Revealing microbial recognition by specific antibodies
© Simón-Soro et al. 2015
Received: 27 May 2014
Accepted: 29 May 2015
Published: 2 July 2015
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.
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.
The application of the technique to healthy and diseased individuals may unravel the contribution of the immune response to microbial infections and polymicrobial diseases.
KeywordsImmunoglobulin Flow cytometry Pyrosequencing 16S rRNA Opsonization Human microbiome
There are extensive data describing the human microbiome, and germ free animal models demonstrate its intricate relationship with the host . However, less is understood about this relationship in humans, either in health or disease. The coating of microorganisms by antibodies may promote defense against infection, and regulate the immune response to the microbiota to limit potentially damaging responses, thus maintaining homeostasis in human-associated microbial communities [1, 2]. The recognition of microbes by different immunoglobulins (Igs) plays a vital role in the host-microbiome relationship , but the associations between Ig classes and specific groups of bacteria and fungi remain relatively poorly characterized . Flow cytometry allows the separation of bacterial cells according to their population structure [5, 6] and to the fluorescence emitted by antibodies specifically bound to different human Igs [7, 8]. These labeled populations of bacteria can be characterized by second-generation sequencing of PCR-amplified microbial rDNA genes, to provide a description of the bacterial and fungal diversity and taxonomic composition .
Sample collection and processing
All donors signed informed consent and the sampling protocol was approved by the Dirección General de Salud Pública (DGSP) ethical committee (Valencian Health Authority, Spain) for the faecal and oral samples; and the Bioethics Subcommittee of Consejo Superior de Investigaciones Científicas (CSIC) for the breast milk samples. For the oral samples, unstimulated saliva samples and supragingival dental plaque from 5 individuals that had never suffered from dental caries and 4 individuals with active caries were collected in sterile tubes 24 h after tooth brushing. Six faecal samples were stored in RNALater within 2 h from sampling and stored at −20 until fixation in formaldehyde. Healthy volunteer mothers with term deliveries were given written instructions for standardised collection of breast milk samples. Before sample collection, the breast was cleaned with an iodine swab to reduce bacteria residing on the skin, and breast milk was collected manually and after discarding first drops collected into a sterile milk collection unit, then immediately frozen and stored at −20 °C until analysis. A total of 12 breast milk samples corresponding to colostrum and mature milk were collected. All samples were centrifuged at 7500 g for 7 min to collect microbial cells and washed twice in physiological solution (NaCl 0.9 %). Cells were immediately fixed in 4 % paraformaldehyde overnight at 4 °C. Fixed cells were washed twice and stored at −20 °C in 50 % ethanol until use. On the experiment day, samples were washed in sterile saline solution and disaggregated 20 s in a sonicator bath, model Raypa VCI-50 at low ultrasound intensity.
Samples were suspended in sterile saline solution with 5 % albumin to prevent non-specific antibody binding, then stained with (i) anti-human IgA or IgG labelled with FITC (Invitrogen catalog # A18782 and A18806); and (ii) the DNA-binding fluorophor SYTO62 (Invitrogen catalog # S11344) according to the manufacturer instructions. Anti-mouse IgA or IgG labeled with FITC (Invitrogen catalog # M31101 and A24525) were used for isotype controls.
Cell sorting was performed with the MoFloTM XDP flow cytometer (Beckman Coulter Inc.) using Argon 488 nm (blue) laser (200 mW power) and the 635 nm (red) diode laser (25 mW power) as light sources. The lasers were aligned using Flow-CheckTM (10 μm) and Flow-SetTM (3 μm) fluorospheres (Beckman Coulter, Inc.). Emission filters were 520/30 for FITC and 680/30 for SYTO62 respectively. Proper fluorescent labeling was assessed by fluorescence and confocal microscopy (Additional file 1: Figure S1). Cells were separated according to their fluorescence in both the FITC and SYTO62 channels (Ig-coated bacteria) or the SYTO62 channel only (non-coated bacteria).
DNA from the Ig-coated and non-coated fractions with more than 5000 cells was extracted using the MasterPure™ Complete DNA and RNA Purification Kit (Epicentre Biotechnologies), following the manufacturer’s instructions, with the addition of a lysozyme treatment . The 16S rRNA gene was amplified using universal bacterial primers 8 F and 533R with sample-specific barcodes, as previously described . Purified PCR products were mixed in equimolar amounts and sequenced using the 454 GS-FLX pyrosequencer (Titanium chemistry, Roche). The resulting 16S rRNA reads were end-trimmed in 10 bp sliding windows with average quality value > 20, then length (200 pp) and quality filtered (average Q > 20). Taxonomic assignments were performed with the RDP classifier , and to estimate total diversity, sequences were clustered at 97 % nucleotide identity over 90 % sequence alignment length to obtain rarefaction curves. Principal Coordinates Analysis (PCoA) was performed with FastUnifrac , comparing the 16S-estimated composition with a phylogenetic approach that takes into account both taxonomically assigned and unassigned reads.
