2017 Poster Abstracts • •
Enumeration of Probiotic Organisms by Flow Cytometry
Andrzej A. Benkowski* and Jean L. Schoeni
Covance Laboratories Inc., Madison, WI
Probiotics manufacturers and consumers are demanding to know more about the identity and quantity of organisms in probiotic products. Enumeration provides the most basic information required and methodologies are evolving to provide results with improved accuracy, precision, and turnaround times. This study evaluated the use of an acoustic focusing flow cytometer, in accordance with the standardized method ISO 19344/IDF 232 (2015), to estimate the number of probiotics in samples rapidly, accurately and precisely.
Use of the acoustic focusing flow cytometer (Invitrogen™ Attune™ NxT, Thermo Fisher Scientific) and ISO enumeration method was verified according to USP 40-NF 35 <1225>/ICH Q2 (R1) for accuracy, precision, linearity, specificity, limit of quantification, range, and robustness. Powder samples containing freeze dried probiotics were evaluated. Further work was conducted to extend the methodology to microencapsulated, freeze dried probiotics. Cytometric values were compared to direct microscopic counts (freeze dried probiotics) and plate counts (freeze dried and microencapsulated probiotics) derived from the same sample preparations.
Functionality of the cytometer was confirmed by recovering counts > 90 % of applied BD Liquid Counting Beads. Performance of the method was verified by meeting or exceeding selected AOAC Appendix K criteria using freeze dried probiotics: Accuracy and robustness 70 to 125 % recovery compared to conventional methods; precision showing ≤ 15 % RSD; and specificity and linearity data producing R2 ≥0.95. Similar accuracy and precision results were observed in matrix extension testing with microencapsulated probiotics.
ISO 19344/IDF 232 (2015), conducted with an autofocusing flow cytometer, provides accurate, reliable enumerations of probiotics in various powders. This study demonstrates a novel application of flow cytometry as a strong, next step in the evolution of probiotic enumeration.
A Novel Far-red Trackable Tet-On System for Lineage Analysis of Stem Cells
Rodrigo Fernandez-Valdivia1,2,3,4, May Chammaa1, and Carlos Redondo1
1Department of Pathology, 2Department of Oncology, 3Cancer Biology Graduate Program, Wayne State University School of Medicine, Detroit, MI 48201, 4Tumor Biology & Microenvironment Program, Barbara Ann Karmanos Cancer Institute. Detroit, MI
Until recently, the existence of cancer stem cells and the notion of their central role in cancer initiation, progression, treatment-resistance, relapse, and metastasis, rested on extensive experimental evidence derived from cell enrichment and xenotransplantation studies that, nonetheless, left some uncertainty as to whether the regarded cancer stem cells actually functioned as such in tumors. However, the recent performing of genetic labeling and fate mapping studies in murine models of human cancers has not only provided conclusive demonstration of the cancer stem cell theory within a normal, immunocompetent, organismal context, but has also established the lineage tracing technique as an indispensable tool to determine cells-of-origin of cancers, study cancer stem cell ontogenesis, and performing tumor growth clonal lineage analyses.
However, notwithstanding great advances in single- and multi-color recombinase-directed genetic labeling, there is currently a preoccupying lack of a system with the ability to inducibly and non-stochastically label, within their own native niche, daughter cells with differing fate arisen through asymmetric cell division. Such system constitutes, especially in the cancer stem cell biology research field, an urgent need for studying cancer stem cell fate determination in vivo, uncovering the earliest molecular determinants dictating cancer stem cell fate decisions, and conducting in vivo genetic modifiers and drug-testing screenings to identify, respectively, novel factors and therapeutic agents modulating cancer stem cell asymmetric division rate.
To overcome this serious limitation in cancer stem cell research, we have recently developed a novel “Stem-cell compliant far-red trackable Tet-On technology”, in which the expression of the third generation rtTA protein is tracked by concordant bicistronic expression—through ribosomal skipping of the P2A peptide—of the stem cell-optimized, far-red fluorescent protein E2-Crimson, which allows combining cell-specific fluorescent labeling with recombinase-directed irreversible genetic labeling to achieve Differential Genetic Labeling of postmitotic daughter cells with differing fate.
