A flow cytometry-based workflow for detection and quantification of anti-plasmodial antibodies in vaccinated and naturally exposed individuals

• Published in: Malaria journal 2012-11, Vol.11 (1), p.367-367, Article 367
• Main Authors: Ajua, Anthony, Engleitner, Thomas, Esen, Meral, Theisen, Michael, Issifou, Saadou, Mordmüller, Benjamin
• Format: Article
• Language: English
• Subjects: Adult; Algorithmic data analysis; Algorithms; Analysis; Anti-malarial antibodies; Antibodies; Antibodies, Protozoan - blood; Antigens; Child, Preschool; Dosage and administration; Double-Blind Method; Elementary school students; Erythrocytes - immunology; Erythrocytes - parasitology; Flow cytometry; Flow Cytometry - methods; Flow Cytometry - statistics & numerical data; Flow cytometry-based IFA; Fluorescent Antibody Technique - methods; Fluorescent Antibody Technique - statistics & numerical data; Gabon; Human serum; Humans; Infant; Information management; Malaria; Malaria vaccine; Malaria Vaccines - administration & dosage; Malaria, Falciparum - immunology; Malaria, Falciparum - prevention & control; Methodology; Methods; Parasites; Plasmodium falciparum; Plasmodium falciparum - immunology; Prevention; Proteins; Public software; Risk factors; Vaccination; Vaccines; Viral antibodies; Viral vaccines
• ISSN: 1475-2875; 1475-2875
• DOI: 10.1186/1475-2875-11-367

Antibodies play a central role in naturally acquired immunity against Plasmodium falciparum. Current assays to detect anti-plasmodial antibodies against native antigens within their cellular context are prone to bias and cannot be automated, although they provide important information about natural exposure and vaccine immunogenicity. A novel, cytometry-based workflow for quantitative detection of anti-plasmodial antibodies in human serum is presented. Fixed red blood cells (RBCs), infected with late stages of P. falciparum were utilized to detect malaria-specific antibodies by flow cytometry with subsequent automated data analysis. Available methods for data-driven analysis of cytometry data were assessed and a new overlap subtraction algorithm (OSA) based on open source software was developed. The complete workflow was evaluated using sera from two GMZ2 malaria vaccine trials in semi-immune adults and pre-school children residing in a malaria endemic area. Fixation, permeabilization, and staining of infected RBCs were adapted for best operation in flow cytometry. As asexual blood-stage vaccine candidates are designed to induce antibody patterns similar to those in semi-immune adults, serial dilutions of sera from heavily exposed individuals were compared to naïve controls to determine optimal antibody dilutions. To eliminate investigator effects introduced by manual gating, a non-biased algorithm (OSA) for data-driven gating was developed. OSA-derived results correlated well with those obtained by manual gating (r between 0.79 and 0.99) and outperformed other model-driven gating methods. Bland-Altman plots confirmed the agreement of manual gating and OSA-derived results. A 1.33-fold increase (p=0.003) in the number of positive cells after vaccination in a subgroup of pre-school children vaccinated with 100 μg GMZ2 was present and in vaccinated adults from the same region we measured a baseline-corrected 1.23-fold, vaccine-induced increase in mean fluorescence intensity of positive cells (p=0.03). The current workflow advances detection and quantification of anti-plasmodial antibodies through improvement of a bias-prone, low-throughput to an unbiased, semi-automated, scalable method. In conclusion, this work presents a novel method for immunofluorescence assays in malaria research.