This time your samples are all coming from the same population of cultures, presumably all identical except that half of them were sampled at one time and half at the other time. All of the data points are linked by the fact that they were obtained from cultures from a common source. However, there is no special one to one correspondence between any one data point in one set and a unique data point in the other. There is no basis for a paired t test, so we must run a test for independent samples.
The assay itself is the variable in this example. If the assay was 100% accurate and reliable, we would only have needed to look at one sample from a given cell line, and maybe repeat it once. Even a highly significant difference should be considered a preliminary result until the experiment can be repeated successfully at least once or twice.
Recall case study #1, for which you measured body weights of two groups of 12 rats each after a year on a special medication. One of your rats died of natural causes during the study, leaving 11 animals in one group while you still had 12 animals in the other. Does this turn of events ruin the experiment? If you do conduct the analysis, how will you modify it, if at all?