Reagent-driven reconfiguration/optimization of a 16-parameter BD FACSARIA II SORP to allow accurate detection of violet- and UV-excited Sirigen dyes

Background. Modern flow cytometers can detect emission from a variety of commercially available fluorescent reagents. However, accurate detection of novel dyes is often difficult due to the lack of readily available quality assurance tools, for instrument manufacturer QC and optimization protocols often become available secondary to new fluorescent reagents. Aims. For standard QC and instrument calibration of the FACSARIA, BD provides a standard 'CS&T' method that includes three-peak beads and a dedicated software module. While this method allows tracking instrument state over time, it does not accurately access PMT performance on a significant part of the spectrum for violet-or UV-excited dyes. In order to ensure accurate detection of reagents within all 16 channels of the Boston University Flow Core 16-color, 4-laser BD FACSARIA SORP, we created and performed an novel optimization process that allows simultaneous accommodation of as many as nine polymeric Sirigen dyes, including those emitting in both long-wavelength violet-and UV-laser excited channels. Methods and Results. Firstly, the electronic noise of all PMTs was assessed and information was collected on rSD of non-stained cells within 100-800V range. The derived basal PMT values then provided a starting point for voltage optimization of instrument-specific panels. These values differed greatly from CS&T-deduced PMT voltages for abovementioned channels, for some the CS&T calculation of optimal PMT voltage was not possible due to a poor resolution of CS&T peaks at certain wavelengths. Several PMTs were identified with sub-par performance and were consequently replaced. Our testing of multiple commercial compensation beads found that the majority demonstrated prohibitively high backgrounds; the eBioscience UltraComp beads performed best and were therefore our reagent of choice. For instrument performance tracking, we also compared multi-peak beads from several manufacturers and found Spherotech Ultra Rainbow beads to be the sole bead type with satisfactory resolution of all peaks on long-wavelength UV channels. Finally, we developed an ergonomic protocol for facility users that includes an experiment template and electronic tables for data processing. With that protocol, a user can: (1) finely tune PMT voltages to accommodate a specific panel, (2) determine antibody concentrations for compensation control preparations, and (3) associate these optimized settings with multi-peak bead target values. Such preliminary setup allows quick panel-specific instrument calibration for each experimental run. This approach was successfully applied to several 16-color panels used in our Core facility and resulted in vastly improved reproducibility of acquired data over months of use. Conclusions. Synchronizing cutting-edge reagent technologies with existing instrument QC and maintenance methodology requires development of mix-and-match solutions not necessarily provided by the instrument manufacturer. Creating a user-friendly, accurate QC and calibration protocol that accommodates novel reagents allows dramatic expansion of our userbase's experimental capabilities

Cloud-based highly parallel execution of t-SNE and SPADE with metaclustering for analysis and visualization of large single-cell datasets

The use of machine learning techniques, in particular unsupervised clustering and dimensionality reduction algorithms, is quickly becoming a standard workflow for identifying and visualizing biological populations from within high-dimensional data. These methods allow researchers to approach data analysis without the bias and subjectivity that has traditionally been standard in the field. Algorithms have context-dependent strengths and weaknesses. Across algorithms, an inability to scale computation to large datasets is a common theme. Most algorithms are designed and distributed to run on individual computers where memory and CPU are quickly exhausted by large datasets. Even when high-performance compute resources are available, algorithms often don't scale to large datasets as a fundamental property of their design. If they do, it might result in an untenable increase in runtime or diminished quality of results. t-SNE and SPADE are two well-published algorithms that suffer problems as discussed above after datasets exceed a number of observations on the order of 1 million. This study introduces an alternative approach to the use of SPADE and t- SNE whereby a dataset is divided and distributed across numerous compute nodes in the cloud to process independently in parallel. The results of each computation are then combined in a metaclustering step for final visualization and analysis. The improvement in execution speed as a function of degree of parallelization is established. The method is validated against a non-parallel analysis of the same dataset to establish concordance of identified populations. The workflow is executed on Cytobank for portability to other researchers

