Colonic transit time is related to bacterial metabolism and mucosal turnover in the gut

Colonic transit time is related to bacterial metabolism and mucosal turnover in the gut


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ABSTRACT Little is known about how colonic transit time relates to human colonic metabolism and its importance for host health, although a firm stool consistency, a proxy for a long colonic


transit time, has recently been positively associated with gut microbial richness. Here, we show that colonic transit time in humans, assessed using radio-opaque markers, is associated with


overall gut microbial composition, diversity and metabolism. We find that a long colonic transit time associates with high microbial richness and is accompanied by a shift in colonic


metabolism from carbohydrate fermentation to protein catabolism as reflected by higher urinary levels of potentially deleterious protein-derived metabolites. Additionally, shorter colonic


transit time correlates with metabolites possibly reflecting increased renewal of the colonic mucosa. Together, this suggests that a high gut microbial richness does not _per se_ imply a


healthy gut microbial ecosystem and points at colonic transit time as a highly important factor to consider in microbiome and metabolomics studies. Access through your institution Buy or


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May 2023 REFERENCES * Le Chatelier, E. _et al._ Richness of human gut microbiome correlates with metabolic markers. _Nature_ 500, 541–546 (2013). Article  Google Scholar  * Lozupone, C. A.,


Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. _Nature_ 489, 220–230 (2012). Article  Google Scholar  *


Vandeputte, D. _et al._ Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates. _Gut_ 65, 57–62 (2015). Article  Google


Scholar  * Tigchelaar, E. F. _et al._ Gut microbiota composition associated with stool consistency. _Gut_ 65, 540–542 (2016). Article  Google Scholar  * Wang, Y. T. _et al._ Regional


gastrointestinal transit and pH studied in 21 healthy volunteers using the wireless motility capsule: influence of age, gender, study country and testing protocol. _Aliment. Pharmacol.


Ther._ 42, 761–772 (2015). Article  Google Scholar  * Nyangale, E. P., Mottram, D. S. & Gibson, G. R. Gut microbial activity, implications for health and disease: the potential role of


metabolite analysis. _J. Proteome Res._ 11, 5573–5585 (2012). Article  Google Scholar  * Tremaroli, V. & Bäckhed, F. Functional interactions between the gut microbiota and host


metabolism. _Nature_ 489, 242–249 (2012). Article  Google Scholar  * Davila, A.-M. _et al._ Intestinal luminal nitrogen metabolism: role of the gut microbiota and consequences for the host.


_Pharmacol. Res._ 68, 95–107 (2013). Article  Google Scholar  * Russell, W. R., Hoyles, L., Flint, H. J. & Dumas, M.-E. Colonic bacterial metabolites and human health. _Curr. Opin.


Microbiol._ 16, 246–254 (2013). Article  Google Scholar  * Andriamihaja, M. _et al._ The deleterious metabolic and genotoxic effects of the bacterial metabolite p-cresol on colonic


epithelial cells. _Free Radic. Biol. Med._ 85, 219–227 (2015). Article  Google Scholar  * Louis, P., Hold, G. L. & Flint, H. J. The gut microbiota, bacterial metabolites and colorectal


cancer. _Nature Rev. Microbiol._ 12, 661–672 (2014). Article  Google Scholar  * Shafi, T. _et al._ Free levels of selected organic solutes and cardiovascular morbidity and mortality in


hemodialysis patients: results from the retained organic solutes and clinical outcomes (ROSCO) investigators. _PLoS ONE_ 10, e0126048 (2015). Article  Google Scholar  * Gabriele, S. _et al._


Urinary p-cresol is elevated in young French children with autism spectrum disorder: a replication study. _Biomarkers_ 19, 463–470 (2014). Article  Google Scholar  * Ibrügger, S. _et al._


Two randomized cross-over trials assessing the impact of dietary gluten or wholegrain on the gut microbiome and host metabolic health. _J. Clin. Trials_ 4, 1000178 (2014). Article  Google


Scholar  * Falony, G. _et al._ Population-level analysis of gut microbiome variation. _Science_ 352, 560–564 (2016). Article  Google Scholar  * Arumugam, M. _et al._ Enterotypes of the human


gut microbiome. _Nature_ 473, 174–180 (2011). Article  Google Scholar  * Roager, H. M., Licht, T. R., Poulsen, S. K., Larsen, T. M. & Bahl, M. I. Microbial enterotypes, inferred by the


prevotella-to-bacteroides ratio, remained stable during a 6-month randomized controlled diet intervention with the new nordic diet. _Appl. Environ. Microbiol._ 80, 1142–1149 (2014). Article


  Google Scholar  * Claus, S. P. _et al._ Systemic multicompartmental effects of the gut microbiome on mouse metabolic phenotypes. _Mol. Syst. Biol._ 4, 219 (2008). Article  Google Scholar 


* He, X. & Slupsky, C. M. Metabolic fingerprint of dimethyl sulfone (DMSO2) in microbial-mammalian co-metabolism. _J. Proteome Res._ 13, 5281–5292 (2014). Article  Google Scholar  *


Kilkkinen, A. _et al._ Use of oral antimicrobials decreases serum enterolactone concentration. _Am. J. Epidemiol._ 155, 472–477 (2002). Article  Google Scholar  * Topp, H., Sander, G.,


Heller-Schöch, G. & Schöch, G. Determination of 7-methylguanine, _N_2,_N_2-dimethylguanosine, and pseudouridine in ultrafiltrated serum of healthy adults by high-performance liquid


chromatography. _Anal. Biochem._ 161, 49–56 (1987). Article  Google Scholar  * Topp, H. & Schöch, G. Whole-body degradation rates of transfer-, ribosomal-, and messenger ribonucleic


acids and resting metabolic rate in 3- to 18-year-old humans. _Pediatr. Res._ 47, 163–163 (2000). Article  Google Scholar  * Mirvish, S. S., Medalie, J., Linsell, C. A., Yousuf, E. &


Reyad, S. 7-methylguanine and other minor urinary purines: values for normal subjects from Israel, Gaza, and Kenya, and for patients with cancer of various organs or cirrhosis of the liver.


