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Updated: Jul 12, 2025
A Semi-automated Approach to Preparing Antibody Cocktails for Immunophenotypic Analysis of Human Peripheral Blood
Published on: February 8, 2016
Automated EuroFlow approach for standardized in-depth dissection of human circulating B-cells and plasma cells
Alejandro H Delgado1,2, Rafael Fluxa1, Martin Perez-Andres2,3,4
1Cytognos SL, Salamanca, Spain.
Insights
This study introduces an automated database-guided gating and identification (AGI) tool for analyzing B-lymphocytes and plasma cells (PC) in human blood. The AGI approach offers a faster, more reproducible, and standardized method compared to conventional flow cytometry analysis.
Area of Science:
- Immunology
- Biotechnology
- Computational Biology
Background:
- Multiparameter flow cytometry (FC) is crucial for identifying human blood leucocytes like B-lymphocytes and plasma cells (PC).
- Conventional FC data analysis is expertise-intensive, time-consuming, and lacks reproducibility.
Purpose of the Study:
- To develop and validate an automated database-guided gating and identification (AGI) approach.
- To enable fast, standardized, and in-depth analysis of B-lymphocyte and PC populations in human blood.
Main Methods:
- Utilized 213 FC standard (FCS) datafiles from umbilical cord and peripheral blood samples.
- Employed the 14-color 18-antibody EuroFlow BIgH-IMM panel for B-lymphocyte and PC identification.
- Developed a reference database and compared automated gating (AGI) with manual gating (MG) using hierarchical and two-step algorithms.
Main Results:
- The hierarchical AGI algorithm demonstrated higher correlation with manual gating (r²=0.94) compared to the two-step algorithm (r²=0.88).
- AGI analysis showed high correlation with expert-based manual gating (r²>0.81 for 79% of populations).
- AGI significantly reduced analysis time (median 6 min vs. 40 min) and variability (intra-sample CV 1.7% vs. 10.4%; inter-expert CV 3.9% vs. 17.3%).
Conclusions:
- The proposed AGI tool provides a faster, more robust, reproducible, and standardized method for analyzing B-lymphocyte and PC subsets.
- AGI enhances the efficiency and reliability of flow cytometry data analysis in human blood.
Background:
Multiparameter flow cytometry (FC) immunophenotyping is a key tool for detailed identification and characterization of human blood leucocytes, including B-lymphocytes and plasma cells (PC). However, currently used conventional data analysis strategies require extensive expertise, are time consuming, and show limited reproducibility.
Objective:
Here, we designed, constructed and validated an automated database-guided gating and identification (AGI) approach for fast and standardized in-depth dissection of B-lymphocyte and PC populations in human blood.
Methods:
For this purpose, 213 FC standard (FCS) datafiles corresponding to umbilical cord and peripheral blood samples from healthy and patient volunteers, stained with the 14-color 18-antibody EuroFlow BIgH-IMM panel, were used.
Results:
The BIgH-IMM antibody panel allowed identification of 117 different B-lymphocyte and PC subsets. Samples from 36 healthy donors were stained and 14 of the datafiles that fulfilled strict inclusion criteria were analysed by an expert flow cytometrist to build the EuroFlow BIgH-IMM database. Data contained in the datafiles was then merged into a reference database that was uploaded in the Infinicyt software (Cytognos, Salamanca, Spain). Subsequently, we compared the results of manual gating (MG) with the performance of two classification algorithms -hierarchical algorithm vs two-step algorithm- for AGI of the cell populations present in 5 randomly selected FCS datafiles. The hierarchical AGI algorithm showed higher correlation values vs conventional MG (r2 of 0.94 vs. 0.88 for the two-step AGI algorithm) and was further validated in a set of 177 FCS datafiles against conventional expert-based MG. For virtually all identifiable cell populations a highly significant correlation was observed between the two approaches (r2>0.81 for 79% of all B-cell populations identified), with a significantly lower median time of analysis per sample (6 vs. 40 min, p=0.001) for the AGI tool vs. MG, respectively and both intra-sample (median CV of 1.7% vs. 10.4% by MG, p<0.001) and inter-expert (median CV of 3.9% vs. 17.3% by MG by 2 experts, p<0.001) variability.
Conclusion:
Our results show that compared to conventional FC data analysis strategies, the here proposed AGI tool is a faster, more robust, reproducible, and standardized approach for in-depth analysis of B-lymphocyte and PC subsets circulating in human blood.