Some aspects of the moss population development on the Svalbard glaciers

Glaciers are rather unusual habitat for mosses, but sometimes they can be suitable for some species due to presence of sufficient moisture and cryoconite substrate in the ablation zone. To date, moss populations were found only on a few glaciers in Alaska, Iceland and Svalbard. An origin and development of moss cushions on ice (so called "glacier mice") are still unclear. In this study, some aspects of the moss population development were explored on ice of the Svalbard glaciers – Bertilbreen (Billefjorden) and Austre Grnfjordbreen (Grnfjorden) in 2012 and 2013. On Bertilbreen, populations of Hygrohypnella polaris (Lindb.) Ignatov & Ignatova and Schistidium abrupticostatum (Bryhn) Ignatova & H.H. Blom were found for the first time. Due to putative morphological features, identification of S. abrupticostatum was confirmed by com-paring ITS1-2 nrDNA sequence data to BLAST searches (megablast). The results indicated a genetic heterogeneity of the population. Although visually moss-free, examination of cryoconite sediments revealed development of new individuals of S. abrupticostatum from filamentous structures consisting of caulonema and rhizoids. The developmental stages of young plants were revealed. Therefore, besides fragmen-tation of existing cushions, cryoconite sediments provided a source of new moss cush-ions in glacier populations. Additionally a few plants of Pohlia cf. wahlenbergii (F. Weber & D. Mohr) Andrews and a gametophyte fragment of Philonotis sp. were found in aggregation of cryoconite. Presence of Paludella squarrosa (Hedw.) Brid. reported for Bertilbreen has not been confirmed. On Austre Grnfjordbreen Bryum cryophilum Mrtensson, Sanionia uncinata (Hedw.) Loeske were found invading into some Hygrohypnella polaris cushions. Each moss polster on ice represents a separate mini-ecosystem that includes successive colonization events

Evaluation of ‘Super Bright’ polymer dyes in 13-16-color human immunophenotyping panels

Sirigen Group Limited developed unique polymer 'Brilliant' dyes that have become a staple of modern multicolor panel design. Polymer-based conjugates are often 4-10 times brighter than conventional fluorochromes with similar excitation/emission parameters. A new group of polymer fluorochromes, the 'Super Bright' dyes, was recently launched by eBioscience. The performance of these new dyes in large polychromatic panels is unclear to date. Therefore, we tested several preparations of the Super Bright dyes (such as Super Bright 436 and Super Bright 600) in two polychromatic fluorescent panels (one 13-and one 16-color). Specifically, we evaluated the spillover spread matrices of both panels to evaluate the compatibility of Super Bright dyes with other fluorochromes in a setup with tight placement of fluorochrome emissions over the spectrum. We have also matched Super Bright conjugates with comparable Brilliant Violet-labeled antibodies of same specificity in an existing 13-color panel where those conjugates are staining relatively dim targets, such as CCR6 and CD25, on resting human PBMC cells. Our results show that Super Bright dyes inflict a modest spillover spread in neighboring channels. In a 16x16 spillover spread matrix (3-UV, 5-VIOLET, 5-BLUE, 3-RED) Super Bright dyes demonstrate low to moderate spillover that is very close quantitatively to the Brilliant Violet dyes. In a 13-color human immunophenotyping panel that we previously developed to quantify T cell subsets, the " brightness " (i.e. the staining index of the Super Bright-conjugated antibodies) appears to be lower than comparable Brilliant Violet dyes when titrated, although stained populations in a full panel are still well separated. As the use of up to nine Brilliant polymer dyes simultaneously in large panels is not uncommon, we also tested the performance of Super Bright dyes in staining protocols that include Brilliant Buffer (BD Biosciences) to prevent polymer dye interactions and found them compatible. Overall, we found Super Bright dyes to perform well in large polychromatic panels. This expansion of commercially available conjugated antibody repertoire with the addition of Super Brights is timely and will greatly facilitate the success of larger (13+ color) fluorescent panel design

viSNE fine-tuning enables better resolution of cell populations

t-Distributed Stochastic Neighbor Embedding (t-SNE or viSNE) is a dimensionality reduction algorithm that allows visualization of complex high-dimensional cytometry data as a two-dimensional distribution or " map ". These maps can be interrogated by human-guided or automated techniques to categorize single cell data into relevant biological populations and otherwise visualize important differences between samples. The method has been extensively adopted and reported in the literature to be superior to traditional biaxial gating. The analyst must carefully choose the parameters of a t-SNE computation, as incorrectly chosen parameters might create artifacts that make the resulting map difficult or impossible to interpret. The correct choice of algorithm parameters is complicated by a lack of agreed-upon quantitative framework for assessing the quality of algorithm results. Gauging result quality currently relies on subjective visual evaluation by an experienced t-SNE user. To overcome these limitations, we used Cytobank viSNE engine for all t-SNE analyses and employed 18-parameter flow cytometry data as well as 32-parameter mass cytometry data of varying numbers of events to optimize t-SNE parameters such as total number of iterations and perplexity. We also investigated the utility of Kullback-Liebler (KL) divergence as a metric for map quality as well as SPADE clustering as an indirect measure of multidimensional data integrity when flattened into t-SNE coordinates. We have established the imperative requirement for the number of t-SNE analysis optimization steps ('iteration number') to be scaled with the total number of data points (events) in the set, suggesting that a number of existing software solutions produce unclear t-SNE maps of flow and mass cytometry data due to built-in user control restrictions. We also evaluated lower-level parameters within the t-SNE code that control the 'early exaggeration' stage initially introduced into t-SNE algorithm for better map optimization. These parameters are not available as part of the standard algorithm interface, but we found that they can be tuned to produce high quality results in shorter periods of time, avoiding unnecessary increases of both analysis duration and computation cost. Therefore, our approach allows to fine-tune the t-SNE analysis to ensure both optimal resolution of t-SNE low-dimensional maps and better faithfulness of their presentation of high-parameter cytometry data

