title: Adjusting microbiome profiles for differences in microbial load by spike-in bacteria.
abstract: 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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: Chair of Statistical Bioinformatics, University of Regensburg, Am BioPark 9, 93053, Regensburg, Germany. Frank.Staemmler@klinik.uni-regensburg.de.|Institute of Clinical Microbiology and Hygiene, University Medical Centre, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany. Frank.Staemmler@klinik.uni-regensburg.de.
authors.forename: Frank
authors.identifier: 0000-0003-2841-0610
authors.initials: F
authors.lastname: Stämmler
authors.affiliation: Institute of Clinical Microbiology and Hygiene, University Medical Centre, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
authors.forename: Joachim
authors.initials: J
authors.lastname: Gläsner
authors.affiliation: Institute of Clinical Microbiology and Hygiene, University Medical Centre, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Hiergeist
authors.affiliation: Department of Haematology and Oncology, Internal Medicine III, University Medical Centre, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
authors.forename: Ernst
authors.initials: E
authors.lastname: Holler
authors.affiliation: Department of Haematology and Oncology, Internal Medicine III, University Medical Centre, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
authors.forename: Daniela
authors.initials: D
authors.lastname: Weber
authors.affiliation: Chair and Institute of Functional Genomics, University of Regensburg, Am BioPark 9, 93053, Regensburg, Germany.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Oefner
authors.affiliation: Institute of Clinical Microbiology and Hygiene, University Medical Centre, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
authors.forename: André
authors.initials: A
authors.lastname: Gessner
authors.affiliation: Chair of Statistical Bioinformatics, University of Regensburg, Am BioPark 9, 93053, Regensburg, Germany.
authors.forename: Rainer
authors.initials: R
authors.lastname: Spang
mesh_terms: D000818:Animals; D001419:Bacteria / Q000145:classification* / Q000235:genetics; D001431:Bacteriological Techniques / Q000379:methods; D004275:DNA, Ribosomal / Q000235:genetics; D005243:Feces / Q000382:microbiology*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D051379:Mice; D064307:Microbiota; D012336:RNA, Ribosomal, 16S / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*
chemical_list: D004275:DNA, Ribosomal; D012336:RNA, Ribosomal, 16S
keywords: 16S rRNA gene sequencing; Bacterial communities; Community analysis; Microbial load; Microbiome profiling; Spike-in bacteria; Standardization