pulled a sample of the gonad with a syringe (non-fatally) and there was no ripe females and only a few males with active sperm. It is not the spawning season right now and these animals might have to overwinter at the hatchery to re-ripen for buoyancy experiment.

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July goals

Goals for July research 2021

First Project: lab work 2-3 days a week on the Pacific Oyster triploid temperature stress experiment #2 with Matt at Pt Whitney -So far I have been labeling oysters, measuring shell lengths, and feeding rate assays. Will eventually be in change of the citrate synthase assay as well.

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