The Effect of IL-2 and IL-15 Based Immunotherapy on Tumor Infiltrating Lymphocyte Populations
Anna Hoefges1, Alexander Rakhmilevich1,3, Kayla Rasmussen1, Jacob Slowinski1 and Paul M. Sondel 1,2,3
1Department of Human Oncology, 2Department of Pediatrics, and 3Carbone Comprehensive Cancer Center, University of Wisconsin- Madison, Madison, WI
Systemic IL-2 administration has long been known to enhance T regulatory (Treg) cells, which could lead to suppression of the immune response. If less immunosuppressive cell types are activated by the immunotherapy, the anti-tumor effect of the immunotherapy is expected to be more extensive. Here we investigated whether combining IL-2 with αCTLA-4 antibody or replacing IL-2 with IL-15 would result in lesser activation of immunosuppressive cell types, namely Treg and myeloid derived suppressor cells (MDSC). Using a B78 mouse melanoma model, we found that intratumoral IL-2 administration enhanced the Treg cell population and MDSC population in the tumor and in the spleen. A combination therapy of αCTLA-4 and IL-2 slightly reduced the amount of Treg cells and did not affect MDSCs. IL-15, which is closely related to IL-2, in contrast to IL-2, did not induce an upregulation in the Treg cell population or MDSC population. In addition, IL-15 caused a strong upregulation in the CD8+ cell population in the tumor and in the spleen, suggesting activation of antitumor T effector cells. IL-2 and IL-15 induced comparable antitumor effects in vivo. Overall, the alternative treatments examined show the ability to improve local IL-2-based immunotherapy by decreasing IL-2-induced immunosuppressive cell types.
Determination of Operational Voltages on an Instrument-by-Instrument Basis as a Means to Facilitate High-dimensional Panel Design in a Shared Resource Setting
Derek D. Jones, Richard D. Schretzenmair, and Jonni S. Moore
University of Pennsylvania Abramson Cancer Center, Flow Cytometry and Cell Sorting Resource Laboratory, Philadelphia, PA
The recent advent of a suite of ultra-bright fluorochromes has advanced flow cytometry to a new level, but often requires users to have a high degree of experience to fully benefit from these improvements. In a shared resource laboratory (SRL), however, users’ cytometry experience can range from novice to expert. Thus, it becomes the responsibility of SRL staff to provide users with the most information to allow them to best design and perform their studies. Here, we describe a straightforward method to integrate multiple techniques to determine the optimal and operational PMT voltages for each detector of a cytometer, and apply these measures to the design of a functional high-dimensional flow cytometry panel. We first determined the maximum resolution for each detector by using anti-human CD4 stained PBMC to calculate the stain index (SI) over a range of PMT voltages. By applying a regression curve to our data, we calculated the optimal PMT voltage (which gives maximal resolution) and operational PMT voltage (which maximizes resolution while ensuring that most CD antigens are on scale and within linearity) for each detector. Notably, the correlation between SI and PMTV is independent of both fluorochrome brightness and antigen density, making this method universally applicable in an SRL regardless of a users’ cell of interest or choice of fluorochrome. We then compared spillover spread matrices (SSM) derived from optimal, operational, and CS&T voltages, revealing a marked decrease in spillover between detectors using the former two methods. Providing SRL users with a SSM will allow them to rapidly identify problematic fluorochromes during panel design. To demonstrate this point, we utilized our SSM to design and predict panel performance to identify murine B cells and plasma cells during influenza immunization. Furthermore, after designating a target MFI, we used application settings to update cytometer changes daily for longitudinal studies. By providing users with information regarding SI and SSM for each cytometer in our SRL, we aim to 1) improve the data generated by users, 2) instruct the way users think about the biology of their experiments, and 3) facilitate the construction of higher-dimensional panels to address increasingly complex hypotheses. Lastly, this technique provides the additional benefit of enabling cross-instrument standardization in the near future.
Characterization of Non-specific Monocyte Binding
Non-specific binding of some fluorophores like PE/Dazzle™ 594, PerCp/Cy5.5, PE/Cy5, PE/Cy7, APC/Cy7 and APC/Fire™ 750 to live monocytes has been documented, although never fully characterized. BioLegend has formulated a buffer called True-Stain Monocyte Blocker™ that effectively blocks any non-specific binding of these tandem fluorophores in antibody-based flow cytometry assays. The blocking solution does not interfere with desirable monocyte-specific antibody staining. There are many assay factors that can influence this phenomenon that are common to flow cytometry assays including stimulation of cells with PMA and the number of antibodies included in the assay.
A Multiple Bead Platform for Protein Profiling of Exosomes by Flow Cytometry
Stefan Wild, Colin DeBakker, Nina Koliha, Yvonne Wiencek, Ute Heider, and Andreas Bosio
Exosomes or extracellular vesicles (EVs) are loaded with specific sets of proteins, lipids, and nucleic acids. The EV composition depends on the originating cell and different EVs can be distinguished by surface marker profiling. We established a multiplex bead-based assay consisting of capture and detection antibodies to analyze the composition of exosomal surface proteins by flow cytometry.
Evaluating Small Particle Scatter Signals from UV to Red Laser Excitation Using a 5 Laser Flow Cytometer
Edward Podniesinski, Paul K. Wallace
Department of Flow and Image Cytometry, Roswell Park Cancer Institute, Buffalo, NY
There has been considerable recent interest with measurement of biological particles less than 1000 nm using Flow Cytometric methods. These small particles are usually thought to have optimum scatter at the lower wavelengths. Before biological experiments can be performed, an understanding of instrument measurement capabilities and resolution must be determined. The Apogee 8 population bead set (Cat# 1493) contains bead particles of varying size, less than 1000 nm, close to the Refractive Index of biological material.
