16S rRNA amplicon sequencing or, more recently, metatranscriptomic analysis are currently the only preferred methods for microbial profiling of samples containing a predominant ratio of human to bacterial DNA. However, due to the off-target amplification of human DNA, current protocols are inadequate for bioptic samples. Here we present an efficient, reliable, and affordable method for the bacteriome analysis of clinical samples human DNA content predominates. We determined the microbiota profile in a total of 40 human biopsies of the esophagus, stomach, and duodenum using 16S rRNA amplicon sequencing with the widely used 515F-806R (V4) primers targeting the V4 region, 68F-338R primers and a modified set of 68F-338R (V1-V2M) primers targeting the V1-V2 region. With the V4 primers, on average 70% of amplicon sequence variants (ASV) mapped to the human genome. On the other hand, this off-target amplification was absent when using the V1-V2M primers. Moreover, the V1-V2M primers provided significantly higher taxonomic richness and reproducibility of analysis compared to the V4 primers. We conclude that the V1-V2M 16S rRNA sequencing method is reliable, cost-effective, and applicable for low-bacterial abundant human samples in medical research.

Department of Biochemistry Faculty of Science Masaryk University Kamenice 735 5 62500 Brno Czech Republic

Department of Gastroenterology and Internal Medicine University Hospital Brno and Faculty of Medicine Masaryk University Jihlavská 20 62500 Brno Czech Republic

Department of Pathophysiology Faculty of Medicine Masaryk University Jihlavská 20 62500 Brno Czech Republic

Department of Surgery University Hospital Brno and Faculty of Medicine Masaryk University Jihlavská 20 62500 Brno Czech Republic

Faculty of Science RECETOX Masaryk University Kotlářská 2 Brno Czech Republic

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Gilbert J, et al. Current understanding of the human microbiome. Nat. Med. 2018;24:392–400. doi: 10.1038/nm.4517. PubMed DOI PMC

Berg G, et al. Microbiome definition re-visited: Old concepts and new challenges. Microbiome. 2020;8:103. doi: 10.1186/s40168-020-00875-0. PubMed DOI PMC

France MT, et al. Insight into the ecology of vaginal bacteria through integrative analyses of metagenomic and metatranscriptomic data. Genome Biol. 2022;23:66. doi: 10.1186/s13059-022-02635-9. PubMed DOI PMC

Pereira-Marques J, et al. Impact of host DNA and sequencing depth on the taxonomic resolution of whole metagenome sequencing for microbiome analysis. Front. Microbiol. 2019;10:1277. doi: 10.3389/fmicb.2019.01277. PubMed DOI PMC

Liu Y-X, et al. A practical guide to amplicon and metagenomic analysis of microbiome data. Protein Cell. 2021;12:315–330. doi: 10.1007/s13238-020-00724-8. PubMed DOI PMC

Johnson JS, et al. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat. Commun. 2019;10:5029. doi: 10.1038/s41467-019-13036-1. PubMed DOI PMC

Thompson LR, et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551:457–463. doi: 10.1038/nature24621. PubMed DOI PMC

Elliott DRF, Walker AW, O’Donovan M, Parkhill J, Fitzgerald RC. A non-endoscopic device to sample the oesophageal microbiota: A case-control study. Lancet Gastroenterol. Hepatol. 2016;2:32–42. doi: 10.1016/S2468-1253(16)30086-3. PubMed DOI PMC

Klindworth A, et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 2013;41:e1. doi: 10.1093/nar/gks808. PubMed DOI PMC

Kameoka S, et al. Benchmark of 16S rRNA gene amplicon sequencing using Japanese gut microbiome data from the V1–V2 and V3–V4 primer sets. BMC Genom. 2021;22:527. doi: 10.1186/s12864-021-07746-4. PubMed DOI PMC

Heidrich V, et al. Choice of 16S ribosomal RNA primers impacts male urinary microbiota profiling. Front. Cell. Infect. Microbiol. 2022;12:862338. doi: 10.3389/fcimb.2022.862338. PubMed DOI PMC

