Profiling of microorganism-binding serum antibody specificities in professional athletes

The goal of this work was to elucidate similarities between microorganisms from the perspective of the humoral immune system reactivity in professional athletes. The reactivity of serum IgG of 14 young, individuals was analyzed to 23 selected microorganisms as antigens by use of the in house ELISA....

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Published in:	PloS one Vol. 13; no. 9; p. e0203665
Main Authors:	Minić, Rajna, Papić, Zlatko, Đorđević, Brižita, Michaličkova, Danica, Ilić, Vesna, Mathiesen, Geir, Živković, Irena, Pantic, Visnja, Dimitrijević, Ljiljana
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 25-09-2018 Public Library of Science (PLoS)
Subjects:	Analogies Analysis Antigens Athletes Bacterial infections Biology and Life Sciences Correlation Correlation analysis Cytokines Data analysis Data processing Diabetes E coli Enzyme-linked immunosorbent assay Genetic aspects Immune response Immune system Immunoglobulin A Immunoglobulin G Immunoglobulin M Immunoglobulins Infections Lactobacillus Lipopolysaccharides Medicine and Health Sciences Microbiota Microorganisms Physiological aspects Population Reactivity Research and Analysis Methods Streptococcus infections Virology Serbia
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Summary:	The goal of this work was to elucidate similarities between microorganisms from the perspective of the humoral immune system reactivity in professional athletes. The reactivity of serum IgG of 14 young, individuals was analyzed to 23 selected microorganisms as antigens by use of the in house ELISA. Serum IgM and IgA reactivity was also analyzed and a control group of sex and age matched individuals was used for comparison. The obtained absorbance levels were used as a string of values to correlate the reactivity to different microorganisms. IgM was found to be the most cross reactive antibody class, Pearson's r = 0.7-0.92, for very distant bacterial species such as Lactobacillus and E. coli.High correlation in IgG levels was found for Gammaproteobacteria and LPS (from E. coli) (r = 0.77 for LPS vs. P. aeruginosa to r = 0.98 for LPS vs. E.coli), whereas this correlation was lower in the control group (r = 0.49 for LPS vs. P. aeruginosa to r = 0.66 for LPS vs. E.coli). The correlation was also analyzed between total IgG and IgG subclasses specific for the same microorganism, and IgG2 was identified as the main subclass recognising different microorganisms, as well as recognising LPS. Upon correlation of IgG with IgA for the same microorganism absence of or negative correlation was found between bacteria-specific IgA and IgG in case of Lactobacillus and Staphylococcusgeni, whereas correlation was absent or positive for Candida albicans, Enterococcusfaecalis,Streptococcus species tested in professional athletes. Opposite results were obtained for the control group. Outlined here is a simple experimental procedure and data analysis which yields functional significance and which can be used for determining the similarities between microorganisms from the aspect of the humoral immune system, for determining the main IgG subclass involved in an immune response as well as for the analysis of different target populations.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Competing Interests: The authors have declared that no competing interests exist.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0203665