0680 - Mass cytometry for detection of silver at the bacterial single cell level

Author(s):  
Yuting Guo
2019 ◽  
Vol 35 (20) ◽  
pp. 4063-4071 ◽  
Author(s):  
Tamim Abdelaal ◽  
Thomas Höllt ◽  
Vincent van Unen ◽  
Boudewijn P F Lelieveldt ◽  
Frits Koning ◽  
...  

Abstract Motivation High-dimensional mass cytometry (CyTOF) allows the simultaneous measurement of multiple cellular markers at single-cell level, providing a comprehensive view of cell compositions. However, the power of CyTOF to explore the full heterogeneity of a biological sample at the single-cell level is currently limited by the number of markers measured simultaneously on a single panel. Results To extend the number of markers per cell, we propose an in silico method to integrate CyTOF datasets measured using multiple panels that share a set of markers. Additionally, we present an approach to select the most informative markers from an existing CyTOF dataset to be used as a shared marker set between panels. We demonstrate the feasibility of our methods by evaluating the quality of clustering and neighborhood preservation of the integrated dataset, on two public CyTOF datasets. We illustrate that by computationally extending the number of markers we can further untangle the heterogeneity of mass cytometry data, including rare cell-population detection. Availability and implementation Implementation is available on GitHub (https://github.com/tabdelaal/CyTOFmerge). Supplementary information Supplementary data are available at Bioinformatics online.


2019 ◽  
Vol 24 (4) ◽  
pp. 408-419
Author(s):  
Hongu Meng ◽  
Antony Warden ◽  
Lulu Zhang ◽  
Ting Zhang ◽  
Yiyang Li ◽  
...  

Mass cytometry (CyTOF) is a critical cell profiling tool in acquiring multiparameter proteome data at the single-cell level. A major challenge in CyTOF analysis is sample-to-sample variance arising from the pipetting process, staining variation, and instrument sensitivity. To reduce such variations, cell barcoding strategies that enable the combination of individual samples prior to antibody staining and data acquisition on CyTOF are often utilized. The most prevalent barcoding strategy is based on a binary scheme that cross-examines the existence or nonexistence of certain mass signals; however, it is limited by low barcoding efficiency and high cost, especially for large sample size. Herein, we present a novel barcoding method for CyTOF application based on mass ratiometry. Different mass tags with specific fixed ratios are used to label CD45 antibody to achieve sample barcoding. The presented method exponentially increases the number of possible barcoded samples with the same amount of mass tags compared with conventional methods. It also reduces the overall time for the labeling process to 40 min and avoids the need for expensive commercial barcoding buffer reagents. Moreover, unlike the conventional barcoding process, this strategy does not pre-permeabilize cells before the barcoding procedure, which offers additional benefits in preserving surface biomarker signals.


2017 ◽  
Vol 89 (16) ◽  
pp. 8228-8232 ◽  
Author(s):  
Angela Ivask ◽  
Andrew J. Mitchell ◽  
Christopher M. Hope ◽  
Simon C. Barry ◽  
Enzo Lombi ◽  
...  

2019 ◽  
Author(s):  
My Kieu Ha ◽  
Jang-Sik Choi ◽  
Zayakhuu Gerelkhuu ◽  
Sook Jin Kwon ◽  
Jaewoo Song ◽  
...  

AbstractThere have been many reports about the adverse effects of nanoparticles (NPs) on the environment and human health. Conventional toxicity assessments of NPs frequently assume uniform distribution of monodisperse NPs in homogeneous cell populations, and provide information on the relationships between the administered dose of NPs and cellular responses averaged for a large number of cells. They may have limitations in describing the wide heterogeneity of cell-NP interactions, caused by cell-to-cell and NP-to-NP variances. To achieve more detailed insight into the heterogeneity of cell-NP interactions, it is essential to understand the cellular association and adverse effects of NPs at single-cell level. In this study, we applied mass cytometry to investigate the interactions between silver nanoparticles (AgNPs) and primary human immune cells. High dimensionality of mass cytometry allowed us to identify various immune cell types and observe the cellular association and toxicity of AgNPs in each population. Our findings showed that AgNPs had higher affinity with phagocytic cells like monocytes and dendritic cells and caused more severe toxic effects than with T cells, B cells and NK cells. Multi-element detection capability of mass cytometry also enabled us to simultaneously monitor cellular AgNP dose and intracellular signaling of individual cells, and subsequently investigate the dose-response relationships of each immune population at single-cell level, which are often hidden in conventional toxicity assays at bulk-cell level. Our study will assist future development of single-cell dose-response models for various NPs and will provide key information for the safe use of nanomaterials for biomedical applications.


