Abstract
Scientists naturally group liquids together when setting up experiments in the lab, whether that be samples or standards, or positive and negative controls. The ability to group liquids is supported in Synthace, but beyond just grouping liquids using a common name (or Tag in Synthace), liquids can also be partitioned and grouped via other properties. The Select element in Synthace allows you to select a subset of liquids from a list of liquids you have previously defined, using a distinguishing feature of the specific liquids, such as their position in the defined list, name, concentration, volume, sub-component names and concentrations or even a specific tag or metadata associated with the liquids.
This technical note outlines a workflow where liquids have been selected based on their concentration, then cherry picked to a new plate using a Hamilton Microlab STAR.
Materials and methods
Description of workflow executed
Within this workflow (Figure 1), there are 48 liquids where some contain water with a blue dye or 100 µM tartrazine as a defined sub-component. Liquids containing tartrazine are selected using the sub-component name tartrazine and 150 µl is aliquot into a new 96 well assay plate. This workflow could be useful if you have a subset of samples, containing a subcomponent of interest, that you would like to use for further experimentation or analysis downstream.
Figure 1: Aliquot workflow using Select to specify a subset of liquids to be aliquoted in Synthace. Workflow used to aliquot only tartrazine containing samples over three liquid handling devices.
In the example here, 24 of the samples contained the tartrazine sub-component and were randomly dispersed amongst the 24 samples with the blue dye on a 96-well plate. By easily selecting the liquids based on the subcomponent of interest the 24 samples with tartrazine were cherry picked and aliquot to an assay plate for measurement.
Figure 2. Execution Details Preview in Synthace. Users can simulate their workflows, preview and verify their experiments in silico prior to physical execution demonstrated here on the Hamilton Microlab STAR.
Results
Images were captured of the Sample and Target plates before and after cherry picking of the 24 samples containing the tartrazine sub-component (Figure 3). Before cherry-picking, the input plate has 48 liquid filled wells where a subset of liquids contains tartrazine (yellow) while the remaining liquids contain water with a blue dye to clearly distinguish between the 2 subsets. The other empty input 96-well plate will have the selected samples aliquot into it as part of the automation workflow (Figure 3A). After cherry picking, all samples containing the tartrazine sub-component were selected and aliquot to the target plate (Figure 3B).
Figure 3. Sample and Target plates at the beginning (A) and the end (B) of the executed workflow.
Conclusions
Synthace enables scientists to easily select a subset of samples from a larger list for full flexibility of how samples should be handled.
We demonstrate simple sample selection based on a liquids properties, in this example the presence of the sub-component tartrazine.
Automated liquid handling reduces repetitive tasks and increases precision, freeing up researchers’ time.
Downloads
Workflow
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