Walker SP, et al. Non-specific amplification of human DNA is a major challenge for 16S rRNA gene sequence analysis. Sci. Rep. 2020;10:16356. doi: 10.1038/s41598-020-73403-7. PubMed DOI PMC

Dacey DP, Chain FJJ. Concatenation of paired-end reads improves taxonomic classification of amplicons for profiling microbial communities. BMC Bioinform. 2021;22:493. doi: 10.1186/s12859-021-04410-2. PubMed DOI PMC

Pichler M, et al. A 16S rRNA gene sequencing and analysis protocol for the Illumina MiniSeq platform. MicrobiologyOpen. 2018;7:e00611. doi: 10.1002/mbo3.611. PubMed DOI PMC

Van Dessel N, Swofford CA, Forbes NS. Potent and tumor specific: Arming bacteria with therapeutic proteins. Ther. Deliv. 2015;6:385–399. doi: 10.4155/tde.14.113. PubMed DOI PMC

McAllister SM, et al. Biodiversity and emerging biogeography of the neutrophilic iron-oxidizing zetaproteobacteria ▿. Appl. Environ. Microbiol. 2011;77:5445–5457. doi: 10.1128/AEM.00533-11. PubMed DOI PMC

Browne HP, et al. Culturing of ‘unculturable’ human microbiota reveals novel taxa and extensive sporulation. Nature. 2016;533:543–546. doi: 10.1038/nature17645. PubMed DOI PMC

Rajilic-Stojanovic M, et al. Systematic review: Gastric microbiota in health and disease. Aliment. Pharmacol. Ther. 2020;51:582–602. doi: 10.1111/apt.15650. PubMed DOI

Di Pilato V, et al. The esophageal microbiota in health and disease. Ann. N. Y. Acad. Sci. 2016;1381:21–33. doi: 10.1111/nyas.13127. PubMed DOI

Bik EM, et al. Molecular analysis of the bacterial microbiota in the human stomach. Proc. Natl. Acad. Sci. U. S. A. 2006;103:732–737. doi: 10.1073/pnas.0506655103. PubMed DOI PMC

Ruan W, Engevik MA, Spinler JK, Versalovic J. Healthy human gastrointestinal microbiome: Composition and function after a decade of exploration. Dig. Dis. Sci. 2020;65:695–705. doi: 10.1007/s10620-020-06118-4. PubMed DOI

Rajilić-Stojanović M, de Vos WM. The first 1000 cultured species of the human gastrointestinal microbiota. FEMS Microbiol. Rev. 2014;38:996–1047. doi: 10.1111/1574-6976.12075. PubMed DOI PMC

Snider EJ, et al. Alterations to the esophageal microbiome associated with progression from Barrett’s esophagus to esophageal adenocarcinoma. Cancer Epidemiol. Biomark. Prev. 2019;28:1687–1693. doi: 10.1158/1055-9965.EPI-19-0008. PubMed DOI PMC

Laserna-Mendieta EJ, et al. Esophageal microbiome in active eosinophilic esophagitis and changes induced by different therapies. Sci. Rep. 2021;11:7113. doi: 10.1038/s41598-021-86464-z. PubMed DOI PMC

Lopetuso LR, et al. Esophageal microbiome signature in patients with Barrett’s esophagus and esophageal adenocarcinoma. PLoS ONE. 2020;15:e0231789. doi: 10.1371/journal.pone.0231789. PubMed DOI PMC

Li, D. et al. Characterization of the esophageal microbiota and prediction of the metabolic pathways involved in esophageal cancer. Front. Cell. Infect. Microbiol.10, (2020). PubMed PMC

Lv J, et al. Alteration of the esophageal microbiota in Barrett’s esophagus and esophageal adenocarcinoma. World J. Gastroenterol. 2019;25:2149–2161. doi: 10.3748/wjg.v25.i18.2149. PubMed DOI PMC

