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Analysis of the Human Breast Milk Microbiome and Bacterial Extracellular Vesicles in Healthy Mothers Su Yeong Kim1 and Dae Yong Yi 1,2

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Analysis of the Human Breast Milk Microbiome and Bacterial Extracellular Vesicles in Healthy Mothers Su Yeong Kim1 and Dae Yong Yi 1,2 Kim and Yi Experimental & Molecular Medicine (2020) 52:1288–1297 https://doi.org/10.1038/s12276-020-0470-5 Experimental & Molecular Medicine ARTICLE Open Access Analysis of the human breast milk microbiome and bacterial extracellular vesicles in healthy mothers Su Yeong Kim1 and Dae Yong Yi 1,2 Abstract The microbiota of human breast milk (HBM) contribute to infant gut colonization; however, whether bacterial extracellular vesicles (EVs) are present in HBM or might contribute to this process remains unknown. In this study, we characterized the HBM microbiota of healthy Korean mothers and measured the key bacteria likely affecting infant gut colonization by analyzing both the microbiota and bacterial EVs. A total of 22 HBM samples were collected from lactating mothers. The DNA of bacteria and bacteria-derived EVs was extracted from each sample. In alpha-diversity analyses, bacterial samples showed higher richness and evenness than bacterial EV samples, and beta-diversity analyses showed significant differences between bacteria and bacterial EVs within identical individual samples. Firmicutes accounted for the largest proportion among the phyla, followed by Proteobacteria, Bacteroidetes, and Actinobacteria, in both bacteria and bacterial EV samples. At the genus level, Streptococcus (25.1%) and Staphylococcus (10.7%) were predominant in bacterial samples, whereas Bacteroides (9.1%), Acinetobacter (6.9%), and Lactobacillaceae(f) (5.5%) were prevalent in bacterial EV samples. Several genera, including Bifidobacterium, were significantly positively correlated between the two samples. This study revealed the diverse bacterial communities in the HBM of healthy lactating mothers, and found that gut-associated genera accounted for a high proportion in bacterial EV samples. Our findings suggest the existence of key bacteria with metabolic activity that are independent of the major bacterial populations that inhabit HBM, and the possibility that EVs derived from these bacteria are involved in the vertical 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; transfer of gut microbiota. Introduction lactoferrin and lysozyme), cytokines, and human milk More than 100 trillion microbes dwell within the oligosaccharide2. Before the 2000s, the presence of bac- human gut and interact with the host in a symbiotic teria in HBM was thought to indicate contamination or relationship to aid the development of the host immune infection, but several researchers have demonstrated that system. The early acquisition of the gut microbiome HBM contains commensal bacteria by using culture- during infancy affects health throughout human life. dependent techniques3,4. The development of the non- Several factors, such as the type of delivery, antibiotic culture-based sequencing technique has led to more therapy, environment of care, and nutritional exposure, thorough investigation of the diversity of the HBM are assumed to influence the early colonization of the microbiota5. Currently, it is recognized that HBM con- infant gut1. Diet plays a key role in the development of the tains abundant commensal bacteria that can affect the newborn’s immune system. Human breast milk (HBM) is colonization of the infant gut6. not only the best source of nutrition for infants, but is also Extracellular vesicles (EVs) are nanometer-sized mem- known to contain immune components, such as secretory brane vesicles that contain various bioactive molecules, antibodies, immune cells, antimicrobial proteins (such as such as transmembrane proteins, cytosolic proteins, nucleic acids, and lipids. It is widely accepted that all kinds of bacteria release EVs. Bacteria are classified into Correspondence: Dae Yong Yi ([email protected]) Gram-positive (G + ) and Gram-negative (G–) bacteria 1Department of Pediatrics, Chung-Ang University Hospital, Seoul 06973, South Korea based on membrane characteristics, and the G + bacteria- 2College of Medicine, Chung-Ang University, Seoul 06911, South Korea © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a linktotheCreativeCommons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Official journal of the Korean Society for Biochemistry and Molecular Biology Kim and Yi Experimental & Molecular Medicine (2020) 52:1288–1297 