The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of computational methods for identifying cell populations in multidimensional flow cytometry data. Here we report the results of FlowCAP-IV where algorithms from seven different research groups predicted the time to progression to AIDS among a cohort of 384 HIV+ subjects, using antigen-stimulated peripheral blood mononuclear cell (PBMC) samples analyzed with a 14-color staining panel. Two approaches (FlowReMi.1 and flowDensity-flowType-RchyOptimyx) provided statistically significant predictive value in the blinded test set. Manual validation of submitted results indicated that unbiased analysis of single cell phenotypes could reveal unexpected cell types that correlated with outcomes of interest in high dimensional flow cytometry datasets.
flow cytometry; bioinformatics; clustering; classification; data analysis; HIV; clinical outcome; supervised analysis
Flow cytometric analysis with multicolor fluoroprobes is an essential method for detecting biological signatures of cells. Here, we present a new full‐spectral flow cytometer (spectral‐FCM). Unlike conventional flow cytometer, this spectral‐FCM acquires the emitted fluorescence for all probes across the full‐spectrum from each cell with 32 channels sequential PMT unit after dispersion with prism, and extracts the signals of each fluoroprobe based on the spectral shape of each fluoroprobe using unique algorithm in high speed, high sensitive, accurate, automatic and real‐time. The spectral‐FCM detects the continuous changes in emission spectra from green to red of the photoconvertible protein, KikGR with high‐spectral resolution and separates spectrally‐adjacent fluoroprobes, such as FITC (Emission peak (Em) 519 nm) and EGFP (Em 507 nm). Moreover, the spectral‐FCM can measure and subtract autofluorescence of each cell providing increased signal‐to‐noise ratios and improved resolution of dim samples, which leads to a transformative technology for investigation of single cell state and function. These advances make it possible to perform 11‐color fluorescence analysis to visualize movement of multilinage immune cells by using KikGR‐expressing mice. Thus, the novel spectral flow cytometry improves the combinational use of spectrally‐adjacent various FPs and multicolor fluorochromes in metabolically active cell for the investigation of not only the immune system but also other research and clinical fields of use. © 2015 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. on behalf of ISAC
spectral flow cytometry; separation of spectrally‐adjacent fluoroprobes; photoconvertible fluorescent protein; immune cell movement
The quantitative expression of cell surface antigens and light scattering properties of five cellular reference populations in stressed bone marrow specimens were compared between pediatric and adult patients treated for acute myeloid leukemia (AML). The mean intensity of each antigen as well as the within patient and between patient variability showed striking consistency between the two different age groups. The only difference between the groups of specimens was the proportion of progenitor cells in the adult cohort averaged less than three times the proportion in the pediatric cohort. These data show that the amounts of gene products expressed on bone marrow cells are invariant with age. © 2016 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. on behalf of ISAC.
flow cytometry; bone marrow aspirates; adult; quantitative antigen expression; support vector machines
Five reference populations in bone marrow specimens were identified by flow cytometry using specific combinations of reagents in order define the variation of gene product expression intensities both within and between individuals. Mature lymphocytes, uncommitted progenitor cells, promyelocytes, mature monocytes and mature neutrophils can be reproducibly identified as distinct clusters of events in heterogeneous, maturing bone marrow specimens. Support Vector Machines were used to identify the reference populations in order to reduce subjective bias in manually defining boundaries of these populations since they were not discretely separated from the remainder of the cells. Reference populations were identified in 50 randomly selected bone marrow aspirates obtained over a period spanning 3 years and 6 months from pediatric patients following chemotherapy for acute myeloid leukemia (AML). The quantitative expression of gene products (cell surface antigens) and light scattering characteristics on these stressed specimens were demonstrated to be tightly regulated both within individuals and between individuals. Within an individual most gene products (CD45, CD34, CD14, CD16, CD64, CD33) demonstrated limited variability with a standard deviation of <0.20 log units while CD13 and CD36 exhibited broader variation >0.25 log units. Surprisingly, with the exception of CD33, the variation of the mean intensities of each antigen between individuals was even less than the variation within an individual. These data confirm that the amounts of gene products expressed on normal developing cells are highly regulated but differ in intensities between different lineages and during the maturational pathway of those lineages. The amounts of gene products expressed at specific stages of development of each lineage are a biologic constant with minimal variation within or between individuals. © 2016 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. on behalf of ISAC.