Wang Z-K, Yang Y-S. Upper gastrointestinal microbiota and digestive diseases. World J. Gastroenterol. WJG. 2013;19:1541–1550. doi: 10.3748/wjg.v19.i10.1541. PubMed DOI PMC

Derakshani M, Lukow T, Liesack W. Novel bacterial lineages at the (sub)division level as detected by signature nucleotide-targeted recovery of 16S rRNA genes from bulk soil and rice roots of flooded rice microcosms. Appl. Environ. Microbiol. 2001;67:623–631. doi: 10.1128/AEM.67.2.623-631.2001. PubMed DOI PMC

Frock AD, Gray SR, Kelly RM. Hyperthermophilic thermotoga species differ with respect to specific carbohydrate transporters and glycoside hydrolases. Appl. Environ. Microbiol. 2012;78:1978–1986. doi: 10.1128/AEM.07069-11. PubMed DOI PMC

Katayama T, et al. Isolation of a member of the candidate phylum ‘Atribacteria’ reveals a unique cell membrane structure. Nat. Commun. 2020;11:6381. doi: 10.1038/s41467-020-20149-5. PubMed DOI PMC

Fadeev, E. et al. Comparison of two 16S rRNA primers (V3–V4 and V4–V5) for studies of arctic microbial communities. Front. Microbiol.12, (2021). PubMed PMC

Sirichoat A, et al. Comparison of different hypervariable regions of 16S rRNA for taxonomic profiling of vaginal microbiota using next-generation sequencing. Arch. Microbiol. 2021;203:1159–1166. doi: 10.1007/s00203-020-02114-4. PubMed DOI

Rintala A, et al. Gut microbiota analysis results are highly dependent on the 16S rRNA gene target region, whereas the impact of DNA extraction is minor. J. Biomol. Tech. JBT. 2017;28:19–30. doi: 10.7171/jbt.17-2801-003. PubMed DOI PMC

Zheng W, et al. An accurate and efficient experimental approach for characterization of the complex oral microbiota. Microbiome. 2015;3:48. doi: 10.1186/s40168-015-0110-9. PubMed DOI PMC

Walters W, et al. Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems. 2015;1:e00009–15. PubMed PMC

Wei Z, Zhang W, Fang H, Li Y, Wang X. esATAC: An easy-to-use systematic pipeline for ATAC-seq data analysis. Bioinformatics. 2018;34:2664–2665. doi: 10.1093/bioinformatics/bty141. PubMed DOI PMC

Callahan BJ, et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods. 2016;13:581–583. doi: 10.1038/nmeth.3869. PubMed DOI PMC

Wang Q, Garrity GM, Tiedje JM, Cole JR. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 2007;73:5261–5267. doi: 10.1128/AEM.00062-07. PubMed DOI PMC

Quast C, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–596. doi: 10.1093/nar/gks1219. PubMed DOI PMC

Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome. 2018;6:226. doi: 10.1186/s40168-018-0605-2. PubMed DOI PMC

Schliep KP. phangorn: Phylogenetic analysis in R. Bioinform. Oxf. Engl. 2011;27:592–593. doi: 10.1093/bioinformatics/btq706. PubMed DOI PMC

McMurdie PJ, Holmes S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8:e61217. doi: 10.1371/journal.pone.0061217. PubMed DOI PMC

Dixon P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 2003;14:927–930. doi: 10.1111/j.1654-1103.2003.tb02228.x. DOI

Lahti, L. & Shetty, S. Microbiome: Microbiome Analytics. (2022) 10.18129/B9.bioc.microbiome.

Xu, S. & Yu, G. MicrobiotaProcess: A comprehensive R package for managing and analyzing microbiome and other ecological data within the tidy framework. R package version. (2022).

Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. doi: 10.1186/s13059-014-0550-8. PubMed DOI PMC

Yu G. Using ggtree to visualize data on tree-like structures. Curr. Protoc. Bioinforma. 2020;69:e96. doi: 10.1002/cpbi.96. PubMed DOI

Pedersen, T. L. patchwork. (2022).