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. 2015 Jul 2:15:132.
doi: 10.1186/s12866-015-0456-y.

Revealing microbial recognition by specific antibodies

Affiliations

Revealing microbial recognition by specific antibodies

Áurea Simón-Soro et al. BMC Microbiol. .

Abstract

Background: Recognition of microorganisms by antibodies is a vital component of the human immune response. However, there is currently very limited understanding of immune recognition of 50 % of the human microbiome which is made up of as yet un-culturable bacteria. We have combined the use of flow cytometry and pyrosequencing to describe the microbial composition of human samples, and its interaction with the immune system.

Results: We show the power of the technique in human faecal, saliva, oral biofilm and breast milk samples, labeled with fluorescent anti-IgG or anti-IgA antibodies. Using Fluorescence-Activated Cell Sorting (FACS), bacterial cells were separated depending on whether they are coated with IgA or IgG antibodies. Each bacterial population was PCR-amplified and pyrosequenced, characterizing the microorganisms which evade the immune system and those which were recognized by each immunoglobulin.

Conclusions: The application of the technique to healthy and diseased individuals may unravel the contribution of the immune response to microbial infections and polymicrobial diseases.

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Figures

Fig. 1
Fig. 1
A mixed Flow Cytometry-Next Generation Sequencing strategy to identify human host-microbial associations. Body samples (saliva, faeces, urine, mucosa, milk, etc.) are disaggregated by vortexing and mild sonication. Microbial cells are fixed in 4 % paraformaldehyde previous to staining with fluorescent markers to detect cells (e.g. by DNA markers [6]), active cells (e.g. by RNA markers [17]) and specific antibodies (e.g. by anti-human IgA) through a flow cytometer. Microbial load can also be accurately estimated by cell counting. Cells are sorted depending on whether they are opsonized with either IgA or IgG antibodies. Each bacterial population can then be PCR-amplified and pyrosequenced, characterizing the microorganisms which evade the immune system and those which are recognized by each immunoglobulin. The application of the technique to healthy and diseased individuals may unravel the contribution of the immune response to microbial infections and polymicrobial diseases
Fig. 2
Fig. 2
Fluorescence activated cell sorting of opsonized bacteria in a faecal sample stained with anti-IgA markers. The frequency histogram (a) represents the events displaying FITC fluorescence with anti-human IgA (green) and anti-mouse IgA (blue) markers. The latter is used as isotype control (non-specific binding). Thus, the green area to the right corresponds to IgA-coated micro-organisms. The green area overlapping with non-specific binding indicates a lack of fluorescence, corresponding to non-opsonized cells. FITC-based histograms are typically bimodal, with the two peaks corresponding to Ig-coated and non-coated populations. The corresponding scatterplots for anti-mouse and anti-human IgA labeling are shown in (b) and (c), respectively. The region above anti-mouse IgA binding was gated to select true opsonization. FS = Forward scatter, which correlates with cell size
Fig. 3
Fig. 3
Ig-coating levels in different human samples. Boxplots show the mean values and variation in IgA- and IgG-opsonization levels for oral biofilm (B), milk (M), fecal samples (F), and saliva (S). Asterisks indicate statistically significant differences between IgA and IgG coating (Wilcoxon test, p < 0.05). For saliva and oral biofilm, samples from Caries-free (NCA) and Caries-bearing (CA) individuals are available. Data are shown for a conservative (Opsonized 1) and a non-conservative (Opsonized 2), upper estimate of Ig-coating. Individual data are shown in Additional file 2: Table S1
Figure 4
Figure 4
Bacterial composition of IgA-coated and non-coated populations. Graphs show the proportion of bacterial genera within the opsonized and non-opsonized populations in individual samples from feces, breast milk, oral biofilm (dental plaque) and saliva as estimated by 16S rDNA pyrosequencing of fluorescence-activated sorted cells. The four samples are from different individuals. Only bacteria found at a frequency >1 % are shown. Some bacterial genera appear at similar proportions in both the Ig-coated and non-coated populations. Others appear only within the opsonized fraction (strong IgA-specificity) whereas some microorganisms are present only within the non-opsonized fraction (immune evasion or non-recognition)
Figure 5
Figure 5
Diversity of Ig-coated and uncoated bacteria in human saliva. Saliva samples collected 24 h after toothbrushing (n = 16) were stained with fluorescent markers for bacterial DNA, IgA and IgG, and sorted in three groups: IgA-coated bacteria, IgG-coated bacteria and uncoated, non-opsonized bacteria. a Bacterial composition at the genus level for total saliva samples, as well as for the IgA- and IgG-coated fractions. The bacterial composition appeared to be different between the different fractions. b Rarefaction curves relating pyrosequencing effort to the estimated number of species (OTUs at 97 % sequence identity). The non-opsonized fractions display a lower diversity and different taxonomic composition to opsonized populations

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