1289 derived EVs are usually called bacterial membrane vesi- supernatant was collected. DNA was extracted using a cles, while the G-bacteria-derived EVs are called outer DNA isolation kit (DNeasy PowerSoil Kit, QIAGEN, membrane vesicles7. Bacteria-derived EVs can be detected Germany) in accordance with the standard protocol in body fluids, such as blood, urine, or stool, indicating provided along with the kit. The DNA from bacteria and that they can affect host cells by directly activating host EVs in each sample was quantified using the QIAxpert receptors, delivering various bioactive molecules, or system (QIAGEN, Germany). – integrating EVs into host cells8 10. However, there has been no study on the analysis of bacteria-derived EVs in Bacterial metagenomic analysis using DNA from human HBM until now. milk samples In this context, the objective of this study was to char- Bacterial genomic DNA was amplified with the primers acterize the HBM microbiota of healthy lactating mothers 16S_V3_F (5′-TCG GCA GCG TCA GAT GTG TAT in Korea, and to measure the abundance of key bacteria AAG AGA CAG CCT ACG GGN GGC WGC AG-3′) and that can affect infant gut colonization by analyzing both 16S_V4_R (5′-GTC TCG TGG GCT CGG AGA TGT the microbiota and bacterial EVs using a culture- GTA TAA GAG ACA GGA CTA CHV GGG TAT CTA independent technique. ATC C-3′), which are specific for the V3–V4 hypervari- able regions of the 16S rDNA gene. The libraries were Materials and methods prepared using PCR products according to the MiSeq Subjects and sample collection System guide (Illumina, USA) and quantified using This study was conducted according to the guidelines QIAxpert (QIAGEN, Germany). Each amplicon was then proposed in the Declaration of Helsinki and approved by quantified, set to an equimolar ratio, pooled, and the Institutional Review Board (IRB) of Chung-Ang Uni- sequenced on a MiSeq instrument (Illumina, USA) versity Hospital, Seoul, South Korea (IRB No.: 1810-004- according to the manufacturer’s recommendations. 309). Healthy lactating mothers who had delivered a full- term baby were recruited within 1 week–4 months of Analysis of bacterial composition in the microbiota childbirth for this study (July 2017–June 2018). Paired-end reads that matched the adapter sequences Samples of breast milk were collected from 22 mothers were trimmed by cutadapt version 1.1.611. The resulting in sterile bags by manual or pump expression. Before milk FASTQ files containing paired-end reads were merged expression, hands were washed, and nipples were cleaned with CASPER and then quality- filtered using the Phred with sterile water. The first ten drops were discarded. The (Q) score-based criteria described by Bokulich12,13. Any fresh samples were delivered to the laboratory within 24 h reads shorter than 350 bp and longer than 550 bp after and then stored at −80 °C until further processing. If the merging were also discarded. To identify the chimeric samples did not reach the laboratory within 24 h, they sequences, a reference-based chimera-detection step was were excluded. Changes in bacterial diversity based on the performed using VSEARCH against the SILVA gold lactation stage, especially the difference between the database14,15. Next, the sequence reads were clustered microbiomes of the colostrum and mature HBM, are well into operational taxonomic units (OTUs) using known1. As we tried to analyze the bacteria that infants VSEARCH with a de novo clustering algorithm with a actually consume while feeding on stabilized mature milk, sequence similarity threshold of 97%. The representative we excluded the colostrum samples obtained within sequences of the OTUs were finally classified using the 1 week of childbirth. Samples from mothers who devel- GREENGENES database with UCLUST (paralle- oped disease or were administered antibiotics during l_assign_taxonomy_uclust.py script on QIIME version lactation were also excluded. 1.9.1) with default parameters16. EV isolation and DNA extraction from human milk samples Statistical analysis To separate the EVs from HBM, EVs in milk samples The richness (rarefaction curves) was analyzed using were isolated using differential centrifugation at 10,000×g Chao 1, and alpha-diversity indices (Chao 1, ACE, Shan- for 10 min at 4 °C. After centrifugation, the pellet con- non index, Simpson index, and Fisher’s index) were cal- tained bacteria, and the supernatant contained EVs. Bac- culated. Significance between subgroups was tested using teria and foreign particles were thoroughly eliminated by a t test for continuous
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