flow cytometry; bone marrow aspirates; quantitative antigen expression; support vector machines
Identification and quantification of maturing hematopoietic cell populations in flow cytometry data sets is a complex and sometimes irreproducible step in data analysis. Supervised machine learning algorithms present promise to automatically classify cells into populations, reducing subjective bias in data analysis. We describe the use of support vector machines (SVMs), a supervised algorithm, to reproducibly identify two distinctly different populations of normal hematopoietic cells, mature lymphocytes and uncommitted progenitor cells, in the challenging setting of pediatric bone marrow specimens obtained 1 month after chemotherapy. Four‐color flow cytometry data were collected on a FACS Calibur for 77 randomly selected postchemotherapy pediatric patients enrolled on the Children's Oncology Group clinical trial AAML1031. These patients demonstrated no evidence of detectable residual disease and were divided into training (n = 27) and testing (n = 50) cohorts. SVMs were trained to identify mature lymphocytes and uncommitted progenitor cells in the training cohort before independent evaluation of prediction efficiency in the testing cohort. Both SVMs demonstrated high predictive performance (lymphocyte SVM: sensitivity >0.99, specificity >0.99; uncommitted progenitor cell SVM: sensitivity = 0.94, specificity >0.99) and closely mirrored manual cell classifications by two expert‐analysts. SVMs present an efficient, automated methodology for identifying normal cell populations even in stressed bone marrows, replicating the performance of an expert while reducing the intrinsic bias of gating procedures between multiple analysts. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC.
flow cytometry; support vector machines; classification; lymphocytes; uncommitted progenitor cells; bone marrow
Compensation is a critical process for the unbiased analysis of flow cytometry data. Numerous compensation strategies exist, including the use of bead-based products. The purpose of this study was to determine whether beads, specifically polystyrene microspheres (PSMS) compare to the use of primary leukocytes for single color based compensation when conducting polychromatic flow cytometry. To do so, we stained individual tubes of both PSMS and leukocytes with panel specific antibodies conjugated to fluorochromes corresponding to fluorescent channels FL1-FL10. We compared the matrix generated by PSMS to that generated using peripheral blood mononuclear cells (PBMC). Ideal for compensation is a sample with a discrete negative and brightly positive population. We demonstrate that PSMS display autofluorescence properties similar to PBMC. When comparing PSMS to PBMC for compensation PSMS yielded more evenly distributed and discrete negative and positive populations to use for compensation. We analyzed three donors’ PBMC stained with our ten-color T cell subpopulation panel using compensation generated by PSMS vs. PBMC and detected no significant differences in the population distribution. Panel specific antibodies bound to PSMS represent an invaluable valid tool to generate suitable compensation matrices especially when sample material is limited and/or the sample requires analysis of dynamically modulated or rare events.
Compensation; Polystyrene Microspheres; Flow Cytometry; Immunophenotyping; Polychromatic; Beads; Leukocytes
Extracellular vesicles (EVs) range in size from 50 nm to 1 μm. Flow cytometry (FCM) is the most commonly used method for analyzing EVs; however, accurate characterization of EVs remains challenging due to their small size and lack of discrete positive populations. Here we report the use of optimization techniques that are especially well-suited for analyzing EVs from a high volume of clinical samples. Utilizing a two pronged approach that included 1) pre-filtration of antibodies to remove aggregates, followed by 2) detergent lysis of a replicate sample to account for remaining false positive events, we were able to effectively limit false positive non-EV events. In addition, we show that lysed samples are a useful alternative to isotypes for setting gates to exclude background fluorescence. To reduce background we developed an approach using filters to “wash” samples post-staining thus providing a faster alternative to ultracentrifugation and sucrose gradient fractionation. In conclusion, use of these optimized techniques enhances the accuracy and efficiency of EV detection using FCM.