2019 ◽  
Vol 91 (18) ◽  
pp. 11514-11519 ◽  
Author(s):  
Ana López-Serrano Oliver ◽  
Andrea Haase ◽  
Anette Peddinghaus ◽  
Doreen Wittke ◽  
Norbert Jakubowski ◽  
...  

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi248-vi248
Author(s):  
Aaron Mochizuki ◽  
Alexander Lee ◽  
Joey Orpilla ◽  
Jenny Kienzler ◽  
Mildred Galvez ◽  
...  

Abstract INTRODUCTION Glioblastoma (GBM) is the most common malignant brain tumor in adults and is associated with a dismal prognosis. Neoadjuvant anti-PD-1 blockade has demonstrated efficacy in melanoma, non-small cell lung cancer and recurrent GBM; however, responses vary. While T cells have garnered considerable attention in the context of immunotherapy, the role of myeloid cells in the GBM microenvironment remains controversial. METHODS We isolated CD45+ immune populations from patients who underwent brain tumor resection at UCLA. We hypothesized that myeloid cells in glioblastoma contribute to T cell dysfunction; however, this immune suppression can be mitigated by neoadjuvant PD-1 inhibition. To test this, we utilized mass cytometry and single-cell RNA sequencing to characterize these immune populations. RESULTS Mass cytometry profiling of tumor infiltrating lymphocytes from patients with GBM demonstrated a preponderance of CD11b+ myeloid populations (75% versus 25% CD3+). At the transcriptomic level, myeloid cells in newly diagnosed GBMs exhibited decreased expression of CCL4 (loge fold change -1.18, Bonferroni-adjusted P = 1.62x10-254) and its ligands compared to anaplastic astrocytoma. In ranked gene set enrichment analysis, patients who received neoadjuvant pembrolizumab demonstrated enrichment in TNFα-, NFκB- and lipid metabolism-related gene sets by bootstrapped Kolmogorov-Smirnov test (Benjamini-Hochberg adjusted P = 4.74x10-3, 1.45x10-2 and 2.48x10-3, respectively) in tumor-associated myeloid populations. Additionally, single-cell trajectory analysis demonstrated increased CCL4 and decreased ISG15 with neoadjuvant checkpoint inhibition. CONCLUSIONS Here, we utilize mass cytometry and single-cell RNA sequencing to demonstrate the predominance and transcriptomic features of myeloid populations in GBM. Myeloid cells in patients who receive neoadjuvant PD-1 blockade re-express increased levels NFκB, TNFα and CCL4, a cytokine crucial for the recruitment of dendritic cells to the tumor for antigen-specific T cell activation. By delving into the GBM microenvironment at the single-cell level, we hope to better delineate the role of myeloid populations in this uniformly fatal tumor.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2626-2626
Author(s):  
Marie Lue Antony ◽  
Klara Noble-Orcutt ◽  
Karen Sachs ◽  
Anna Khoroshilov ◽  
Daniel Chang ◽  
...  

