DURAClone IM Innate Lymphoid Cell Tube Performance

The intrinsic variability in biological material and the instability of samples can make flow cytometry assays prone to variability. Adding to that, the requirement for instrument setup and standardization of acquisition settings—as well as operator differences and inconsistencies in the analysis of complex data outputs—contribute to assay variability. Robust panel design and reduction of error-prone steps can increase the reliability of the method.

Commitment to quality. Beckman Coulter fully characterizes the quality of our reagents. Multiple lots of each reagent are tested by multiple operators to determine the recommended ideal antibody concentration per test, robust incubation times and the variation of staining results within and between lots. Each new lot is evaluated to ensure that established QC parameters are met.

Precision across 4 different product lots. Peripheral whole blood samples were collected withEDTA as an anticoagulant from 10 normal donors and were stained using 4 different lots of DURAClone IM Innate Lymphoid Cell Tube (C96081) with 3 replicates for each lot, resulting in 12 replicates for each donor. Populations were quantified as % of the respective parent gate (e.g., a lymphocyte gate) and the respective Median Fluorescence Intensity (MdFI) for positive populations was recorded. The range of a) %gated and b) MdFI values obtained within a series of replicates is represented by the respective 95% confidence interval, illustrating the tight ranges of values obtained for each donor.

a)

% gated 405nm 488nm 633nm
Pacific Blue Krome Orange FITC PE ECD PC5.5 PC7 APC AF700 APCA-F750
Donor 1 95% confidence interval - CD45 CD294
(CRTH2)
LIN - CD117 CD335
(NKp46)
CD127 - CD161
Donor 2 varies with trigger / threshold setting 1.3-1.4% "dump" channel; mixture of 11 markers Cell line 100% positive 0.7-0.8% -72.6%
19.5-19.9%
Donor 3 3.2-3.5% 1.4-1.8%

77.5-78.2%

27.9-28.3%
Donor 4

2.9-3.0%

0.8-0.9% 65.7-66.4%
28.3-28.7%
Donor 5 1.4-1.5% 2.8-2.9% 69.9-70.6%
28.5-29.0%
Donor 6 2.0-2.1% 0.5-0.6% 66.0-67.1%
30.8-31.4%
Donor 7 2.0-2.1% 0.6-0.7% 65.9-66.6%
25.4-25.9%
Donor 8 2.5-2.6% 1.1-1.3% 68.0-68.6% 30.4-30.8%
Donor 9 4.6-4.8% 0.6-0.8% 49.8-50.3%

26.0-26.7%

Donor 10 5.3-5.5% 0.7-0.8% 67.0-67.5% 22.2-22.9%
Donor 11 2.6-2.8% 0.4-0.5% 72.1-73.0% 19.4-20.3%

 

b)
MdFI 405nm 488nm 633nm
Pacific Blue Krome Orange FITC PE ECD PC5.5 PC7 APC AF700 APCA-F750
Donor 1 95% confidence interval - CD45 CD294
(CRTH2)
LIN - CD117 CD335
(NKp46)
CD127 - CD161
Donor 2 varies with trigger / threshold setting 16.0-17.2 11 marker "dump" channel; Cell line 100% positive 0.7-0.8% 71.8-72.6%
19.5-19.9%
Donor 3 13.4-14.0 1.4-1.8%

77.5-78.2%

27.9-28.3%
Donor 4

16.7-18.2

0.8-0.9% 65.7-66.4%
28.3-28.7%
Donor 5 13.7-14.7 2.8-2.9% 69.9-70.6%
28.5-29.0%
Donor 6 19.1-20.5 0.5-0.6% 66.0-67.1%
30.8-31.4%
Donor 7 22.5-24.2 0.6-0.7% 65.9-66.6%
25.4-25.9%
Donor 8 23.5-26.2 1.1-1.3% 68.0-68.6% 30.4-30.8%
Donor 9 24.6-26.6 0.6-0.8% 49.8-50.3%

26.0-26.7%

Donor 10 19.6-21.1 0.7-0.8% 67.0-67.5% 22.2-22.9%
Donor 11 13.7-15.3 0.4-0.5% 72.1-73.0% 19.4-20.3%

 

Data Clustering. The graphical representations illustrate the narrow clustering of the measurements used to calculate the 95% confidence intervals. Grey dots indicate average values

Variability of gated CD294CRTH2

Variability of MdFI CD294CRTH2

Variability of gated CD335NKp46
Variability of MdFI CD335NKp46

 

 
Variability of gated CD127

Variability of MdFI CD127

Variability of gated CD161

Variability of MdFI CD161

*Median Fluorescence Intensity

 

Selected Literature References On DURA Innovations-supported Standardization

A standardized immune phenotyping and automated data analysis platform for multicenter biomarker studies.

Ivison S, Malek M, Garcia RV, Broady R, Halpin A, Richaud M, Brant RF, Wang SI, Goupil M, Guan Q, Ashton P, Warren J, Rajab A, Urschel S, Kumar D, Streitz M, Sawitzki B, Schlickeiser S, Bijl JJ, Wall DA, Delisle JS, West LJ, Brinkman RR, Levings MK. JCI Insight. 2018 Dec 6;3(23).

 

Standardization procedure for flow cytometry data harmonization in prospective multicenter studies.

Le Lann L, Jouve PE, Alarcón-Riquelme M, et al. Sci Rep. 2020;10(1):11567. Published 2020 Jul 14. doi:10.1038/s41598-020-68468-3

 

An easy and reliable whole blood freezing method for flow cytometry immuno-phenotyping and functional analyses.

Braudeau C, Salabert-Le Guen N, Chevreuil J, Rimbert M, Martin JC, Josien RCytometry B Clin Cytom. 2021 Feb 5.

 

Standard protocols for immune profiling of peripheral blood leucocyte subsets by flow cytometry

Kronenberg K, Riquelme P, Hutchinson JA. using DuraClone IM reagents. Research Square; 2021. DOI: 10.21203/rs.3.pex-757/v1.

 

Deep phenotyping of immune cell populations by optimized and standardized flow cytometry analyses.

Pitoiset F, Cassard L, El Soufi K, et al. Cytometry A. 2018;93(8):793-802. doi:10.1002/cyto.a.23570

 

Literature References Guiding DURAClone ILC Marker Selection

Innate Lymphoid Cells: 10 years on.

Eric Vivier, David Artis et. al. Cell. (2018). 174 (5). 1054-1066.

 

Human innate lymphoid cells.

Mjösberg and Spits. J Allergy Clin Immunol. (2016). 138 (5). 1265-1276.

 

Human innate lymphoid cells (ILCs): Toward a uniform immune-phenotyping.

Trabanelli, Gomez-Cadena et. al. Cytometry B Clin Cytom. 2018. 94 (3). 392-399