microparticles; flow cytometry; antibody aggregates; filtration; extracellular vesicles
Microscopy is a fundamental technology driving new biological discoveries. Today microscopy allows a large number of images to be acquired using, for example, High Throughput Screening (HTS) and 4D imaging. It is essential to be able to interrogate these images and extract quantitative information in an automated fashion. In the context of neurobiology, it is important to automatically quantify the morphology of neurons in terms of neurite number, length, branching and complexity, etc. One major issue in quantification of neuronal morphology is the “crossover” problem where neurites cross and it is difficult to assign which neurite belongs to which cell body. In the present study, we provide a solution to the “crossover” problem, the software package NeuronCyto II. NeuronCyto II is an interactive and user‐friendly software package for automatic neurite quantification. It has a well‐designed graphical user interface (GUI) with only a few free parameters allowing users to optimize the software by themselves and extract relevant quantitative information routinely. Users are able to interact with the images and the numerical features through the Result Inspector. The processing of neurites without crossover was presented in our previous work. Our solution for the “crossover” problem is developed based on our recently published work with directed graph theory. Both methods are implemented in NeuronCyto II. The results show that our solution is able to significantly improve the reliability and accuracy of the neurons displaying “crossover.” NeuronCyto II is freely available at the website: https://sites.google.com/site/neuroncyto/
, which includes user support and where software upgrades will also be placed in the future. © 2016 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc. on behalf of ISAC.
neurite tracing; quantitative information; neurite outgrowth; software development; high throughput screening
Originally developed to study fundamental aspects of cellular biology, high‐content imaging (HCI) was rapidly adapted to study host–pathogen interactions at the cellular level and adopted as a technology of choice to unravel disease biology. HCI platforms allow for the visualization and quantification of discrete phenotypes that cannot be captured using classical screening approaches. A key advantage of high‐content screening technologies lies in the possibility to develop and interrogate physiologically significant, predictive ex vivo disease models that reproduce complex conditions relevant for infection. Here we review and discuss recent advances in HCI technologies and chemical biology approaches that are contributing to an increased understanding of the intricate host–pathogen interrelationship on the cellular level, and which will foster the development of novel therapeutic approaches for the treatment of human bacterial and protozoan infections. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC
drug discovery; antimicrobial; antiprotozoal; screening; hit identification; chemical biology
The cytokinesis‐block micronucleus (CBMN) assay is a well‐established technique that can be employed in triage radiation biodosimetry to estimate whole body doses of radiation to potentially exposed individuals through quantitation of the frequency of micronuclei (MN) in binucleated lymphocyte cells (BNCs). The assay has been partially automated using traditional microscope‐based methods and most recently has been modified for application on the ImageStreamX (ISX) imaging flow cytometer. This modification has allowed for a similar number of BNCs to be automatically scored as compared to traditional microscopy in a much shorter time period. However, the MN frequency measured was much lower than both manual and automated slide‐based methods of performing the assay. This work describes the optimized analysis template which implements newly developed functions in the IDEAS® data analysis software for the ISX that enhances specificity for BNCs and increases the frequency of scored MN. A new dose response calibration curve is presented in which the average rate of MN per BNC is of similar magnitude to those presented in the literature using automated CBMN slide scoring methods. In addition, dose estimates were generated for nine irradiated, blinded samples and were found to be within ±0.5 Gy of the delivered dose. Results demonstrate that the improved identification accuracy for MN and BNCs in the ISX‐based version of the CBMN assay will translate to increased accuracy when estimating unknown radiation doses received by exposed individuals following large‐scale radiological or nuclear emergencies. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC
cytokinesis‐block micronucleus assay; automated MN analysis; imaging flow cytometry; biodosimetry; population triage; ImageStreamX
An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen‐specific T‐cells from subject samples under different conditions. Antigen‐specific T‐cells compose a very small fraction of total T‐cells. Developments in cytometry technology over the past five years have enabled the measurement of single‐cells in a multivariate and high‐throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen‐specific T‐cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi‐dimensional cytometry datasets. However, the automated identification and visualization of rare, high‐dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen‐specific cell populations. By using OpenCyto to perform semi‐automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t‐SNE we are able to identify polyfunctional subpopulations of antigen‐specific T‐cells and visualize treatment‐specific differences between them. © 2015 The Authors. Published by Wiley Periodicals, Inc.
