TY - JOUR
T1 - Determining the most accurate 16S rRNA hypervariable region for taxonomic identification from respiratory samples
AU - López-Aladid, Ruben
AU - Fernández-Barat, Laia
AU - Alcaraz-Serrano, Victoria
AU - Bueno-Freire, Leticia
AU - Vázquez, Nil
AU - Pastor-Ibáñez, Roque
AU - Palomeque, Andrea
AU - Oscanoa, Patricia
AU - Torres, Antoni
N1 - Funding Information:
We would like to thank members of the IDIBAPS Genomics Unit for sequencing the raw data. We would also like to thank Dr Robert Sykes and Michael Maudsley for correcting the manuscript in English.
Funding Information:
We received funding from CB 06/06/0028/CIBER de enfermedades respiratorias—Ciberes ISCIII-FEDER-FSE (Intraciber 2018, FIS18-PI18/00145 to AT and LFB and FI19/00090 awarded to RLA). The funders had no role in the study design, data collection, data analysis, interpretation, or writing of this manuscript.
Publisher Copyright:
© 2023, The Author(s).
PY - 2023/3/9
Y1 - 2023/3/9
N2 - 16S rRNA gene profiling, which contains nine hypervariable regions (V1–V9), is the gold standard for identifying taxonomic units by high-throughput sequencing. Microbiome studies combine two or more region sequences (usually V3–V4) to increase the resolving power for identifying bacterial taxa. We compare the resolving powers of V1–V2, V3–V4, V5–V7, and V7–V9 to improve microbiome analyses in sputum samples from patients with chronic respiratory diseases. DNA were isolated from 33 human sputum samples, and libraries were created using a QIASeq screening panel intended for Illumina platforms (16S/ITS; Qiagen Hilden, Germany). The analysis included a mock community as a microbial standard control (ZymoBIOMICS). We used the Deblur algorithm to identify bacterial amplicon sequence variants (ASVs) at the genus level. Alpha diversity was significantly higher for V1–V2, V3–V4, and V5–V7 compared with V7–V9, and significant compositional dissimilarities in the V1–V2 and V7–V9 analyses versus the V3–V4 and V5–V7 analyses. A cladogram confirmed these compositional differences, with the latter two being very similar in composition. The combined hypervariable regions showed significant differences when discriminating between the relative abundances of bacterial genera. The area under the curve revealed that V1–V2 had the highest resolving power for accurately identifying respiratory bacterial taxa from sputum samples. Our study confirms that 16S rRNA hypervariable regions provide significant differences for taxonomic identification in sputum. Comparing the taxa of microbial community standard control with the taxa samples, V1–V2 combination exhibits the most sensitivity and specificity. Thus, while third generation full-length 16S rRNA sequencing platforms become more available, the V1–V2 hypervariable regions can be used for taxonomic identification in sputum.
AB - 16S rRNA gene profiling, which contains nine hypervariable regions (V1–V9), is the gold standard for identifying taxonomic units by high-throughput sequencing. Microbiome studies combine two or more region sequences (usually V3–V4) to increase the resolving power for identifying bacterial taxa. We compare the resolving powers of V1–V2, V3–V4, V5–V7, and V7–V9 to improve microbiome analyses in sputum samples from patients with chronic respiratory diseases. DNA were isolated from 33 human sputum samples, and libraries were created using a QIASeq screening panel intended for Illumina platforms (16S/ITS; Qiagen Hilden, Germany). The analysis included a mock community as a microbial standard control (ZymoBIOMICS). We used the Deblur algorithm to identify bacterial amplicon sequence variants (ASVs) at the genus level. Alpha diversity was significantly higher for V1–V2, V3–V4, and V5–V7 compared with V7–V9, and significant compositional dissimilarities in the V1–V2 and V7–V9 analyses versus the V3–V4 and V5–V7 analyses. A cladogram confirmed these compositional differences, with the latter two being very similar in composition. The combined hypervariable regions showed significant differences when discriminating between the relative abundances of bacterial genera. The area under the curve revealed that V1–V2 had the highest resolving power for accurately identifying respiratory bacterial taxa from sputum samples. Our study confirms that 16S rRNA hypervariable regions provide significant differences for taxonomic identification in sputum. Comparing the taxa of microbial community standard control with the taxa samples, V1–V2 combination exhibits the most sensitivity and specificity. Thus, while third generation full-length 16S rRNA sequencing platforms become more available, the V1–V2 hypervariable regions can be used for taxonomic identification in sputum.
UR - http://www.scopus.com/inward/record.url?scp=85149625083&partnerID=8YFLogxK
U2 - 10.1038/s41598-023-30764-z
DO - 10.1038/s41598-023-30764-z
M3 - Article
C2 - 36894603
AN - SCOPUS:85149625083
SN - 2045-2322
VL - 13
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 3974
ER -