Results and discussion
Formaldehyde-fixed samples were stained with (i) anti-human IgA or IgG labelled with FITC; and (ii) the DNA-binding fluorophor SYTO62. Proper fluorescent marking was confirmed by fluorescence and confocal laser scanning microscopy (Additional file 1: Figure S1). Anti-mouse IgA or IgG, of identical isotype to the anti-human antibodies, labeled with FITC, (Invitrogen) were used to control for non-specific binding. Cells were separated in the flow cytometer according to their fluorescence in both the FL1-FITC and FL8-SYTO62 channels (Ig-coated bacteria) or the SYTO62 channel only (non-coated bacteria). DNA from the Ig-coated and non-coated fractions was extracted and the 16S rDNA gene amplified and pyrosequenced, in order to describe bacterial composition of the sorted populations. An outline of the experimental pipeline is described in Fig. 1. The density and number of cells that could be sorted from each fraction varied among samples (Additional file 2: Table S1). Although PCR and subsequent pyrosequencing was achieved with as few as 5000 sorted bacteria, a larger number of cells is recommended for accurate description of microbial composition .
Finally, rarefaction curves of species-level bacterial diversity show that the opsonized population is more diverse than the non-opsonized one (Fig. 5b). In future studies, we anticipate that the sequencing of the non-opsonized fractions will reveal those micro-organisms that are undetected or ignored by specific antibodies. Although the current work was done with titanium chemistry FLX pyrosequencing and sequences were under 500 bp long on average, current advances in this and other technologies are expected to allow read lengths over 900 bp shortly, allowing taxonomic assignment at the species level. This will no doubt be necessary for accurate description of antibody-microbial specificity, as current read lengths are mainly reliable at the genus level .
Another aspect that can readily be observed in flow cytometry scatter plots in environmental samples is the presence of aggregated populations as evidence by their larger size and specific shapes . Our own observations in human samples through fluorescence and confocal microscopy revealed that some of those large-size clusters are bacterial aggregates and others are formed by bacteria bound to host cells like detached buccal epithelial cells. These aggregates can by sorted and subsequently identified by 16S rDNA pyrosequencing (Additional file 3: Figure S2). In individual CA060, for instance, 70 % of a bacterial aggregate in a saliva sample was found to be formed by Porphyromonas, Streptococcus, Prevotella, Propionibacterium, Veillonella, and unidentified Bacteroidetes. This approach paves the way to unravel the nature of bacterial aggregation in body fluids with important repercussion for active and passive immunization approaches and novel antimicrobial strategies. For instance, aggregated microorganisms may be less accessible to antibodies and partially escape opsonization.
The mixed FACS-pyrosequencing approach presented here can also be applied to identify fungi, by using fungal-specific fluorescent markers and subsequent sequencing of PCR-amplified fungal ITS or 28S rRNA regions . In addition, an RNA-binding fluorophor like pyronin can be used to quantify, separate and sequence-identify active bacteria [6, 17]. In our saliva samples (n = 6), 31-43 % of bacteria appeared to be marked by pyronin, suggesting that a large portion of organisms in the oral cavity can be transient or inactive (Additional file 1: Figure S1). In the future, marking of IgA and IgG with different fluorescent markers could be used in the same sample, in order to distinguish individual cells coated by both of these antibodies. Finally, micro-organisms cell counts can be used to accurately calculate bacterial and fungal load, which can be related to the body fluid chemical and biological components. That way, features of the immune response can be associated to microbial composition and density, providing insights about functioning of the immune system and suggesting potential biomarkers of health and disease conditions.
The approach presented here involves the identification of Ig-detected and ignored microbes in healthy and diseased individuals [14, 20]. This approach offers novel insights into understanding host-microbe homeostasis in health and its disruption in myriad diseases, ranging from oral diseases (e.g. dental caries or periodontal disease) to gut disorders (e.g. Crohn’s disease, ulcerative colitis, or irritable bowel disease ) and even Ig-recognition of tumor cells. Considering immune recognition and opsonization in healthy individuals as a reference, deviations from that balanced microbe-immune interaction can potentially be related to microbial-mediated disorders, and the characterization of individual-specific opsonization profiles may also prove fruitful in diagnostic and therapeutic strategies for personalized medicine.
This work was supported by projects BIO2012-40007 and Consolider CSD2009-0002 and CSD2007-00063 from the Spanish Ministry of Economy and Competitiveness; by grant CP09/00049 Miguel Servet, Instituto de Salud Carlos III, Spain; and by projects 071/2011 AP-034/11 from Generalitat Valenciana. Flow Cytometry cell sorting was carried out using facilities at the Servei Central de Suport a la Investigació Experimental (SCSIE), University of Valencia.
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