antigen‐specific T cells; automated gating; dimension reduction; intracellular cytokine staining; polyfunctionality; visualization
Clofazimine (CFZ) is an optically active, red-colored chemotherapeutic agent that is FDA – approved for the treatment of leprosy and is on the World Health Organization's list of essential medications. Interestingly, CFZ massively accumulates in macrophages where it forms crystal–like–drug inclusions (CLDIs) following oral administration of the drug in animals and humans. Analysis of the fluorescence spectra of CLDIs formed by resident tissue macrophages revealed that CFZ, when accumulated as CLDIs, undergoes a red shift in fluorescence excitation (from Ex:540-570 nm to Ex:560-600 nm) and emission (Em: 560-580 nm to Em: 640-700 nm) signal relative to the soluble and free-base crystal forms of CFZ. Using epifluorescence microscopy, CLDI(+) cells could be identified, relative to CLDI(−) cells, based on a >3-fold increment in mean fluorescence signal at excitation 640 nm and emission at 670 nm. Similarly, CLDI(+) cells could be identified by flow cytometry, based on a >100-fold increment in mean fluorescence signal using excitation lasers at 640 nm and emission detectors >600 nm. CLDI's fluorescence excitation and emission was orthogonal to that of cell viability dyes such as propidium iodide and DAPI, cellular staining dyes such as Hoechst 33342 (nucleus) and FM 1-43 (plasma membrane), as well as many other fluorescently-tagged antibodies used for immunophenotyping analyses. In vivo, >85% of CLDI(+) cells in the peritoneal exudate were F4/80(+) macrophages and >97% of CLDI(+) cells in the alveolar exudate were CD11c(+). Most importantly, the viability of cells was minimally affected by the presence of CLDIs. Accordingly, these results establish that CFZ fluorescence in CLDIs is suitable for quantitative flow cytometric phenotyping analysis and functional studies of xenobiotic sequestering macrophages.
CFZ; intracellular crystals; immunophenotyping; spectral microscopy
Harnessing mesenchymal stem cells for tissue repair underpins regenerative medicine. However, how the 3D tissue matrix maintains such cells in a quiescent state whilst at the same time primed to respond to tissue damage remains relatively unknown. Developing more physiologically relevant 3D models would allow us to better understand the matrix drivers and influence on cell‐lineage differentiation in situ. In this study, we have developed an ex vivo organotypic rat mandible slice model; a technically defined platform for the culture and characterization of dental pulp progenitor cells expressing GFP driven by the β‐actin promoter (cGFP DPPCs). Using confocal microscopy we have characterized how the native environment influences the progenitor cells transplanted into the dental pulp. Injected cGFP‐DPPCs were highly viable and furthermore differentially proliferated in unique regions of the mandible slice; in the dentine region, cGFP‐DPPCs showed a columnar morphology indicative of expansion and lineage differentiation. Hence, we demonstrated the systematic capacity for establishing a dental pulp cell‐micro‐community, phenotypically modified in the tooth (the “biology”); and at the same time addressed technical challenges enabling the mandible slice to be accessible on platforms for high‐content imaging (the biology in a “multiplex” format). © 2015 The Authors. Published by Wiley Periodicals, Inc.
mesenchymal stem cell; organ culture; high‐content imaging
The cytokine secretion assay identifies live cytokine-secreting cells by capturing the secreted cytokine on a surface-bound capture antibody in dilute suspension culture, followed by detection with a fluorescent anti-cytokine antibody. However, examining the kinetics of cytokine detection revealed that IL-2 staining reached a maximum at early times and then declined, whereas staining for other cytokines including IFNγ increased for up to 90 minutes. The decline in IL-2 staining could have been due to rapid cessation of cytokine synthesis, coupled with internalization of cytokine/antibody complexes from the cell surface. Consistent with this model, addition of the anti-IL-2 detection antibody during the cytokine secretion step resulted in higher and more sustained staining. This modified method enhanced staining of IL-2 and IL-4, but not IFNγ, TNFα or IL-5. However, the longer secretion times possible in the modified assay also improved detection of other cytokines in multi-cytokine combinations.