Automated analysis of 16-color polychromatic flow cytometry data maps immune cell populations and reveals a distinct inhibitory receptor signature in systemic sclerosis

Background. The phenotypic profiles of both peripheral blood and tissue-resident immune cells have been linked to the health status of individuals with infectious and autoimmune diseases, as well as cancer. In light of the promising clinical trial results of agents that block the Inhibitory Receptor (IR) Programmed Death 1 (PD-1) axis, novel flow cytometric panels that simultaneously measure multiple IRs on several immune cell subsets could provide the distinct IR signatures to target in combinational therapies for many disease states. Also, due to the paucity of human samples, larger (14+ color) ‘1-tube’ panels for immune cell characterization ex vivo are of a high value in translational studies. Development of fluorescent-based panels offer several advantages as compared with analogous mass cytometric methods, including the ability to sort multiple populations of interest from the sample for further study. However, automated platforms of multi-dimensional single cell analysis that allow objective and comprehensive population characterization are severely underutilized on data generated from large polychromatic panels. Methods. A 16-color flow cytometry (FCM) panel was developed and optimized for the simultaneous characterization and purification of multiple human immune cell populations on a 4- laser BD FACSARIA II cell sorter. FCM data of samples obtained from healthy subjects and individuals with systemic sclerosis (SSc) were loaded into Cytobank cloud, then compensated and analyzed with SPADE clustering algorithm. The viSNE algorithm was also employed to compress the data into a 2D map of phenotypic space that was subsequently clustered using SPADE. For comparison, the FCM data were also analyzed manually using FlowJo software. Results. Our novel 16-color panel recognizes CD3, CD4, CD8, CD45RO, CD25, CD127, CD16, CD56, γδTCR, vα24, PD-1, LAG-3, CTLA-4, and TIM-3; it also contains a CD1d-tetramer and a live-dead dye (with CD19 and CD14 included as a combined dump channel). This panel allows combinational IR signatures to be determined from CD4+ T, CD8+ T, Natural Killer (NK), invariant Natural Killer (iNKT), and gamma delta (γδ) immune cell subsets within one sample. We have successfully identified all subsets of interest using automatic SPADE and viSNE algorithms integrated into Cytobank services, and demonstrated a distinctive phenotype of IR distribution on healthy versus systemic sclerosis subject groups. Conclusions. Methods of automatic analysis that were originally developed for processing multi-dimensional mass cytometry can be applied to polychromatic FCM datasets and provide robust results, including subset identification and distinct IR signatures in healthy compared to diseased subject groups

Risky investments and survival probability in the insurance model with two-sided jumps: Problems for integrodifferential equations and ordinary differential equation and their equivalence

We consider a model of an insurance portfolio that includes both non-life and life annuity insurance while assuming  that the surplus (or some of its fraction) is invested in risky assets with the price dynamics given by a geometric Brownian motion. The portfolio  surplus (in the absence of investments)  is described by a stochastic process involving two-sided jumps and a continuous drift. Downward jumps correspond to the claim sizes and upward jumps are interpreted as random gains  that arise at the final moments of the life annuity contracts realizations (i.e. at the moments of the death of policyholders). The drift is determined by the difference between premiums in the non-life insurance contracts and the annuity payments. We study the ruin problem for the model with investment using an approach based on integrodifferential equations (IDE) for the survival probabilities as a function of initial surplus. The main problem in calculating the survival probability as a solution of the IDE is that the initial value of the probability itself or its derivative at a zero initial surplus is priori unknown.  For the case of the exponential distributions of the jumps, we propose a solution to this problem based on the assertion that the problem for an IDE  is equivalent to a problem for an ordinary differential equation (ODE) with some nonlocal condition added. As a result,  a solution to the original problem can be obtained as a solution to the ODE problem with an unknown parameter, which is finally determined using the specified nonlocal condition and a normalization condition

