Perfect Pipetting – Part 3

The return of glycerol

Aim

To assess the volume accuracy of SQWERTY transferring a high viscosity liquid against the manual options available.

Method

A solution of 75% glycerol (and a drop of red food dye) was prepared and used to transfer liquid using a Gilson single-channel P200 manual pipette, a Gilson P300 8-channel pipette and SQWERTY. All pipettes were calibrated and compatible 200 μL tips were used to transfer 180 μL liquid into a 96 multi-well plate (MWP) using forward pipetting (where the aspiration volume is equal to the dispense volume). This was done in triplicate. The weight change was calculated to estimate the average volume per well over the entire 96 MWP. The absorbance at 519 nm (most effective for red liquid) was measured with a BMG SpectroStar Nano spectrometer. The average absorbance decreases with lower volume and the standard deviation shows the consistency of volume transferred in each well (both calculated with MARS software).

Results

SQWERTY (before optimisation) delivered too high a volume, but was the most accurate and most consistent of the three methods of transferring 75% glycerol. The inaccuracy can be explained by the immersion depth being too high so glycerol adhered to the outside of the tip and formed droplets, ultimately increasing the overall volume dispensed. The single channel pipette delivered the lowest volume and was inconsistent between wells, but averaged out across the plates. The multi-channel pipette was the most inconsistent and inaccurate. Part of the reason for the large standard deviation in this pipette was that the middle two tips in replicate 2 under-aspirated at each transfer. However, even if replicate 2 were discounted from the data, the standard deviation would still be the widest (data not shown).

Further optimisation of glycerol transfer

For perfecting the delivery of glycerol, I made use of SQWERTY’s pipetting optimisation features:

• Liquid Level Detection & Liquid Level Tracking – allow SQWERTY to use automated pressure sensing to detect the surface of glycerol surface to minimise tip immersion depth 
• Liquid Classes – slow the flow rate and increase the dwell time to allow the glycerol enough time to be aspirated effectively. The flow rate that works best will vary depending on the conditions in your lab, e.g. temperature, humidity, stock solution concentration.
• Pre-wet Tip – coat the inside of the pipette tip prior to aspiration with glycerol and leave a residue to increase the accuracy of the ace less residue and so dispense a more accurate volume. 
• Eject Tip – do this often to prevent build up of too much residue on both the inside and the outside of the pipette tip, and to make the dispensing more accurate.

Conclusion

In summary, SQWERTY was a more consistent, more accurate option even BEFORE workflow optimisation. After optimisation, it just got even more accurate. The perfect workflow and liquid class will be unique to each lab. Fluid dynamics are affected by factors like humidity, temperature and altitude so even if the same workflow was run with the same settings and stock solution in two different labs, the accuracy results may differ slightly. 

Trial and error in settings optimisation is essential to SQWERTY users, but it makes it easy with ‘Interactive mode’. This mode is used to make quick adjustments to your settings and witness the results easily – no workflow design necessary.