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With the added emphasis on reproducibility, it is critical to look at every step where experiments can be improved. No single step makes an experiment more reproducible, rather it is a process, making changes at each stage that leads to reproducibility. Antibodies comprise a critical component that needs to be reviewed. As Bradbury et al. in a commentary in Nature pointed out, the global spending on antibodies is about $1.6 billion a year, and it is estimated about half of that money is spent on “bad” antibodies. This does not include the additional costs of wasted time and effort by the researcher using these bad antibodies. Using tools to identify the best reagent to use, considering a switch to recombinant antibodies, and properly validating reagents for use in an assay, are 3 steps that will improve the reproducibility of your experiments.

Dyes exist for the detection of everything from large nucleic acids to reactive oxygen species, and from lipid aggregates to small ions. Concentrations of physiologically important ions such as sodium, potassium, and calcium can be important indicators of health and disease. Calcium ions play an especially critical role in cellular signaling. As a signaling messenger, calcium is involved in everything from muscle contractions, to cell motility, to enzyme activity. Calcium experiments can be very informative, and with the advent of cheaper UV lasers, more and more researchers can use ratiometric measurements to evaluate the signaling processes in phenotypically defined populations.

Flow cytometry is designed to measure physical and biochemical characteristics of cells and cell-like particles using fluorescence. Fundamentally, any single-particle suspension (within a defined size range) can pass through the flow cytometer. Beads, for better or worse, are a sine qua non for the flow cytometrist. From quality control,to standardization, to compensation, there is a bead for every job. They are important — critical, even — for flow cytometry.

There is a lot of preparatory work that must be done before the first flow cytometry experiment can be attempted. Each step builds upon the previous one and extends where the assay is going. Be prepared for some trial and error in this process, and don’t expect perfect results the first time around. An educated user is a good user, and makes the SRL staff’s job that much easier. The partnership between investigator and SRL staff is a rewarding one, when both parties work together to achieve the ultimate goal of generating excellent data and sort results that help answer the biological question being tested.

Here, we cover 5 lessons from the trenches of flow cytometry looking at important aspects of how best practices have changed over time, which practices need to be adopted, and which are outdated. Put those old, coffee-stained protocols away and take advantage of the best practices for digital instruments to write new and improved ones (coffee stains optional). Your data will thank you.

You are probably familiar with the term, “doublet discrimination” or “doublet exclusion”, and have likely included this flow cytometry measurement into at least some (if not all) of your gating strategies. Even though you may utilize this important gating strategy, you may not have had the chance to delve deeper to explore exactly what doublets are and why it’s critical to exclude them. This article aims to give you insight on the what, why, and how of doublet discrimination.

For those working in the signaling field, having the ability to take a sample and phenotypically identify it, while knowing what is happening inside the cell to the target molecules of choice opens up a host of new opportunities. These assays are amenable to high throughput setup, meaning that biologically relevant outcomes in pre-clinical drug discovery can be measured directly. All told, with a little forethought, some careful planning and validation, and our helpful tips, phosphoflow assays are within your reach.

Flow cytometry is a numbers game. There are percentages of a population, fluorescence intensity measurements, sample averages, data normalization, and more. Many of these common calculations are useful, but surrounded by misconceptions. This primer will help you decide which calculation to use, when to use it, and how to interpret the results.

Measuring the receptor occupancy of a given target showcases the power of flow cytometry. With the right reagents, best practices, and attention to detail, this assay can become a mainstay in your research toolkit. It extends quantitative flow cytometry to the next level, to determine a complete biological picture of how efficiently a given target is being bound. This also serves as the basis for even more fine-analysis when combined with assessment of downstream targets that the engagement of the receptor by the target antibody may affect. Phosphorylation, cell cycle arrest, and protein expression are all within reach, resulting in an even more complete picture of the process, that will ultimately give the medical community a fuller understanding of how these potential therapeutics work and when to use them. This is truly personalized medicine at its fullest potential.

Some technological advances are incremental, while others are significant game-changing tools that offer the researcher the ability to significantly improve current assays while allowing for new and novel avenues of research to be performed. With speed, sensitivity, and capacity to spare, the ZE5 fits into the game-changing category. Reduced carryover, increased speed of acquisition, and a large number of parameters all open up new and novel assays while improving the quality and reproducibility of ongoing ones.

The ultimate goal of any experiment is to analyze data and determine whether it supports or disproves a given hypothesis. To do that, scientists turn to statistics. If we wish to compare either a single group to a theoretical hypothesis, or two different groups, and these groups are normally distributed, the test of choice is the Student’s t-Test. To perform the t-Test, it is critical to start from the beginning of the experiment to establish several parameters, including the type of test, the null hypothesis, the assumptions about the data, the number of samples to be analyzed (Power of the experiment), and the threshold. The experiments are performed, and only then, after the primary analysis is completed, is statistical testing performed.

One of the most common assays in flow cytometry is the surface labeling of cells with antibodies. Often termed “immunophenotyping”, it allows the researcher to identify, count, and isolate cells of interest in a mix of input cells. Every lab has their own favorite protocol to move from sample to cytometer, handed down from some hallowed, chemical-stained notebook, and followed as exactly as making a souffle. The real questions are, which of those steps are critical, and what other factors should be considered when staining cells? This article will focus on staining immune cells, but the principles apply in general, and specific issues for a specific sample type can be optimized in a similar way.