I am getting ready to start doing some cell counts. I have the Chinese improved nebular Haemocytometer. The only references I can find online for the proper way to do a count use the fancier triple line slide.
I am curious about which cells that lay on the perimeter to count.
Your picture is a tad confusing, but you should count the ones marked X, that are within the 4x4 square.
You need to decide what your cutoffs are, then count it the same way every time.
I was not sure what to do about the double line vs triple line.
Surely there is a SOP, otherwise me and you sharing a cell count would be pretty worthless. If I decided anything touching the line and you said anything 50% in, that could make a pretty huge difference . Or is it all within the margin of error anyway?
Seems to me that you would count cells touching the outer lines on the upper/left sides, but not count those touching the outer lines in the lower/right sides. However, I'm not a biologist and would never play one on TV.
I don't think it matters too much so long as you are consistent and the area you are counting is correct. That is, upper left/lower right whatever doesn't matter. It's the same as rounding numbers...you can use whatever system you like so long as you apply it consistently. There are varying conventions that people use (even/odd) but the most important thing is that it is unbiased and consistent.
Yes, taking into account ajdelange's advice about the "ruling" of the slide, and adjusting appropriately to use the inner or outer line as your limit.Basically, you are saying follow that 2nd image I posted and ignore the fact that there are only 2 lines instead of three.
There is also a pretty large margin of error, which can be reduced when more cells are counted.
It turns out this is very simple to quantify. The coefficient of variation (multiply by 100 to get percentage error) is simply 1/sqrt(number of cells you count). This if you count 1200 cells total your Cv is 2.88%. If you only count 300 it's twice this.
More details at http://www.wetnewf.org/pdfs/hemocytometer.html
A little acidic acid helps with un clumping the cells, but seems to make staining difficult. Glycine work well for declumping and seems to work better with stains.
I'm fighting that right now. I got a sample of 002 from a 60bbl conical. It is extremely thick and clumped worse than cottage cheese! Based on Kai's site I did the first dilution with wort. That seemed to help some, but after 20 minutes the cells were still clumping. I dropped a few grains of PBW into the tube and agitated. That solved the clumping issue immediately! But Kai says PBW interferes with staining.
I did the viability count with MB diluted with water, and the cell density count with a 5% acetic acid solution. (actually just distilled white vinegar)
I did the viability count with MB diluted with water, and the cell density count with a 5% acetic acid solution. (actually just distilled white vinegar)
Rough volume? Did you just do all your dilutions into vinegar instead of water?
Thanks for that. I didn't think of using vinegar.
Lab standard seems to be sulfuric acid but I'd like to avoid that.
Kai
AJ's statistical analysis is a good way to decide how many boxes to count. I also look at box to box standard deviation and make sure it is reasonable.
..keep in mind that dilutions and homogenization are also critical.
One thing that I have found recently is that a pipette can retain 5% of the previous sample clinging to it's walls. So if you wash your pipette and then pull a sample it could be 5% diluted.
One thing that I have found recently is that a pipette can retain 5% of the previous sample clinging to it's walls. So if you wash your pipette and then pull a sample it could be 5% diluted.
That's why you should rinse the pipette with the sample solution. In practice this means pulling in a sample, pushing out that sample and pulling in another sample.
Kai
That's why you should rinse the pipette with the sample solution. In practice this means pulling in a sample, pushing out that sample and pulling in another sample.
Kai
During a serial dilution, when I pipette my 1mL of sample into 10mL of diluent, should I then suck up some the diluted sample and rinse the pipette with it?
As a practical matter, generally how consistent are your counts?yes, you want all the the solution in the pipette to have the same cell density.
properly mixing the diluted sample is also important. But don't shake it and create lots of foam. Some yeast strains like to aggregate in the foam and you may end up removing cells from the suspension.
When counting you should at least fill both sides of the hemocytometer with different samples. If you mixed correctly both counts should be close. If not there is a problem. Others recommend to fill the hemocytometer three times and count 3 times.
Kai
The lady on YouTube said I should do that 3 times! (I'm having to get all my chem lab teachings from the internet as I had very little of it in school.)
One thing I am not quite sure on -
During a serial dilution, when I pipette my 1mL of sample into 10mL of diluent, should I then suck up some the diluted sample and rinse the pipette with it?
If you mixed correctly both counts should be close. If not there is a problem. Others recommend to fill the hemocytometer three times and count 3 times.
As a practical matter, generally how consistent are your counts?
1/sqrt(100) = 10%; 1/sqrt(300) = 5.77%. Ain't science grand.Sometime I just need a ball park number and might only count 100-300 cells. These have an average box to box standard deviation of 6%.
If I take my time and do everything right and count 500 cells or more the standard deviation is 3% on average.
That's called a 'bias error'. If I snuck into your lab and replaced your 0.0001 mL heomocytometer with one that had a volume of 0.00009 mL all your counts would be 10% low but your variances would be little changed.It is quite possible to have a very low standard deviation but have the numbers be way off. Recently I had some alcohol left in a tube from cleaning and didn't realize that it had not completely evaporated. My viability was much lower than expected.
It might have to do with some post processing of the data. I throw out the high and low of both the dead and live cell counts. The data includes 21 cell counts of more than 500 cells.
Remember that the mean isn't that robust an estimator. I'd say that if he has readings that are more than a couple of sigmas out he should toss them as the probability of getting a reading like that without some manipulation error like counting a square more than once, or not counting a square or doing a dilution wrong or waiting too long after pipetting before filling the slide (so that cells settle to the bottom of the pipet) is very small.
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