Single stressor leachate exposure summary

A 48 hour exposure to polyvinyl chloride (PVC) leachate and to aged polypropylene (PP) leachate

lab records
Author

Sarah Tanja

Published

May 3, 2024

This summary serves as a broad overview and notes of the acute (48hour) single stressor polyvinyl chloride (PVC) and polypropylene (PP) leachate exposure to Anthopleura elegantissima.

The following is a timeline overview of the experiment.

Note

Sample processing for Mitotic index, chlorophyll content, and DNA & RNA sequencing still have to be done!

This timeline was made using the vistime1 package

  • 1 Checkout the vistime package vignette here

    • Specimen collection & acclimation

    We collected anemones under Washington Dept. of Fish & Wildlife scientific collection permit Tanja-010 at Owens Beach Park in Tacoma on Monday March 18th and at Constellation Park in West Seattle on Saturday March 30th. After collection, each anemone was placed on a acid-washed 60mm glass petri dish to adhere and heal their pedal disc during an acclimation phase. All anemones were acclimated for at least 24 days in a recirculating seawater table at 10C prior to the start of the treatment exposure.

    Leachate preparation

    We prepared leachate for PVC (<500um) and for PP (aged) according to the leachate preparation protocol.

    In short, we created 1L artificial seawater using salt and deionized water, and adjusted the pH down from ~8.5 to 8.2 by slowly, iteratively, adding a very small amount of 0.1M hydrochloric acid (HCl) via a burette.

    Weighed out 41.953 grams of ASTM D1141-98 sea salt

    We then carefully measured out 250mg of each microplastic type, and added it to a dry flask.

    Initial pH was ~8.4, we lowered it to ~8.2 using 0.1M HCl

    After, we transferred 250mL of the pH-adjusted artifical seawater to each flask, set them in a shaker plate rotating at 90 rotations per minute, and left them to ‘shake and soak’ for 7 days.

    250mL of artificial seawater and 250mg of aged polypropylene microplastic. Note that this microplastic is buoyant.

    Flasks of seawater and microplastics were covered with foil to ensure no further photodegradation, and left to shake at 90rpm for 7 days

    After the 7 days were up, we filtered the microplastics from the seawater using 45micron filter paper.

    Here we can see the microplastics accumulating on the filter as the leachate passes through the funnel.

    Leachate filtration was a simple gravity filtration process and didn’t require the use of vacuum filtration.

    After the leachate was filtered, we put it on ice and transported it to a 4C fridge where it was stored for 48 hours prior to dilution and application to the anemones.

    Leachate dilution

    We performed a serial dilution on each prepared leachate to create leachate treatments that represent a mass of microplastic type to volume of water:

    • 100 mg/L
    • 10 mg/L
    • 1 mg/L
    • 0.1 mg/L
    • 0.01 mg/L

    For this we took 20mL of the 1000 mg/L leachate, and added it to 180mL of filtered seawater to make the 100mg/L concentration.

    We then serially diluted the remaining concentrations in a similar fashion.

    Exposure

    We exposed individual anemones to the leachate treatments for 48 hours in closed-systems. For this, we used 0.5 pint mason jars set in a recirculating seawater bath temperature-controlled by a heat exchanger and the Neptune Apex aquarium controller system.

    The water bath was kept at 10C throughout the exposure.

    Response measurements

    After 48 hours we measured:

    • Rapid Light Curves using a Walz Diving II PAM

    • 30 minutes of respirometry in the dark-adapted state (oxygen consumption, cellular respiration)

    • 30 minutes of respirometry in the light-saturated state (oxygen production, photosynthesis)

    • wet weight

    And then placed anemones in labelled 5mL centrifuge tubes and flash froze them in liquid-nitrogen

    Initial results

    # Install packages
if ("tidyverse" %in% rownames(installed.packages()) == 'FALSE') install.packages('tidyverse')
if ("dplyr" %in% rownames(installed.packages()) == 'FALSE') install.packages('dplyr')
if ("car" %in% rownames(installed.packages()) == 'FALSE') install.packages('car')

# Load packages
library(dplyr)
library(tidyverse)
library(car)
    Warning: package 'car' was built under R version 4.2.3
    Loading required package: carData
    Warning: package 'carData' was built under R version 4.2.3
    
Attaching package: 'car'
    The following object is masked from 'package:dplyr':

    recode
    The following object is masked from 'package:purrr':

    some
    rates <- read_csv('rates.csv')
    Rows: 55 Columns: 17
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr  (2): id, treatment
dbl (15): run, channel, auto_resp_rate, auto_resp_r2, resp_bg_adj.rate, resp...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

    Respiration

    First glimpse of data

    ggplot(rates) +
  aes(x = treatment, y = massnorm_resp_rate, color = treatment) +
  geom_jitter() +
  theme(legend.position = "none")

    Data normality

    resp_aov <-  aov(massnorm_resp_rate ~ treatment, data = rates)
    par(mfrow = c(1, 2)) # combine plots

# histogram
hist(resp_aov$residuals)

# QQ-plot
qqPlot(resp_aov$residuals,
  id = FALSE # id = FALSE to remove point identification
)

    Boxplot

    ggplot(rates) +
  aes(x = treatment, y = massnorm_resp_rate) +
  geom_boxplot() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

    ANOVA

    resp_aov <- aov(massnorm_resp_rate ~ treatment,
  data = rates
)

summary(resp_aov)
                Df    Sum Sq   Mean Sq F value Pr(>F)
treatment   10 5.268e-10 5.268e-11   1.302  0.259
Residuals   44 1.780e-09 4.045e-11

    Photosynthesis

    First glimpse of data

    ggplot(rates) +
  aes(x = treatment, y = massnorm_phot_rate, color = treatment) +
  geom_jitter() +
  theme(legend.position = "none")

    Data normality

    res_aov <-  aov(massnorm_phot_rate ~ treatment, data = rates)
    par(mfrow = c(1, 2)) # combine plots

# histogram
hist(res_aov$residuals)

# QQ-plot
qqPlot(res_aov$residuals,
  id = FALSE # id = FALSE to remove point identification
)

    Boxplot

    ggplot(rates) +
  aes(x = treatment, y = massnorm_phot_rate) +
  geom_boxplot() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

    ANOVA

    phot_aov <- aov(massnorm_phot_rate ~ treatment,
  data = rates
)

summary(phot_aov)
                Df    Sum Sq   Mean Sq F value Pr(>F)
treatment   10 1.433e-10 1.433e-11   1.355  0.233
Residuals   44 4.652e-10 1.057e-11

    Coming up next

    • Start the PAM Rapid Light Curve analysis

    • Extract RNA for gene expression of host anemone and symbiont dinoflagellate

    Gaps & improvements

    Important

    We still need to be able to take the background signature of our filtered seawater using C18 SPME fiber extractions, preserve the fibers, and send them to the Saliu Lab for analysis

    Note

    We are limited to short exposures because of the 48 hour window we have to work with fresh leachate. We can get around this by making leachate in batches and doing water changes every 48 hours, but we will need larger stocks of microplastic with which to make the leachate if we want to pursue this