Metagenome analysis using serum extracellular vesicles identified distinct microbiota in asthmatics

Abstract

Different patterns of bacterial communities have been reported in the airways and gastrointestinal tract of asthmatics when compared to healthy controls. However, the blood microbiome of asthmatics is yet to be investigated. Therefore, we aimed to determine whether a distinct serum microbiome is observed in asthmatics by metagenomic analysis of serum extracellular vesicles (EVs). We obtained serum from 190 adults with asthma and 260 healthy controls, from which EVs were isolated and analyzed. The bacterial composition of asthmatics was significantly different from that of healthy controls. Chao 1 index was significantly higher in the asthma group, while Shannon and Simpson indices were higher in the control group. At the phylum level, Bacteroidetes was more abundant in asthmatics, while Actinobacter, Verrucomicrobia, and Cyanobacteria were more abundant in healthy controls. At the genus level, 24 bacterial genera showed differences in relative abundance between asthmatics and controls, with linear discriminant analysis scores greater than 3. Further, in a diagnostic model based on these differences, a high predictive value with a sensitivity of 0.92 and a specificity of 0.93 was observed. In conclusion, we demonstrated distinct blood microbiome in asthma indicating the role of microbiome as a potential diagnostic marker of asthma.

The Origin of Plasma-Derived Bacterial Extracellular Vesicles in Healthy Individuals and Patients with Inflammatory Bowel Disease: A Pilot Study

“…As an initial experiment prior to the main study, we compared two commonly used EV isolation methods: ultracentrifugation and SEC [53,54] as well as boiling, which is frequently used for plasma BEV-associated DNA isolation [26,27,[55][56][57]. Based upon the relative amplification of the V3-V4 region of the 16S rRNA gene per mL of plasma, SEC and boiling were optimal for maximal DNA isolation (Figure 3a).…”

“…Consequently, a number of studies using DNA (16S rRNA) sequencing have investigated the origin of the "blood microbiome", indicating that the blood microbiome of healthy individuals comprises of DNA originating from mainly Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes [23], although the source of this circulating DNA is often not described. BEV-associated DNA has been identified in patients with Alzheimer's disease [24], Parkinson's disease [25], dermatitis [26], asthma [27], cardiovascular disease [28], gastric cancer [29], biliary tract cancer [30], and COVID-19 [31]. However, few have investigated the origin of blood-derived BEVs in IBD.…”

Pharmacokinetics of Ginsenoside Compound K From a Compound K Fermentation Product, CK‐30, and From Red Ginseng Extract in Healthy Korean Subjects

“…Libraries were prepared from the EV DNA polymerase chain reaction products according to the MiSeq System guide (Illumina, San Diego, California) and quantified using QIAxpert (Qiagen). For amplification of the V3‐V4 hypervariable region of the 16S rDNA gene, 16S_V3_F (5′‐TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CCT ACG GGN GGC WGC AG‐3′) and 16S_V4_R (5′‐GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GGA CTA CHV GGG TAT CTA ATC C‐3′) primers were used as previously reported 12–15 . Each amplicon was then quantified, set at an equimolar ratio, pooled, and sequenced on a MiSeq system (Illumina).…”

Exosomes: A Key Piece in Asthmatic Inflammation

“…This year, several manuscripts have probed the importance of serum EVs analysis to understand other parameters that can exert an effect on asthma pathology. Lee et al [ 139 ] used EVs from the serum of healthy and asthmatic individuals to extract DNA and study, by means of metagenomic analysis, the microbial composition and its relation to clinical characteristics of asthma. The authors obtained a bacterial composition that was significantly different between the two groups, creating a diagnostic model based on these differences with good predictive values (sensitivity: 0.92, specificity: 0.93).…”