Abstract In acute myeloid leukemia (AML) standard therapies often induce complete remission, but patients frequently relapse and die of the disease. Leukemia stem cells (LSCs) have self-renewal potential and ability to recapitulate the disease. Our goal is to define the molecular mechanisms that allow AML to relapse. We have previously shown that activated NRAS (NRASG12V) facilitates self-renewal in the LSC-enriched subpopulation in a mouse model of AML (Mll-AF9/NRASG12V, Sachs et al. Blood 2014). We subsequently utilized single-cell RNA sequencing of the LSCs from this model to define and validate the only subset of the LSC-enriched population that can efficiently transplant leukemia in mice. We hypothesize that NRASG12V exerts a unique signaling profile that directs self-renewal in this subset of LSCs. Understanding these pathways at the single-cell level would enable us to design rational therapeutics that would prevent relapse in AML. We used mass cytometry (CyTOF2) to define the signaling activation state of LSC subsets in our AML model. Similar to flow cytometry, mass cytometry provides quantitative measurements of cell-surface and intracellular proteins at the single-cell level. In addition, it can simultaneously and accurately measure over 40 proteins, allowing us to quantitate a panel of intracellular signaling molecules in well-defined immunophenotypic leukemia subpopulations. We previously reported that the LSC-enriched population in this leukemia model is Mac1LowKit+Sca1+ (MKS) and subsequently showed that the self-renewing subset within the MKS population is MKSCD36LowCD69High. In contrast, the MKSCD36HighCD69Low population is incapable of transplanting leukemia in mice. The MKS cells displayed elevated levels of activated signaling molecules relative to the non-MKS population. Comparing the MKS subsets to each other, we found that the self-renewing MKSCD36LowCD69High population displayed significantly higher levels of several signaling molecules including Myc, NF-kB, and β-catenin relative to MKSCD36HighCD69Low cells (which lack self-renewal capacity). We reasoned that self-renewal might be mediated through these signaling molecules uniquely elevated in MKSCD36LowCD69High cells. Next, we sought to define the global signaling activation network within individual MKS subsets to determine if the signaling cascades and dependencies vary between these populations. We used Bayesian network modeling (Sachs K et al. Science 2005) to compare the statistical relationships between these signaling molecules, at the single-cell level. Signaling molecules that impact the levels of downstream effectors can be inferred using this approach. Using this method, we found that the signaling activation network does not significantly vary between MKS subsets. These observations suggest that self-renewal may be driven by alteration in the levels of signaling intermediates rather than alternate signal transduction architecture. We previously found that NRASG12V-mediated signals drive self-renewal in this AML model (Sachs Z. et al. Blood 2014). We used this model to ask which of these self-renewal-associated signaling molecules might be NRASG12V-regulated. We abolished NRASG12V transgene expression in these mice and harvested leukemia cells 72 hours later (per our standard lab protocol). Using this approach, found that self-renewal-associated signaling molecules, including NF-kB and β-catenin, are significantly reduced after NRASG12V-withdrawal indicating that NRASG12V -dependent signaling likely leads to the increase in these signaling molecules. In conclusion, we used mass cytometry analysis to identify the LSC self-renewal-associated signaling state in a murine model of AML and show that NRASG12V activates this signaling program. These data can be used to rationally design therapeutics such as small molecule inhibitors to target self-renewal-specific signaling and prevent relapse in AML. Disclosures No relevant conflicts of interest to declare.


2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Yu-Sang Sabrina Yang ◽  
Prabhani U Atukorale ◽  
Kelly D. Moynihan ◽  
Ahmet Bekdemir ◽  
Kavya Rakhra ◽  
...  

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Yu-Sang Sabrina Yang ◽  
Prabhani U. Atukorale ◽  
Kelly D. Moynihan ◽  
Ahmet Bekdemir ◽  
Kavya Rakhra ◽  
...  

Abstract Inorganic nanoparticles (NPs) are studied as drug carriers, radiosensitizers and imaging agents, and characterizing nanoparticle biodistribution is essential for evaluating their efficacy and safety. Tracking NPs at the single-cell level with current technologies is complicated by the lack of reliable methods to stably label particles over extended durations in vivo. Here we demonstrate that mass cytometry by time-of-flight provides a label-free approach for inorganic nanoparticle quantitation in cells. Furthermore, mass cytometry can enumerate AuNPs with a lower detection limit of ∼10 AuNPs (3 nm core size) in a single cell with tandem multiparameter cellular phenotyping. Using the cellular distribution insights, we selected an amphiphilic surface ligand-coated AuNP that targeted myeloid dendritic cells in lymph nodes as a peptide antigen carrier, substantially increasing the efficacy of a model vaccine in a B16-OVA melanoma mouse model. This technology provides a powerful new level of insight into nanoparticle fate in vivo.


2017 ◽  
Vol 8 ◽  
Author(s):  
Yuting Guo ◽  
Sabine Baumgart ◽  
Hans-Joachim Stärk ◽  
Hauke Harms ◽  
Susann Müller

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