Difference between revisions of "Milk Creamatocrit"

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==Mouse Milk Creamatocrit (milk fat %)==
 
==Mouse Milk Creamatocrit (milk fat %)==
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This method is done to assess the total fat content of mouse milk. It does not differentiate between type of fat present. Additional information on mouse milk composition can be ascertained through triglyceride or cholesterol assay, or through lipidomics.
 
===Materials===
 
===Materials===
 
*Milk samples (from -80)
 
*Milk samples (from -80)
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* After the 8th spin, immediately read the creamatocrit using the calipers
 
* After the 8th spin, immediately read the creamatocrit using the calipers
 
===Reading the samples===
 
===Reading the samples===
* Measure to the nearest 0.01 inch the aqueous layer, the fat layer, and the small aqueous layer on top of the fat layer.  
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* Measure each of the 3 layers to the nearest 0.01 inch with the calipers. Record the number in the corresponding columns of [https://docs.google.com/spreadsheets/d/e/2PACX-1vTm1Zo5Cf9RTuw_uRwum8h_dOBb0mjc5HYcOHR1nBPHKbSzxlFqwYfJs0NMdChFHrczE_8sKCU3K9lp/pub?output=csv the spreadsheet](the aqueous layer(Aqueous.inches.1), the fat layer(Fat.inches), and the small aqueous layer on top of the fat layer(Aqueous.inches.2)).  
* Record results in a csv file.
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* Calculate the milk fat percentage using the following R code:
 
* Calculate the milk fat percentage using the following R code:
  
 
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  ```{r data-manipulation}
mutated.milk.data<-milk.data%>%
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  mutated.milk.data<-milk.data%>%
 
   group_by(replicate, MouseID, Genotype)%>%
 
   group_by(replicate, MouseID, Genotype)%>%
 
   mutate(fat = Fat.inches*25.4,
 
   mutate(fat = Fat.inches*25.4,
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   mutate(total.volume = water.corrected+fat)%>%
 
   mutate(total.volume = water.corrected+fat)%>%
 
   mutate(fat.percent = (fat/total.volume)*100)
 
   mutate(fat.percent = (fat/total.volume)*100)
 +
  ```

Latest revision as of 20:29, 18 March 2022

Mouse Milk Creamatocrit (milk fat %)

This method is done to assess the total fat content of mouse milk. It does not differentiate between type of fat present. Additional information on mouse milk composition can be ascertained through triglyceride or cholesterol assay, or through lipidomics.

Materials

  • Milk samples (from -80)
  • Ice bucket
  • CritSpin Micro-Hematocrit Spinner (from the Pennathur lab in Brehm tower)
  • 1XPBS + EDTA (50mL 1X PBS + 100uL 0.5M EDTA)
  • Untreated glass hematocrit tubes
  • Fractional dial calipers
  • Critoseal
  • Kimwipes
  • P10 pipette with tips

Preparing the samples

  1. Thaw whole milk on ice. To homogenize thawed milk, pipette up and down for five seconds. DO NOT shake!
  2. Dilute the milk in aa 1:3 solution with the 1XPBS + EDTA. Make enough for 4 capillary tubes
  3. Take capillary tube and draw in enough milk to fill ~3/4 of the tube (stop before the blue line)
  4. Hold horizontally and seal the other end of the tube with critoseal twice. Be sure to continue to hold the tube horizontally, or the milk will be ejected.
  5. Wipe excess milk from the tube with the kimwipe
  6. Each sample should be run in duplicate (you may need to run additional tubes if the variance between the first 2 sample results is >=25%)

Running samples

  • Place sealed and filled capillaries into the critspin micro-hematocrit spinner. The sealed end should point toward the outer edge of the centrifuge.
  • Record the position of each tube/sample before running..
  • Screw on the centrifuge cover so that it is secure, but not too difficult to loosen later.
  • Spin for 120 seconds, eight separate times. Between spins, the centrifuge will come to a complete stop on its own.
  • After the 8th spin, immediately read the creamatocrit using the calipers

Reading the samples

  • Measure each of the 3 layers to the nearest 0.01 inch with the calipers. Record the number in the corresponding columns of the spreadsheet(the aqueous layer(Aqueous.inches.1), the fat layer(Fat.inches), and the small aqueous layer on top of the fat layer(Aqueous.inches.2)).
  • Calculate the milk fat percentage using the following R code:
 ```{r data-manipulation}
 mutated.milk.data<-milk.data%>%
 group_by(replicate, MouseID, Genotype)%>%
 mutate(fat = Fat.inches*25.4,
        water = (Aqueous.inches.1 + Aqueous.inches.2)*25.4)%>%
 mutate(water.corrected = water/4)%>%
 mutate(total.volume = water.corrected+fat)%>%
 mutate(fat.percent = (fat/total.volume)*100)
 ```