Gene expression profiling is a powerful approach that promotes a deeper understanding of the characteristics of cells at the transcriptional level and has broad implications for basic and clinical research. Historically, gene expression profiling has been performed on populations of cells, typically cell lysates, where observed expression levels represent an average of the unique expression states of each cell within the population. Such phenotypically similar populations can be purified in bulk by flow cytometry based cell sorting prior to RNA analysis. ^1,2

Much of cell research happens in the context of cultured or modified cells. More biologically relevant experiments can be done with blood. However, blood cannot entirely capture what takes place within a live organism. In their paper Futamura, et al. describes a method to study the movement and subsequent interactions of immune cells in live mice by flow cytometry.

Recent advances in genome editing and the application of fluorescent proteins have accelerated Interest in isolating specific populations of brain cells from mixed populations. Researchers are also using cell sorting to isolate single cells for expansion and analysis.

Placing several fluorescent proteins together in a flow cytometry panel offers greater power and capability for experiments. However, handling autofluorescent signal with fluorescent proteins is out of reach for conventional flow cytometetry users. Sony spectral flow cytometry analyzers enable researchers to harness up to five near infra-red fluorescent proteins in a single experiment. Moreover, spectral technology lets users accurately identify autofluorescence, and eliminate it if needed.

Bacteria, most notably the gut microbiome, have gained increased attention for their role in agriculture and human disease. However study of individual bacterium can be challenging since most bacteria do not grow under simple culture conditions. In a recent study, Blow, et al. have published a draft sequence of the bacteria, Candidatus Erwinia dacicola (Enterobacteriaceae). This bacteria has a symbiotic relationship with the Bactrocera oleae, also known as the olive fly. The larva of the olive fly grow in unripened olives leading to reduced crop yields. The larva has adapted to the special environment of the unripened olive with help from Candidatus Erwinia dacicola bacteria. Without bacteria the larva do not develop.

1. Purchase larger sizes of common antibodies on established fluorochromes. Packaging and shipping antibodies can be costly. Therefore smaller sizes typically cost greater than two times more compared to larger sizes.

Bacteria such as E. coli are popular model systems for engineering and production of modified proteins. Yet the idea of putting bacteria in a cell sorter conjures unwelcome images. Take heart, the Sony SH800 cell sorter, simplifies decontamination by quickly and easily letting researchers replace key components that come in contact with the sample. Here are some examples, and publication citations.

Listen to Dr. Jennifer Doudna, one of the discoverers of CRISPR systems discusses how the new genome engineering technology was discovered.

Video: Genome Engineering with CRISPR-Cas9: Birth of a Breakthrough Technology

Most commercially available antibodies contain small amounts of preservatives such as sodium azide to prevent microbial growth. However, sodium azide is also toxic to mammalian cells as it inhibits cellular respiration. Actual toxicity varies by cell type with neuronal cells being most sensitive. Toxicity is concentration, time, and temperature dependent. For most cell sorting experiments the health of cells are not impacted because the antibody is diluted and cells are typically incubated on ice for less than one hour.

Join us for a free webinar on Spectral Flow and FCS Express 6 which provides native support for Sony spectral data files. See how spectral flow cytometry delivers better data and simplifies panel design. In addition we’ll show how seamless integration between FCS Express and Sony spectral flow cytometry analyzers allows you to move quickly from acquisition to expanded data visualization with spectral overlays, tSNE, Spade, and plate based heat maps.