Work from our lab

Check the blog and news section of our site for updates

concerning current and publised projects that contain work from lab! 

(click here - availalbe soon)

Immune profiling in peripheral blood mononuclear cells (PBMCs)

We have  performed analysis of immune populations in peripheral blood mononuclear cells (PBMCs) and mononuclear cells from bone marrow using the Direct Immune Profiling Assay From Fluidgim (Cat no. 201325).

 

This kit is designed and optimized for the analysis of human peripheral whole blood and PBMCs (but can also be used to analyse immune populations from any cell supension). This kit contains 30 antibodies provided in a dry single-tube that included Cell-ID Intercalator-103Rh for the identificiation of live/dead cells. This assay enables comprehensive identifiaction and characterization of 37 immune populations including major T cells subsets (Th1-like,Th2-like, Th17-like Tregs), B cells,  monocytes, DCs and many other. 

Click here for Fluidigm White paper and TDS

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A simplified workflow for the Direct Immune profiling Assay. 

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Below is a sample of analysis performed by our lab using the pathsetter software and the cloud-based platform cytobank.

The example here shows mainly an example of exploratory analysis of immune populations in human PBMCs using pathsetter and cytobank

 

The analysis of high dimensinal data is a rapidly expanding and exciting field. Many alogrithms exist that can be used to discover novel clusters of phenoytpically distinct cells and identify differences (statistical inference) such as CITRUS and Phenograph between groups of samples like diffferent conditions and diseases, responders and responders, different developmental stages. 

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Pathsetter software provides a full analysis pipeline from data cleanup and data quality checks. 

These include debris, doublet, aggregate eclusion as well assesmnet of staining index. 

This report also provides informatino on the stability of signals during run as well as plasma Temp and oxide ratio which are essential elements of a quality acquisit acquisitino and are indiciative of qulaity and reliable data overall. 

Pathsetter software provides a full data report with percetnages and counts of 37 immune populatinos based on predifined gates and definitions on these immune susbsets based on latest literature. 

Pathsetter also creates a cen-se plot which clusters population based on phenotypic similarity and allows a more unbiased exploratory investigation of the data. 

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We also use cloud-based tool Cytobank to further explore these data. 

One such example is the algorithm viSNE (similar to Cen-se shown above). 

 

In this example you can see the phenotypic investigation of a cluster of CD3-CD19+ cells (B cells). The expression pattern of various markers like CD19, CD20, IgD, CXCR5, CCR7 and CCR6 can be examined. 

Click the link below for a very elegant review of the different approaches in analysing high dimensional cytometry data (such as the data the CyTOF technology produces). 

Kimball et al., A Beginner's Guide to Analyzing and Visualizing Mass Cytometry Data., JI 2018 (DOI:10.4049/jimmunol.1701494)

Fell free to contact us concerning queries regarding analysis of mass (and flow) cytometry data. 

Analysis of immune infiltrates in murine bladder

CyTOF technology can also be used to analyze cell populations in liquid suspension prepared from solid tissue, especialy when dealing with liquid cell suspensions from solid tissues (that would give high levels of autofluoesencece if analysed with conventinoal flow cytometry).   

We have recently used a 6-marker panel to analyze immune infiltrates in bladder tissue from mice with interstitial cystitis. 

Results from these experiments were recently published in JCI Insight (Paraskevopoulou et al., A. Klinakis Lab BRFAA).

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Figure 2B. Analysis of mass cytometry data on leukocytic populations of bladder tissue from WT and Krt5CreERT2 Ncstnfl/fl mice (n = 10 in each group). Scatter dot plots from normalized data showing expression of CD45, CD3, CD4, CD8, B220, and CD11b. CD3 marks all T cells, CD4 detects helper T cells, CD8 is expressed in cytotoxic T cells, B220 is expressed in B cells, and CD11b is a common myeloid marker. Representative of 3 experiments. (JCI Insight DOI: 10.1172/jci.insight.133232)

To access the full publication click here