Determination of background, signal-to-noise, and dynamic range of a flow cytometer: A novel practical method for instrument characterization and standardization.

A well-defined scale calibration in flow cytometry can improve many aspects of data acquisition such as cytometer setup, instrument comparison and sample comparison. The theory for scale calibration was proposed by Steen over two decades ago, but it has never been put into regular use due to the lack of a widely available precision light source. The introduction of such a light source, the quantiFlashTM , gave this possibility. Here, we describe how this light source can be used to characterize a cytometer's PMT performance. We, therefore, characterized the instrument's response over the entire PMT voltage range. As a consequence, we propose a practical method to characterize a cytometer's signal-to-noise ratio (SNR) and dynamic range (DNR). This allows the selection of a voltage/gain corresponding to a PMT's maximum efficiency and hence the lowest electronic noise, which can help with experiment design. We further introduced a decibel (dB) scale for the presentation of SNR and DNR values. SNR and DNR are stand-alone values that allow the direct comparison of different instruments. Finally, with this method, it becomes clear that increased SNR comes at the expense of DNR and thus the limiting factor of modern cytometers is the DNR. © 2017 International Society for Advancement of Cytometry.

Multispectral flow cytometry: The consequences of increased light collection.

In recent years, multispectral flow cytometry systems have come to attention. They differ from conventional flow cytometers in two key ways: a multispectral flow cytometer collects the full spectral information at the single cell level and the detector configuration is fixed and not explicitly tuned to a particular staining panel. This brings about clear hardware advantages, as a closed system should be highly stable, and ease-of-use should be improved if used in conjunction with custom unmixing software. An open question remains: what are the benefits of multispectral over conventional flow cytometry in terms of sensitivity and resolution? To probe this, we use Q (detection efficiency) and B (background) values and develop a novel "multivariate population overlap factor" to characterize the cytometer performance. To verify the usefulness of our factor, we perform representative experiments and compare our overlap factor to Q and B. Finally, we conclude that the increased light collection of multispectral flow cytometry does indeed lead to increased sensitivity, an improved detection limit, and a higher resolution. © 2016 International Society for Advancement of Cytometry.

Cell population identification using fluorescence-minus-one controls with a one-class classifying algorithm.

MOTIVATION: The tried and true approach of flow cytometry data analysis is to manually gate on each biomarker separately, which is feasible for a small number of biomarkers, e.g. less than five. However, this rapidly becomes confusing as the number of biomarker increases. Furthermore, multivariate structure is not taken into account. Recently, automated gating algorithms have been implemented, all of which rely on unsupervised learning methodology. However, all unsupervised learning outputs suffer the same difficulties in validation in the absence of external knowledge, regardless of application domain. RESULTS: We present a new semi-automated algorithm for population discovery that is based on comparison to fluorescence-minus-one controls, thus transferring the problem into that of one-class classification, as opposed to being an unsupervised learning problem. The novel one-class classification algorithm is based on common principal components and can accommodate complex mixtures of multivariate densities. Computational time is short, and the simple nature of the calculations means the algorithm can easily be adapted to process large numbers of cells (10(6)). Furthermore, we are able to find rare cell populations as well as populations with low biomarker concentration, both of which are inherently hard to do in an unsupervised learning context without prior knowledge of the samples' composition. AVAILABILITY AND IMPLEMENTATION: R scripts are available via https://fccf.mpiib-berlin.mpg.de/daten/drfz/bioinformatics/with{username,password}={bioinformatics,Sar=Gac4}.

A UV-C LED-based unit for continuous decontamination of the sheath fluid in a flow-cytometric cell sorter.

Aseptic cell sorting is challenging, especially when a flow-cytometric cell sorter is not operated in a sterile environment. The sheath fluid system of a cell sorter may be contaminated with germs such as bacteria, yeasts, viruses, or fungi. Thus, a regular chemical cleaning procedure is required to prepare a sorter for aseptic cell sorting by flushing the fluidic system. However, this procedure is time consuming, and most importantly, the researcher can never be sure that the cleaning process was successful. Here we present a method in which the sheath fluid of a cell sorter was decontaminated by irradiation with UV-C light using a flow-through principle. Using this principle, we were able to achieve a 5 log reduction of bacteria in the sheath fluid.

Multi-angle pulse shape detection of scattered light in flow cytometry for label-free cell cycle classification.

Flow cytometers are robust and ubiquitous tools of biomedical research, as they enable high-throughput fluorescence-based multi-parametric analysis and sorting of single cells. However, analysis is often constrained by the availability of detection reagents or functional changes of cells caused by fluorescent staining. Here, we introduce MAPS-FC (multi-angle pulse shape flow cytometry), an approach that measures angle- and time-resolved scattered light for high-throughput cell characterization to circumvent the constraints of conventional flow cytometry. In order to derive cell-specific properties from the acquired pulse shapes, we developed a data analysis procedure based on wavelet transform and k-means clustering. We analyzed cell cycle stages of Jurkat and HEK293 cells by MAPS-FC and were able to assign cells to the G1, S, and G2/M phases without the need for fluorescent labeling. The results were validated by DNA staining and by sorting and re-analysis of isolated G1, S, and G2/M populations. Our results demonstrate that MAPS-FC can be used to determine cell properties that are otherwise only accessible by invasive labeling. This approach is technically compatible with conventional flow cytometers and paves the way for label-free cell sorting.

