“What Have You Done To My Cells??!!!”

This cry of pain from researchers, frequently aimed at core facility operators, is heard after receiving incomprehensible data for an invaluable tube of cells. Equally baffling to the trained user of flow cytometric instrumentation is when data emerges that is either unreliable or inconsistent with the known properties of the biological cells that are being studied.

In many cases, the CICO (crap in, crap out) phenomenon may be at work!

CICO can operate at a number of levels.

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First level of CICO: the sample

The first and most important level is that of the sample. A flow cytometer can do no more than analyze what is present in the sample. For this reason, it is vital for the individual user of cytometric equipment to be intimately familiar with the biological behavior of the cells, before and after any imposed treatment.

Flushing out the first level

This is best dealt with through conventional light and fluorescence microscopy. It should be axiomatic for core facilities to have available these types of microscopes. The recent availability of fluorescence microscopes incorporating LED illumination is a particularly encouraging development since these are reliable, convenient, and cost-effective.

A peek at the sample with a microscope allows you to match visual analysis of cell suspensions with flow analyses. Bright-field illumination, with additional use of phase or interference contrast configurations, provides valuable information concerning:

• the proportion of cellular debris to intact cells
• the viability of the intact cells
• any unusual alterations in morphology (blebs, vacuoles, nuclear fragmentation, changes in cytoplasmic streaming, and so-on)

Any abnormalities noted by visual inspection can be taken into account when analyzing cells on the cytometer. For example, a cell suspension having large proportions of subcellular debris produces flow cytometric light scatter data having a correspondingly large proportion of events in low channel numbers. Automatic rescaling during accumulation can obscure relevant biodata in higher measurement channels. If you’ve noted the debris during visual inspection, then you can judiciously adjust discriminator settings to eliminate contributions from irrelevant debris.

A word of caution: when using a microscope to visually confirm fluorescently-labeled cells, make sure the cytometer and microscope have comparable fluorescence excitation/emission filters and light sources. Staining protocols should also be cross-validated, to the fullest extent possible, utilizing microscopy and appropriate cellular controls

If cell sorting is involved, re-analysis of the sorted subpopulations, by both microscopy and flow cytometry, will provide you with valuable confirmation of the effects of the sort itself.

In brief, get to know your sample, and be alert for any alterations to cellular structure that may reflect biologically-relevant change.

Second level of CICO: instrument configuration

It is extremely important to verify the properties and positions of the optical filters in all flow cytometric measurements. It is not widely appreciated that the optical properties of filters can degrade over time.

A number of additional factors can impact cellular viabilities and integrity in flow cytometry and cell sorting. These include:

• the composition of the medium in which the cell samples are suspended
• the composition of the sheath
• the temperature at which the cells are held prior to and during analysis
• the size of the flow tip relative to that of the cells
• various mechanical issues associated with the speed at which the sample passes through the instrumentation
• the deceleration experienced during collection after sorting
• the sizes of the cells relative to the dimensions of the functional parts (tubing, flow cell tip, etc.) of the flow instrumentation.

Flushing out the second level

Again, the microscope is an important tool in verifying filter positioning. You can cross-validate the performance of the flow cytometer to the observed patterns of fluorescence under the microscope. The amounts of fluorescence observed for each parameter, correcting for differences in illumination and detection efficiencies, should be consistent. Use of a scanning spectrophotometer to regularly monitor the transmission properties of optical filters is a good idea. Replacement OEM filters are not prohibitively expensive.

Third level of CICO: the unexpected

Unsuspected variables are a final complication in CICO. By their very nature, they are difficult to define and detect. One recent example relates to the requirement for pressurized sheath and sample in conventional jet-in-air flow sorters. Originally, this was achieved using pressurized nitrogen gas but this was switched to mechanical air compressors. Under these conditions, cells experience the stress of unnaturally high levels of oxygen during sorting. The extent to which this may significantly affect the results of downstream experiments remains to be determined across different cell types, tissues, organs, individuals and species. Another issue is that of repetition and replication: although flow cytometers, since they analyze large numbers of cells in populations provide robust within-sample statistics, achieving useful statistical power across samples requires analysis of multiple samples.

Flushing out the third level

You can’t plan for the unexpected, particularly since biology is a continuously emerging discipline. However, you can pay attention to the published literature, which can provide early warnings of potential new variables. Employing adequate sample sizes allows statistical analysis of the results emerging from the flow cytometric data, and can detect unsuspected variation for further study.

The bottom line: Be familiar with your cells, the instruments, and the variables. Be alert for unexpected changes. Remember, familiarity breeds contentment!

David Galbraith

David received his BA, MA and PhD degrees in Biochemistry from Cambridge University, and was a NATO Postdoctoral Fellow at Stanford University. He is Professor of Plant Sciences and Professor of Biomedical Engineering at the University of Arizona, and his research interests include biological instrumentation, developmental and tissue-specific gene expression in eukaryotes, functional genomics and proteomics, and issues in biodiversity.

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