분석 방법 변화에 따른 음성 대조군과 호흡기 검체 간 미생물 구성 차이 비교
Comparison of differences in microbial compositions between negative controls and subject samples with varying analysis configurations
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Purpose: Identifying microbial communities with 16S ribosomal RNA (rRNA) gene sequencing is a popular approach in microbiome studies, and various software tools and data resources have been developed for microbial analysis. Our aim in this study is investigating various available software tools and reference sequence databases to compare their performance in differentiating subject samples and negative controls. Methods: We collected 4 negative control samples using various acquisition protocols, and 2 respiratory samples were acquired from a healthy subject also with different acquisition protocols. Quantitative methods were used to compare the results of taxonomy compositions of these 6 samples by varying the configuration of analysis software tools and reference databases. Results: The results of taxonomy assignments showed relatively little difference, regardless of pipeline configurations and reference databases. Nevertheless, the effect on the discrepancy was larger using different software configurations than using different reference databases. In recognizing different samples, the 4 negative controls were clearly separable from the 2 subject samples. Additionally, there is a tendency to differentiate samples from different acquisition protocols. Conclusion: Our results suggest little difference in microbial compositions between different software tools and reference databases, but certain configurations can improve the separability of samples. Changing software tools shows a greater impact on results than changing reference databases; thus, it is necessary to utilize appropriate configurations based on the objectives of studies.
Abstract
Purpose: Identifying microbial communities with 16S ribosomal RNA (rRNA) gene sequencing is a popular approach in microbiome studies, and various software tools and data resources have been developed for microbial analysis. Our aim in this study is investigating various available software tools and reference sequence databases to compare their performance in differentiating subject samples and negative controls. Methods: We collected 4 negative control samples using various acquisition protocols, and 2 respiratory samples were acquired from a healthy subject also with different acquisition protocols. Quantitative methods were used to compare the results of taxonomy compositions of these 6 samples by varying the configuration of analysis software tools and reference databases. Results: The results of taxonomy assignments showed relatively little difference, regardless of pipeline configurations and reference databases. Nevertheless, the effect on the discrepancy was larger using different software configurations than using different reference databases. In recognizing different samples, the 4 negative controls were clearly separable from the 2 subject samples. Additionally, there is a tendency to differentiate samples from different acquisition protocols. Conclusion: Our results suggest little difference in microbial compositions between different software tools and reference databases, but certain configurations can improve the separability of samples. Changing software tools shows a greater impact on results than changing reference databases; thus, it is necessary to utilize appropriate configurations based on the objectives of studies.
참고문헌 (23)
- Staley JT, "Measurement of in situ activities of nonphotosynthetic microorganisms in aquatic and terrestrial habitats", Annu Rev Microbiol, 39, pp.321~346 (1985)[DOI]
- Zoetendal EG, "Molecular ecological analysis of the gastrointestinal microbiota: a review", J Nutr, 134, pp.465~472 (2004)[DOI]
- NIH HMP Working Group, "The NIH Human Microbiome Project", Genome Res, 19, pp.2317~2323 (2009)[DOI]
- Ley RE, "Ecological and evolutionary forces shaping microbial diversity in the human intestine", Cell, 124, pp.837~848 (2006)[DOI]
- Clemente JC, "The impact of the gut microbiota on human health: an integrative view", Cell, 148, pp.1258~1270 (2012)[DOI]
- Lederberg J, "'Ome sweet' omics: a genealogical treasury of words", Scientist, 15, pp.8~10 (2001)
- Grice EA, "The human microbiome: our second genome", Annu Rev Genomics Hum Genet, 13, pp.151~170 (2012)[DOI]
- Weinstock GM, "Genomic approaches to studying the human microbiota", Nature, 489, pp.250~256 (2012)[DOI]
- Morgan XC, "Chapter 12: human microbiome analysis", PLoS Comput Biol, 8, pp.e1002808~ (2012)[DOI]
- Armougom F, "Exploring microbial diversity using 16S rRNA high-throughput methods", J Comput Sci Syst Biol, 2, pp.74~92 (2009)
- Clarridge JE 3rd, "Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases", Clin Microbiol Rev, 17, pp.840~862 (2004)[DOI]
- Balvociute M, "SILVA, RDP, Greengenes, NCBI and OTT - how do these taxonomies compare?", BMC Genomics, 18(Suppl 2), pp.114~ (2017)[DOI]
- Schloss PD, "Application of a database-independent approach to assess the quality of operational taxonomic unit picking methods", mSystems, 1(2) (2016)
- Plummer E, "A comparison of three bioinformatics pipelines for the analysis of preterm gut microbiota using 16S rRNA gene sequencing data", J Proteomics Bioinform, 8, pp.283~291 (2015)
- Masella AP, "PANDAseq: paired-end assembler for illumina sequences", BMC Bioinformatics, 13, pp.31~ (2012)[DOI]
- Rognes T, "VSEARCH: a versatile open source tool for metagenomics", PeerJ, 4, pp.e2584~ (2016)[DOI]
- Caporaso JG, "QIIME allows analysis of high-throughput community sequencing data", Nat Methods, 7, pp.335~336 (2010)[DOI]
- Edgar RC, "Search and clustering orders of magnitude faster than BLAST", Bioinformatics, 26, pp.2460~2461 (2010)[DOI]
- DeSantis TZ, "Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB", Appl Environ Microbiol, 72, pp.5069~5072 (2006)[DOI]
- Quast C, "The SILVA ribosomal RNA gene database project: improved data processing and web-based tools", Nucleic Acids Res, 41(Database issue), pp.D590~D596 (2013)
- Magoc T, "FLASH: fast length adjustment of short reads to improve genome assemblies", Bioinformatics, 27, pp.2957~2963 (2011)[DOI]
- Li W, "Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences", Bioinformatics, 22, pp.1658~1659 (2006)[DOI]
- Lozupone C, "UniFrac: a new phylogenetic method for comparing microbial communities", Appl Environ Microbiol, 71, pp.8228~8235 (2005)[DOI]