SCI 발표논문

SCI 발표논문

← SCI 발표논문 목록

PLoS One. 2021;16(4):e0249688.

Microbiome profiling of uncinate tissue and nasal polyps in patients with chronic rhinosinusitis using swab and tissue biopsy.

, , , , ,

제1저자 조성우, 김동영 · 교신저자 강혜련, 이하나

PMID 33831071 PMC8031401 DOI 10.1371/journal.pone.0249688 IF 2.8 알레르기내과
소속 (8)
  1. Department of Otorhinolaryngology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.
  2. Department of Otorhinolaryngology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.
  3. Institute for Biomaterials, Korea University, Seoul, Republic of Korea.
  4. Department of Public Health Science, Seoul National University, Seoul, South Korea.
  5. Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.
  6. Institute of Allergy and Clinical Immunology, Seoul National University Medical Research Center, Seoul National University College of Medicine, Seoul, Korea.
  7. Interdisciplinary Program in Precision Public Health, Korea University, Seoul, Republic of Korea.
  8. School of Biosystem and Biomedical Science, Korea University, Seoul, Republic of Korea.

Abstract

Chronic rhinosinusitis (CRS) is characterized according to the presence or absence of nasal polyps (NPs) and displays nasal microbiota dysbiosis. However, optimal sampling methods of the nasal microbiome in CRS have not been identified. We aimed to assess the microbial composition in patients with CRS, comparing different sampling methods (swab and tissue biopsy), tissue types (uncinate tissue and NP), and disease subtypes. Samples were obtained by swabbing the middle meatus and taking a biopsy of uncinate tissue (UT) in patients with CRS with (CRSwNP, N = 8) or without NP (CRSsNP, N = 6) and controls (N = 8). NPs were also harvested in CRSwNP. DNAs were extracted from fifty-two samples and analyzed by 16S rRNA gene amplicon sequencing. As a result, a great interpersonal variance was observed in nasal swabs, while UT samples presented distinct microbiome with low inter-personal differences. Moreover, the UT microbiomes were further differentiated into three clusters which are associated with disease status (control, CRSsNP, and CRSwNP). Compared to UT, NP revealed a unique microbiome profile with significantly less bacterial diversity. Prevotella was the genus whose abundance was negatively correlated with disease severity in NP. In conclusion, tissue samples are better specimens than nasal swabs for assessing the microbiomes of CRS patients. Several bacteria in UT and NP tissues revealed an association with clinical severity of CRSwNP.

Figures

Fig 1
Fig 1 Distribution of bacterial taxa across disease and sampling subsites. Each stacked bar chart summarizes the percent relative abundances. A, At the phylum level, Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, and Fusobacteria were the five dominant phyla in both swabs and uncinate tissues regardless of the disease subtype. B, Top 30 bacterial genera in the microbiomes according to sample and disease subtypes. Abbreviations: NP, nasal polyp; CRSwNP, chronic rhinosinusitis with nasal polyp; CRSsNP, chronic rhinosinusitis without nasal polyp.
Fig 2
Fig 2 Variable microbiome structure as a function of clinical sample type and disease subtype. Beta-diversity was calculated by weighted UniFrac distance and plotted by PCoA. A, Microbiome distinctiveness depending on the clinical sample type. B, Uncinate tissue microbiome distinctiveness depending on the disease subtype. Confidence ellipse (dotted line) defines the region that contains 68% of all samples in each group. Abbreviations: CRSwNP, chronic rhinosinusitis with nasal polyp; CRSsNP, chronic rhinosinusitis without nasal polyp.
Fig 3
Fig 3 Uncinate tissue bacteria differ with disease subtype. Log-transformed bacterial genus abundances were regressed on the experimental groups to determine bacterial genera associated with disease subtypes. Only genera with P < 0.05 are shown. Abbreviations: C, control; S, CRSsNP (chronic rhinosinusitis without nasal polyp); W, CRSwNP (chronic rhinosinusitis with nasal polyp).
Fig 4
Fig 4 Characteristics of nasal polyp microbiome compared to uncinate tissue microbiome. Tissues from NP and UT of patients with CRSwNP were compared. A, NP exhibited a significantly decreased Shannon index (P = 0.012 by Wilcoxon signed rank test). B, The abundance of genus Prevotella is depleted in NP in all patients examined (n = 8). C, The abundance of genus Sediminibacterium is depleted in UT in all patients examined (n = 8). Abbreviations: NP, nasal polyp; UT, uncinate tissue; CRSwNP, chronic rhinosinusitis with nasal polyp.
Fig 5
Fig 5 Correlation between bacterial genera and disease severity. The genera most correlated with disease severity in NP, UT_CRSwNP, and UT_CRSsNP were Prevotella, Lachnospira, and Roseburia, respectively. Relative abundances of these genera were then compared to Lund-Mackay scores by correlation analysis in different tissue microenvironments (NP, UT_CRSwNP, and UT_CRsNP). Abbreviations: NP, nasal polyp; UT, uncinate tissue; CRSwNP, chronic rhinosinusitis with nasal polyp; CRSsNP, chronic rhinosinusitis without nasal polyp; LM, Lund-Mackey.

그림 출처: PubMed Central 공개 논문 (PMC8031401)

Conflict of interest statement

The authors have declared that no competing interests exist

그 밖의 정보
출판 형태
Journal Article, Research Support, Non-U.S. Gov't
저널
PloS one · eISSN 1932-6203
전자 출판
2021-04-08
MeSH
Adult · Bacteria / genetics · Biopsy / methods · Chronic Disease · Female · Humans · Male · Microbiota / genetics · Middle Aged · Nasal Polyps / microbiology · RNA, Ribosomal, 16S / genetics · Sinusitis / microbiology · Specimen Handling / methods
Substances
RNA, Ribosomal, 16S
참고문헌
43편