B Cell Depletion Therapy as a Cutting-Edge Treatment of Demyelinating Diseases of the Central Nervous System

Demyelinating diseases of the central nervous system and multiple sclerosis in particular are a pressing issue for medical community and society as a whole. Deve- lopment and implementation of highly effective specific therapy significantly slow the disease progression and help maintain patients' quality of life and social participation. We analyzed pathogenic mechanisms of multiple sclerosis and other B cell-mediated diseases and reviewed therapeutic options for main disease stages

Abstract 803: Targeting β-catenin/CBP signaling in OSCC

OBJECTIVES: Oral squamous cell carcinoma (OSCC) is an aggressive malignancy characterized by molecular heterogeneity and locoregional spread associated with high morbidity. Aggressive cancers are thought to arise from populations of cancer initiating cells (CICs) that exhibit the properties of stem cells and drive tumor development, recurrence and resistance to therapy. The transcriptional regulator, β-catenin, has been implicated in OSCC CICs. Nuclear β-catenin has been shown to recruit the chromatin remodeling CREB binding protein (CBP) to drive expression of proliferation and survival genes, as well as genes that maintain stem-like phenotypes. We hypothesized that targeting β-catenin-CBP interaction will inhibit CICs in oral tumors and restore an epithelial phenotype. METHODS: To test tumor aggressive potential of OSCC CICs, we used zebrafish as a model system. We isolated CD44+CD24hiCD29hi cells fom aggressive HSC-3 OSCC cells by FACS and assayed their ability to drive tumor growth and metastases in zebrafish compared to unsorted and CD44+CD24lowCD29low cells. In addition, we examined the role of the β-catenin/CBP axis in the aggressive phenotype of these cells. We also assessed whether the β-catenin/CBP axis affected CICs in tumors from immune competent HPV+ mice. RESULTS: Zebrafish injected with subpopulation of cells co-expressing CD44+CD24hiCD2hi primitive cell surface markers drove rapid tumor growth and metastases, followed by unsorted and sorted CD44+CD24lowCD29low. Treatment of CD44+CD24hiCD29hi cells with a small molecule inhibitor of the β-catenin-CBP interaction, ICG-001, interfered with tumor growth and metastases in zebrafish. Further, ICG-001 inhibited tumor growth in immunocompetent HPV+ murine model. On a cellular level, ICG-001 promoted membrane localization of β-catenin, enhanced E-cadherin adhesion and restored epithelial phenotype. Significantly, ICG-001 gene signatures tracked with reduced overall patient survival in the cancer genome atlas, TCGA. Conclusion: Our studies indicate that the β-catenin/CBP axis promotes OSCC CICs and that ICG-001 may be an effective therapeutic agent for this malignancy.Support: Evans Center for Interdisciplinary Biomedical Research ARC funding AU 5303015 8000000

Epithelial cell–derived secreted and transmembrane 1a signals to activated neutrophils during pneumococcal pneumonia

Airway epithelial cell responses are critical to the outcome of lung infection. In this study, we aimed to identify unique contributions of epithelial cells during lung infection. To differentiate genes induced selectively in epithelial cells during pneumonia, we compared genome-wide expression profiles from three sorted cell populations: epithelial cells from uninfected mouse lungs, epithelial cells from mouse lungs with pneumococcal pneumonia, and nonepithelial cells from those same infected lungs. Of 1,166 transcripts that were more abundant in epithelial cells from infected lungs compared with nonepithelial cells from the same lungs or from epithelial cells of uninfected lungs, 32 genes were identified as highly expressed secreted products. Especially strong signals included two related secreted and transmembrane (Sectm) 1 genes, Sectm1a and Sectm1b. Refinement of sorting strategies suggested that both Sectm1 products were induced predominantly in conducting airway epithelial cells. Sectm1 was induced during the early stages of pneumococcal pneumonia, and mutation of NF-kB RelA in epithelial cells did not diminish its expression. Instead, type I IFN signaling was necessary and sufficient for Sectm1 induction in lung epithelial cells, mediated by signal transducer and activator of transcription 1. For target cells, Sectm1a bound to myeloid cells preferentially, in particular Ly6GbrightCD11bbright neutrophils in the infected lung. In contrast, Sectm1a did not bind to neutrophils from uninfected lungs. Sectm1a increased expression of the neutrophil-attracting chemokine CXCL2 by neutrophils from the infected lung. We propose that Sectm1a is an epithelial product that sustains a positive feedback loop amplifying neutrophilic inflammation during pneumococcal pneumonia