Staemmler, Frank and Glaesner, Joachim and Hiergeist, Andreas and Holler, Ernst and Weber, Daniela and Oefner, Peter J. and Gessner, Andre and Spang, Rainer (2016) Adjusting microbiome profiles for differences in microbial load by spike-in bacteria. MICROBIOME, 4: UNSP 28. ISSN 2049-2618,
Full text not available from this repository. (Request a copy)Abstract
Background: Next-generation 16S ribosomal RNA gene sequencing is widely used to determine the relative composition of the mammalian gut microbiomes. However, in the absence of a reference, this does not reveal alterations in absolute abundance of specific operational taxonomic units if microbial loads vary across specimens. Results: Here we suggest the spiking of exogenous bacteria into crude specimens to quantify ratios of absolute bacterial abundances. We use the 16S rDNA read counts of the spike-in bacteria to adjust the read counts of endogenous bacteria for changes in total microbial loads. Using a series of dilutions of pooled faecal samples from mice containing defined amounts of the spike-in bacteria Salinibacter ruber, Rhizobium radiobacter and Alicyclobacillus acidiphilus, we demonstrate that spike-in-based calibration to microbial loads allows accurate estimation of ratios of absolute endogenous bacteria abundances. Applied to stool specimens of patients undergoing allogeneic stem cell transplantation, we were able to determine changes in both relative and absolute abundances of various phyla, especially the genus Enterococcus, in response to antibiotic treatment and radio-chemotherapeutic conditioning. Conclusion: Exogenous spike-in bacteria in gut microbiome studies enable estimation of ratios of absolute OTU abundances, providing novel insights into the structure and the dynamics of intestinal microbiomes.
Item Type: | Article |
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Uncontrolled Keywords: | GENOMIC ANALYSIS; GUT MICROBIOME; SP-NOV.; DISEASE; TRANSPLANTATION; NORMALIZATION; COLONIZATION; METABOLOME; ABUNDANCE; CANCER; Microbial load; Spike-in bacteria; 16S rRNA gene sequencing; Standardization; Microbiome profiling; Bacterial communities; Community analysis |
Subjects: | 600 Technology > 610 Medical sciences Medicine |
Divisions: | Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner) Medicine > Lehrstuhl für Innere Medizin III (Hämatologie und Internistische Onkologie) Medicine > Lehrstuhl für Medizinische Mikrobiologie und Hygiene Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang) |
Depositing User: | Dr. Gernot Deinzer |
Date Deposited: | 08 Apr 2019 09:08 |
Last Modified: | 08 Apr 2019 09:08 |
URI: | https://pred.uni-regensburg.de/id/eprint/3754 |
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