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Int J Med Microbiol. 2016 Aug;306(5):343-355. doi: 10.1016/j.ijmm.2016.03.004. Epub 2016 Mar 15.

Analysis of factors contributing to variation in the C57BL/6J fecal microbiota across German animal facilities.

Author information

1
Max Planck Institute for Evolutionary Biology, Evolutionary Genomics, August-Thienemann-Str. 2, 24306, Plön, Germany; Institute for Experimental Medicine, Evolutionary Genomics, Christian-Albrechts-University of Kiel, Arnold-Heller-Str. 3, Haus 17, 24105 Kiel, Germany.
2
Institute for Laboratory Animal Science and Central Animal Facility, Hannover Medical School, Carl-Neuberg-Str.1, 30625 Hannover, Germany.
3
Charité-Universitätsklinikum Berlin, Medical Department, Division of Gastroenterology, Infectiology and Rheumatology, Hindenburgdamm 30, 12203 Berlin, Germany.
4
Department of Nutritional Medicine, University of Hohenheim, Fruwirthstr. 12, 70593 Stuttgart, Germany.
5
Department of Gastrointestinal Microbiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558, Nuthetal, Germany.
6
ZIEL Institute for Food and Health, Technische Universität München, Gregor-Mendel-Str. 2, 85354, Freising-Weihenstephan, Germany.
7
Institute for Medical Microbiology and Hygiene, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany.
8
Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Arnold-Heller-Str. 3, 24105 Kiel, Germany.
9
German Center for Infection Research (DZIF), Hannover-Braunschweig Site, Carl-Neuberg-Str. 1, 30625 Hannover, Germany; Institute of Medical Microbiology and Hospital Epidemiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625 Hannover, Germany; Research Center Borstel, Parkallee 1-40, 23845, Borstel, Germany.
10
Medical Clinic 1, Friedrich Alexander University, Ulmenweg 18, 91054 Erlangen, Germany.
11
ZIEL Institute for Food and Health, Technische Universität München, Gregor-Mendel-Str. 2, 85354, Freising-Weihenstephan, Germany; Chair of Nutrition and Immunology, Technische Universität München, Gregor-Mendel-Str. 2, 85354 Freising-Weihenstephan, Germany.
12
Lübeck Institute of Experimental Dermatology, University of Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany.
13
Mikrobiologisches Institut - Klinische Mikrobiologie, Immunologie und Hygiene, Lehrstuhl für Mikrobiologie und Infektionsimmunologie, Wasserturmstr. 3/5, 91054 Erlangen, Germany.
14
Charité - Universitätsklinikum Berlin, Research Institutes for Experimental Medicine, Krahmerstr. 6-10, 12207 Berlin, Germany.
15
Institute of Molecular Medicine, RWTH University, Pauwelsstraße 30, 52074, Aachen, Germany.
16
Helmholtz Centre for Infection Research, Inhoffenstraße 7, 38124 Braunschweig, Germany.
17
Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Arnold-Heller-Str. 3, 24105 Kiel, Germany; Department of Medicine I, University Medical Center Dresden and Center for Regenerative Therapies, Technical University Dresden, 01307 Dresden, Germany.
18
Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Arnold-Heller-Str. 3, 24105 Kiel, Germany; Department of General Pediatrics, University Medical Center Dresden, Technical University Dresden, 01307 Dresden, Germany.
19
Max Planck Institute for Evolutionary Biology, Evolutionary Genomics, August-Thienemann-Str. 2, 24306, Plön, Germany; Institute for Experimental Medicine, Evolutionary Genomics, Christian-Albrechts-University of Kiel, Arnold-Heller-Str. 3, Haus 17, 24105 Kiel, Germany. Electronic address: baines@evolbio.mpg.de.

Abstract

The intestinal microbiota is involved in many physiological processes and it is increasingly recognized that differences in community composition can influence the outcome of a variety of murine models used in biomedical research. In an effort to describe and account for the variation in intestinal microbiota composition across the animal facilities of participating members of the DFG Priority Program 1656 "Intestinal Microbiota", we performed a survey of C57BL/6J mice from 21 different mouse rooms/facilities located at 13 different institutions across Germany. Fresh feces was sampled from five mice per room/facility using standardized procedures, followed by extraction and 16S rRNA gene profiling (V1-V2 region, Illumina MiSeq) at both the DNA and RNA (reverse transcribed to cDNA) level. In order to determine the variables contributing to bacterial community differences, we collected detailed questionnaires of animal husbandry practices and incorporated this information into our analyses. We identified considerable variation in a number of descriptive aspects including the proportions of major phyla, alpha- and beta diversity, all of which displayed significant associations to specific aspects of husbandry. Salient findings include a reduction in alpha diversity with the use of irradiated chow, an increase in inter-individual variability (beta diversity) with respect to barrier access and open cages and an increase in bacterial community divergence with time since importing from a vendor. We further observe a high degree of facility-level individuality, which is likely due to each facility harboring its own unique combination of multiple varying attributes of animal husbandry. While it is important to account and control for such differences between facilities, the documentation of such diversity may also serve as a valuable future resource for investigating the origins of microbial-driven host phenotypes.

KEYWORDS:

16S rRNA gene; C57BL/6J; Gut microbiota; Mouse husbandry

PMID:
27053239
DOI:
10.1016/j.ijmm.2016.03.004
[Indexed for MEDLINE]
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