Primary Cell Culture of Purified GABAergic or Glutamatergic Neurons Established through Fluorescence-activated Cell Sorting.

The overall goal of this protocol is to generate purified neuronal cultures derived from either GABAergic or glutamatergic neurons. Purified neurons can be cultured in defined media for 16 days in vitro and are amenable to any analyses typically performed on dissociated cultures, including electrophysiological, morphological and survival analyses. The major advantage of these cultures is that specific cell types can be selectively studied in the absence of complex external influences, such as those arising from glial cells or other neuron types. When planning experiments with purified cells, however, it is important to note that neurons strongly depend on glia-conditioned media for their growth and survival. In addition, glutamatergic neurons further depend on glia-secreted factors for the establishment of synaptic transmission. We therefore also describe a method for co-culturing neurons and glial cells in a non-contact arrangement. Using these methods, we have identified major differences between the development of GABAergic and glutamatergic neuronal networks. Thus, studying cultures of purified neurons has great potential for furthering our understanding of how the nervous system develops and functions. Moreover, purified cultures may be useful for investigating the direct action of pharmacological agents, growth factors or for exploring the consequences of genetic manipulations on specific cell types. As more and more transgenic animals become available, labeling additional specific cell types of interest, we expect that the protocols described here will grow in their applicability and potential.

From transcriptome to cytome: integrating cytometric profiling, multivariate cluster, and prediction analyses for a phenotypical classification of inflammatory diseases.

Gene expression studies of peripheral blood cells in inflammatory diseases revealed a large array of new antigens as potential biomarkers useful for diagnosis, prognosis, and therapy stratification. Generally, their validation on the protein level remains mainly restricted to a more hypothesis-driven manner. State-of-the-art multicolor flow cytometry make it attractive to validate candidate genes at the protein and single cell level combined with a detailed immunophenotyping of blood cell subsets. We developed multicolor staining panels including up to 50 different monoclonal antibodies that allowed the assessment of several hundreds of phenotypical parameters in a few milliliters of peripheral blood. Up to 10 different surface antigens were measured simultaneously by the combination of seven different fluorescence colors. In a pilot study blood samples of ankylosing spondylitis (AS) patients were compared with normal donors (ND). A special focus was set on the establishment of suitable bioinformatic strategy for storing and analyzing hundreds of phenotypical parameters obtained from a single blood sample. We could establish a set of multicolor stainings that allowed monitoring of all major leukocyte populations and their corresponding subtypes in peripheral blood. In addition, antigens involved in complement and antibody binding, cell migration, and activation were acquired. The feasibility of our cytometric profiling approach was demonstrated by a successful classification of AS samples with a reduced subset of 80 statistically significant parameters, which are partially involved in antigen presentation and cell migration. Furthermore, these parameters allowed an error-free prediction of independent AS and ND samples originally not included for parameter selection. This study demonstrates a new level of multiparametric analysis in the post-transcriptomic era. The integration of an appropriate bioinformatic solution as presented here by the combination of a custom-made Access database along with cluster- and prediction-analysis tools predestine our approach to promote the human cytome project.

Rapidly maturing red fluorescent protein variants with strongly enhanced brightness in bacteria.

A rapidly maturing variant of the red fluorescent protein DsRed was optimized for bacterial expression by random mutagenesis. The brightest variant contains six mutations, two of which (S4T and a silent mutation in codon 2) explain most of the fluorescence enhancement. The novel variants are expressed at 9-60-fold higher levels in Escherichia coli compared to DsRed.T3, but are not superior fluorophores on a per molecule basis. In contrast to previously available DsRed variants, DsRed.T3_S4T is sufficiently bright to monitor Salmonella gene expression in infected animals using flow cytometry. However, no fluorescence enhancement was observed in Leishmania or HeLa cells, indicating that these novel variants are specifically useful for bacteria.

Differentiation-dependent and subset-specific recruitment of T-helper cells into murine liver.

It has been suggested that the liver traps and deletes activated and potentially harmful T cells, especially of the CD8(+) subset, providing mechanisms to limit systemic immune responses. It is unknown whether this also applies to CD4(+) T cells. In this study, we show that activated stages of CD4(+) T cells were trapped in the liver on intraportal injection. Intravital microscopy showed an immediate adhesion of activated CD4(+) T cells within periportal sinusoids after intraportal injection. Furthermore, we detected high frequencies of interferon gamma (IFN-gamma)-- (Th1) and interleukin 4 (IL-4)-- (Th2) synthesizing effector cells in the liver. Transfer experiments were performed to identify those phenotypes showing specific retention in the liver. Our data show that effector stages and activated cells in general are more efficiently recruited into the liver than resting CD4(+) T cells, similar to what has previously been shown for CD45RB(low) memory cells. In addition, we observed a certain preference for Th1-polarized cells to be trapped by the liver. However, the actual cytokine-producing cells did not specifically enrich among the total population. In conclusion, these data indicate that the liver acts as a filter for activated and memory/effector cells. Cells trapped in the liver might subsequently undergo modulatory influences exerted by the postulated specific microenvironment of the liver.