The lack of software interoperability with respect to gating has traditionally been a bottleneck preventing the use of multiple analytical tools and reproducibility of flow cytometry data analysis by independent parties. To address this issue, ISAC developed Gating-ML, a computer file format to encode and interchange gates. Gating-ML 1.5 was adopted and published as an ISAC Candidate Recommendation in 2008. Feedback during the probationary period from implementors, including major commercial software companies, instrument vendors and the wider community, has led to a streamlined Gating-ML 2.0. Gating-ML has been significantly simplified and therefore easier to support by software tools. To aid developers, free, open source reference implementations, compliance tests and detailed examples are provided to stimulate further commercial adoption. ISAC has approved Gating-ML as a standard ready for deployment in the public domain and encourages its support within the community as it is at a mature stage of development having undergone extensive review and testing, under both theoretical and practical conditions.
flow cytometry; bioinformatics; gating; data standard; file format
An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional sub-populations of antigen-specific T-cells and visualize treatment-specific differences between them.
Antigen-specific T cells; automated gating; dimension reduction; intracellular cytokine staining; polyfunctionality; visualization
A key feature of directed cell movement is the ability of cells to reorient quickly in response to changes in the direction of an extracellular stimulus. Mathematical models have suggested quite different regulatory mechanisms to explain reorientation, raising the question of how we can validate these models in a rigorous way. In this study, we fit three reaction—diffusion models to experimental data of Dictyostelium amoebae reorienting in response to alternating gradients of mechanical shear flow. The experimental readouts we use to fit are spatio-temporal distributions of a fluorescent reporter for cortical F-actin labeling the cell front. Experiments performed under different conditions are fitted simultaneously to challenge the models with different types of cellular dynamics. Although the model proposed by Otsuji is unable to provide a satisfactory fit, those suggested by Meinhardt and Levchenko fit equally well. Further, we show that reduction of the three-variable Meinhardt model to a two-variable model also provides an excellent fit, but has the advantage of all parameters being uniquely identifiable. Our work demonstrates that model selection and identifiability analysis, commonly applied to temporal dynamics problems in systems biology, can be a powerful tool when extended to spatio-temporal imaging data.
cell reorientation; Dictyostelium; actin; image based model fitting; spatio-temporal pattern formation; fluorescence microscopy; identifiability analysis
T-cell; Memory T-cell; Immune Checkpoint; PD-1; TIM3; LAG-3; CTLA4; Tumor-infiltrating Lymphocyte; TIL; Immunotherapy
Identifying homogenous sets of cell populations in flow cytometry is an important process for sorting and selecting populations of interests for further data acquisition and analysis. Many computational methods are now available to automate this process, with several algorithms partitioning cells based on high-dimensional separation versus the traditional pairwise two-dimensional visualization approach of manual gating. ISAC’s Classification Results File Format (CLR) was developed to exchange the results of both manual gating and algorithmic classification approaches in a standardized way based on per event based classifications, including the potential for soft classifications expressed as the probability of an event being a member of a class.
flow cytometry; classification; clustering; standard; software interoperability; file format; analysis interchange
In vivo optical imaging with near-infrared (NIR) probes is an established method of diagnostics in preclinical and clinical studies. However, the specificities of these probes are difficult to validate ex vivo due to the lack of NIR flow cytometry. To address this limitation, we modified a flow cytometer to include an additional NIR channel using a 752 nm laser line. The flow cytometry system was tested using NIR microspheres and cell lines labeled with a combination of visible range and NIR fluorescent dyes. The approach was verified in vivo in mice evaluated for immune response in lungs after intratracheal delivery of the NIR contrast agent. Flow cytometry of cells obtained from the lung bronchoalveolar lavage demonstrated that the NIR dye was taken up by pulmonary macrophages as early as four-hours post-injection. This combination of optical imaging with NIR flow cytometry extends the capability of imaging and enables complementation of in vivo imaging with cell-specific studies.
Near-infrared; in vivo imaging; flow cytometry; alveolar macrophage; lung imaging
The blood–brain barrier (BBB) is primarily comprised of brain microvascular endothelial cells (BMVEC) and astrocytes and serves as a physical and chemical barrier that separates the periphery from the brain. We describe a flow cytometric method using our in vitro model of the human BBB to characterize BMVEC surface junctional proteins critical for maintenance of barrier function, cell viability, and leukocyte adhesion. For this methodology, BMVEC are cocultured with astrocytes in a transwell tissue culture insert to establish the barrier, after which time the BBB are treated with specific agents, and the BMVEC collected for flow cytometric analyses. We use a standard and optimized method to recover the BMVEC from the coculture model that maintains junctional protein expression and cell viability. A novel leukocyte adhesion assay enables a quantitative analysis of peripheral blood mononuclear cell (PBMC) interactions with the BMVEC and can be used to assess the adhesion of many cell types to the BBB. Furthermore, this method enables the concomitant analysis of a large number of adhesion molecules and tight junction proteins on both the BMVEC and adherent PBMC under homeostatic and pathologic conditions. Flow cytometry is an extremely powerful tool, and this technique can also be applied to assess variables not performed in this study, including cell cycle progression, and calcium flux.