A 5 laser LSRII flow cytometer was used to acquire data from the Apogee 8 population bead set to determine optimum wavelength for Side Scatter detection. The Cytometer was configured to simultaneously detect Side Scatter from the 355 nm, 405 nm, 488 nm, 561 nm and 640 nm laser intercepts using existing PMTs.
8 peaks were seen using all laser lines except the 355 nm which only resolved 3 populations above noise. The other 405 nm, 488 nm, 561 nm, and 640 nm laser lines had 8 unique peaks but they were not baseline separated. When 2 Side Scatters from different wavelengths were evaluated in a 2 parameter dot plot clear resolution was achieved between all populations even the smallest.
Analysis of Signaling in a Rare B Cell Subset, by Phospho-flow Cytometry
Nicholas A. Zwang, MD and colleagues
University of Illinois Hospital, Chicago, IL
Kidney transplantation is a lifesaving treatment for end stage kidney disease. Rejection, however, remains a constant threat to the health of any kidney or solid organ transplants. Unique lymphocytes such as regulatory T cells, the best studied type of suppressor cell population, help prevent rejection. Surprisingly, one of the clearest markers of kidney allograft tolerance in clinical studies is not a T cell but a B cell signature, suggesting a critical role for B cells in graft survival. New studies have elucidated the importance of transitional B cells (TrBs), a unique sub-population of B cells with suppressive functions in transplantation. While circulating TrBs are low in overall frequency, deficient numbers correlates with antibody-mediated rejection in clinical transplantation. Aberrations TrB functionality have been found in patients with chronic rejection and lupus. Phospho-flow cytometry is a powerful tool to study intracellular signaling in rare cell populations. Current techniques require harsh treatment with paraformaldehyde-based fixation followed by methanol-based permeabilization. These treatments can both degrade surface antigens and antibody-conjugated fluorochromes. Here we have developed a protocol to preserve flow cytometric identification of rare B cell subsets, including TrBs, and probe intracellular phospho-signaling. We further demonstrate diminished overall MAP kinase signaling in TrBs compared to other B cell subsets.
Automated template-based recognition and classification of myeloid-derived suppressor cells using flowMatch algorithm
Ye Chen1, Ryan Calvert1, Ariful Azad2, Bartek Rajwa1 and Alex Pothen1*
1Purdue University, West Lafayette, IN; 2Lawrence Berkeley National Laboratory, Berkeley, CA
In the context of cancer, specific immune cells can be recruited to the tumor site where they protect the tumor by inhibiting host T cells. One group of suppressive cells are known as myeloid derived suppressor cells (MDSC). While the existence of these cells has been demonstrated in both animal and human studies, the identification of cells with the suppressive phenotype has not been possible with traditional flow cytometry. These cells exist as two distinct subtypes; monocyte-like and polymorphonuclear. Within each subtype, both suppressive and non-suppressive precursors are characterized by the same extracellular markers. Identification of functional vs. non-functional cells may aid in fine tuning immunotherapies at different stages of development. Here we describe algorithms for discovering immunophenotypes present in an extensive collection of biological samples from three biological classes (tissue from healthy animals, premalignant tissue, and advanced tumor), and using the discovery to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for efficient and robust cytometry data mining, including the creation of collections of cell populations’ characteristic of different classes of samples, robust classification, anomaly detection, and class prediction. We pre-select the myeloid cells by employing an automated gating algorithm based on density histograms of FC markers. Compared with the traditional visual gating practice that is influenced by operators’ experience and preferences, automated gating removes bias and lowers variability by selecting cells via a reproducible procedure that only depends on the density distributions of cellular functionalities defined by specific markers. We summarize a set of samples belonging to a particular biological class with a statistically-derived template for the class that supports the identification of immunophenotypes. Whereas individual samples are represented in terms of their cell populations (clusters), our template consists of generic meta-populations (a group of homogeneous cell populations obtained from the samples in a class) that summarize key phenotypes shared among all those samples. While most of the current automated FC analysis methods are single-sample-based, our batch analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in multiple samples while ignoring the noise and small sample-specific variations. With appropriate parameters chosen, our template-based classifier has an overall accuracy of nearly 90% when predicting the biological class of an unknown input FC file. Core algorithms used in our data analysis are available in the flowMatch package at www.bioconductor.org. The package has been downloaded almost 6,000 times since 2014. As a complementary method, the nearest neighbor classification approach has been used to identify different immunophenotypes on the basis of a distance between pre-clustered FC files. This extension of flowMatch resulted in an accuracy of ca. 96% in the described setting.
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