Dataset Information

Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry.

ABSTRACT: Adaptive immune responses are complex dynamic processes whereby B and T cells undergo division and differentiation triggered by pathogenic stimuli. Deregulation of the response can lead to severe consequences for the host organism ranging from immune deficiencies to autoimmunity. Tracking cell division and differentiation by flow cytometry using fluorescent probes is a major method for measuring progression of lymphocyte responses, both in vitro and in vivo. In turn, mathematical modeling of cell numbers derived from such measurements has led to significant biological discoveries, and plays an increasingly important role in lymphocyte research. Fitting an appropriate parameterized model to such data is the goal of these studies but significant challenges are presented by the variability in measurements. This variation results from the sum of experimental noise and intrinsic probabilistic differences in cells and is difficult to characterize analytically. Current model fitting methods adopt different simplifying assumptions to describe the distribution of such measurements and these assumptions have not been tested directly. To help inform the choice and application of appropriate methods of model fitting to such data we studied the errors associated with flow cytometry measurements from a wide variety of experiments. We found that the mean and variance of the noise were related by a power law with an exponent between 1.3 and 1.8 for different datasets. This violated the assumptions inherent to commonly used least squares, linear variance scaling and log-transformation based methods. As a result of these findings we propose a new measurement model that we justify both theoretically, from the maximum entropy standpoint, and empirically using collected data. Our evaluation suggests that the new model can be reliably used for model fitting across a variety of conditions. Our work provides a foundation for modeling measurements in flow cytometry experiments thus facilitating progress in quantitative studies of lymphocyte responses.

SUBMITTER: Kan A

PROVIDER: S-EPMC4704825 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry.

Kan Andrey A Pavlyshyn Damian D Markham John F JF Dowling Mark R MR Heinzel Susanne S Zhou Jie H S JH Marchingo Julia M JM Hodgkin Philip D PD

PloS one 20160107 1

Adaptive immune responses are complex dynamic processes whereby B and T cells undergo division and differentiation triggered by pathogenic stimuli. Deregulation of the response can lead to severe consequences for the host organism ranging from immune deficiencies to autoimmunity. Tracking cell division and differentiation by flow cytometry using fluorescent probes is a major method for measuring progression of lymphocyte responses, both in vitro and in vivo. In turn, mathematical modeling of cel ...[more]

PMID: 26742110

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Project description:BackgroundIn our previous study that characterized different human CD4+ lymphocyte preparations, it was found that both commercially available cryopreserved peripheral blood mononuclear cells (PBMC) and a commercially available lyophilized PBMC (Cyto-Trol™) preparation fulfilled a set of criteria for serving as biological calibrators for quantitative flow cytometry. However, the biomarker CD4 protein expression level measured for T helper cells from Cyto-Trol was about 16% lower than those for cryopreserved PBMC and fresh whole blood using flow cytometry and mass cytometry. A primary reason was hypothesized to be due to steric interference in anti- CD4 antibody binding to the smaller sized lyophilized control cells.MethodTargeted multiple reaction monitoring (MRM) mass spectrometry (MS) is used to quantify the copy number of CD4 receptor protein per CD4+ lymphocyte. Scanning electron microscopy (SEM) is utilized to assist searching the underlying reasons for the observed difference in CD4 receptor copy number per cell determined by MRM MS and CD4 expression measured previously by flow cytometry.ResultsThe copy number of CD4 receptor proteins on the surface of the CD4+ lymphocyte in cryopreserved PBMCs and in lyophilized control cells is determined to be (1.45 ± 0.09) × 10(5) and (0.85 ± 0.11) × 10(5), respectively, averaged over four signature peptides using MRM MS. In comparison with cryopreserved PBMCs, there are more variations in the CD4 copy number in lyophilized control cells determined based on each signature peptide. SEM images of CD4+ lymphocytes from lyophilized control cells are very different when compared to the CD4+ T cells from whole blood and cryopreserved PBMC.ConclusionBecause of the lyophilization process applied to Cyto-Trol control cells, a lower CD4 density value, defined as the copy number of CD4 receptors per CD4+ lymphocyte, averaged over three different production lots is most likely explained by the loss of the CD4 receptors on damaged and/or broken microvilli where CD4 receptors reside. Steric hindrance of antibody binding and the association of CD4 receptors with other biomolecules likely contribute significantly to the nearly 50% lower CD4 receptor density value for cryopreserved PBMC determined from flow cytometry compared to the value obtained from MRM MS.

Project description:Over the past years, gut microbiota became a major field of interest with increasing reports suggesting its association with a large number of human diseases. In this context, there is a major interest to develop analysis tools allowing simple and cost-effective population pattern analysis of these complex ecosystems to follow changes over time. Whereas sequence-based metagenomics profiling is widely used for microbial ecosystems characterization, it still requires time and specific expertise for analysis. Flow cytometry overcomes these disadvantages, providing key information on communities within hours. In addition, it can potentially be used to select, isolate and cultivate specific bacteria of interest. In this study, we evaluated the culturability of strictly anaerobic bacteria that were stained with a classical Live/Dead staining, and then sorted using flow cytometry under anaerobic conditions. This sorting of "viable" fraction demonstrated that 10-80% of identified "viable" cells of pure cultures of strictly anaerobic bacteria were culturable. In addition, we tested the use of a combination of labeled vancomycin and Wheat Germ Agglutinin (WGA) lectin to discriminate Gram-positive from Gram-negative bacteria in complex ecosystems. After validation on both aerobic/anaerobic facultative and strictly anaerobic bacteria, the staining methods were applied on complex ecosystems, revealing differences between culture conditions and demonstrating that minor pH variations have strong impacts on microbial community structure, which was confirmed by 16S rRNA gene sequencing. This combination of staining methods makes it possible to follow-up evolutions of complex microbial communities, supporting its future use as a rapid analysis tool in various applications. The flow cytometry staining method that was developed has the potential to facilitate the analysis of complex ecosystems by highlighting changes in bacterial communities' dynamics. It is assumed to be applicable as an efficient and fast approach to improve the control of processes linked to a wide range of ecosystems or known communities of bacterial species in both research and industrial contexts.

Dataset Information

Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry.

Publications

Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry.

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