adhesion molecule; tight junction protein; brain microvascular endothelium; leukocyte–endothelial cell interaction; adhesion; flow cytometry
Deciphering the complex interactions between human and simian immunodeficiency viruses (HIV/SIV) and their host cells is crucial to the development of improved therapies and vaccines. Investigating these relationships has been complicated by the inability to directly analyze infected cells among freshly isolated peripheral blood lymphocytes. Here, we describe a method to detect cells productively infected with SIVmac239 ex vivo from the blood or lymph nodes by flow cytometry. Using this method, we show a close correlation between the frequency of productively infected cells in both sample type and the plasma viral load. We define that the minimum threshold for detecting productively infected cells in lymph nodes by flow cytometry requires a plasma virus concentration of ~2.5 × 104 vRNA copy Equivalents (Eq)/ml. Conversely, an approximately 2 logs higher plasma viral load is needed to detect productively infected cells in the peripheral blood. This novel protocol provides a direct analytical tool to assess interactions between SIV and host cells, which is of key importance to investigators in AIDS research.
SIV infected cells; flow cytometry; ex vivo detection
There is growing interest in the development of methods capable of non‐invasive characterization of stem cells prior to their use in cell‐based therapies. Raman spectroscopy has previously been used to detect biochemical changes commensurate with the osteogenic, cardiogenic, and neurogenic differentiation of stem cells. The aim of this study was to characterize the adipogenic differentiation of live adipose derived stem cells (ASCs) under aseptic conditions. ASCs were cultured in adipogenic or basal culture medium for 14 days in customized culture flasks containing quartz windows. Raman spectra were acquired every 3 days. Principal component analysis (PCA) was used to identify spectral changes in the cultures over time. Adipogenic differentiation was confirmed using quantitative reverse transcription polymerase chain reaction for the marker genes PPARγ and ADIPOQ and Oil red O staining performed. PCA demonstrated that lipid associated spectral features varied throughout ASC differentiation with the earliest detection of the lipid associated peak at 1,438 cm−1 after 3 days of induction. After 7 days of culture there were clear differences between the spectra acquired from ASCs in adipogenic or basal culture medium. No changes were observed in the spectra acquired from undifferentiated ASCs. Significant up‐regulation in the expression of both PPARγ and ADIPOQ genes (P < 0.001) was observed after 14 days of differentiation as was prominent Oil red O staining. However, the Raman sampling process resulted in weaker gene expression compared with ASCs that had not undergone Raman analysis. This study demonstrated that Raman spectroscopy can be used to detect biochemical changes associated with adipogenic differentiation in a non‐invasive and aseptic manner and that this can be achieved as early as three days into the differentiation process. © 2015 The Authors. Published by Wiley Periodicals, Inc. on behalf of the International Society for Advancement of Cytometry.
adipogenic differentiation; adipose derived stem cell; cell‐based therapy; non‐invasive characterization; principal component analysis; Raman spectroscopy
Purpose and Appropriate Sample Types
This panel was developed to assess antigen-specific T cells using peptide pools to various antigens of interest, although other types of antigens such as recombinant proteins or whole pathogens could be considered using different stimulation times. In addition to multiple functional markers, the panel includes differentiation markers and markers to assess follicular helper T cells and NK cells (Table 1). It was optimized using cryopreserved peripheral blood mononuclear cells (PBMC) from human immunodeficiency virus (HIV) uninfected and HIV infected adults with known cytomegalovirus (CMV) responses and it underwent assay qualification. The panel is being used to evaluate the responses to HIV and malaria vaccine candidates in adults and children from different geographic areas.
cytometry; human PBMC; T cells; TFH cells; NK cells; memory; intracellular cytokines