_Cancer_ 27, 736–743 (1971). Article  Google Scholar  * Johansson, M. E. V., Larsson, J. M. H. & Hansson, G. C. The two mucus layers of colon are organized by the MUC2 mucin, whereas the


outer layer is a legislator of host–microbial interactions. _Proc. Natl Acad. Sci. USA_ 108(Suppl), 4659–4665 (2011). Article  CAS  Google Scholar  * Barrios, C. _et al._


Gut-microbiota-metabolite axis in early renal function decline. _PLoS ONE_ 10, e0134311 (2015). Article  Google Scholar  * Pimentel, M. _et al._ Methane, a gas produced by enteric bacteria,


slows intestinal transit and augments small intestinal contractile activity. _Am. J. Physiol. Gastrointest. Liver Physiol._ 290, G1089–G1095 (2006). Article  Google Scholar  * Soret, R. _et


al._ Short-chain fatty acids regulate the enteric neurons and control gastrointestinal motility in rats. _Gastroenterology_ 138, 1772–1782 (2010). Article  Google Scholar  * Degen, L. P.


& Phillips, S. F. How well does stool form reflect colonic transit? _Gut_ 39, 109–113 (1996). Article  Google Scholar  * Macfarlane, G. T., Cummings, J. H., Macfarlane, S. & Gibson,


G. R. Influence of retention time on degradation of pancreatic enzymes by human colonic bacteria grown in a 3-stage continuous culture system. _J. Appl. Bacteriol._ 67, 520–527 (1989).


Article  Google Scholar  * Macfarlane, S., Quigley, M., Hopkins, M., Newton, D. F. & Macfarlane, G. Polysaccharide degradation by human intestinal bacteria during growth under


multi-substrate limiting conditions in a three-stage continuous culture system. _FEMS Microbiol. Ecol._ 26, 231–243 (1998). Article  Google Scholar  * Cummings, J. H., Hill, M. J., Bone, E.


S., Branch, W. J. & Jenkins, D. J. The effect of meat protein and dietary fiber on colonic function and metabolism. II: Bacterial metabolites in feces and urine. _Am. J. Clin. Nutr._ 32,


2094–2101 (1979). Article  Google Scholar  * Benus, R. F. J. _et al._ Association between _Faecalibacterium prausnitzii_ and dietary fibre in colonic fermentation in healthy human subjects.


_Br. J. Nutr._ 104, 693–700 (2010). Article  Google Scholar  * Manach, C., Scalbert, A., Morand, C., Remesy, C. & Jimenez, L. Polyphenols: food sources and bioavailability. _Am. J.


Clin. Nutr._ 79, 727–747 (2004). Article  Google Scholar  * van Duynhoven, J. _et al._ Metabolic fate of polyphenols in the human superorganism. _Proc. Natl Acad. Sci. USA_ 108(Suppl),


4531–4538 (2011). Article  CAS  Google Scholar  * Gross, G. _et al._ _In vitro_ bioconversion of polyphenols from black tea and red wine/grape juice by human intestinal microbiota displays


strong interindividual variability. _J. Agric. Food Chem._ 58, 10236–10246 (2010). Article  Google Scholar  * Bode, L. M. _et al._ _In vivo_ and _in vitro_ metabolism of trans-resveratrol by


human gut microbiota. _Am. J. Clin. Nutr._ 97, 295–309 (2013). Article  Google Scholar  * Shimotoyodome, A., Meguro, S., Hase, T., Tokimitsu, I. & Sakata, T. Decreased colonic mucus in


rats with loperamide-induced constipation. _Comp. Biochem. Physiol. A. Mol. Integr. Physiol._ 126, 203–212 (2000). Article  Google Scholar  * Toden, S., Bird, A. R., Topping, D. L. &


Conlon, M. A. Resistant starch attenuates colonic DNA damage induced by higher dietary protein in rats. _Nutr. Cancer_ 51, 45–51 (2005). Article  Google Scholar  * Ten Bruggencate, S. J. M.,


Bovee-Oudenhoven, I. M. J., Lettink-Wissink, M. L. G., Katan, M. B. & Van Der Meer, R. Dietary fructo-oligosaccharides and inulin decrease resistance of rats to salmonella: protective


role of calcium. _Gut_ 53, 530–535 (2004). Article  Google Scholar  * Rao, J. N. & Wang, J.-Y. in _Molecule to Function to Disease_ (eds Granger, N., Granger, J. & Princeton, N. )


11–114 (Morgan & Claypool, 2011). Google Scholar  * Sakata, T. Effects of indigestible dietary bulk and short chain fatty acids on the tissue weight and epithelial cell proliferation


rate of the digestive tract in rats. _J. Nutr. Sci. Vitaminol. (Tokyo)_ 32, 355–362 (1986). Article  Google Scholar  * Goodlad, R. A. _et al._ Effects of an elemental diet, inert bulk and


different types of dietary fibre on the response of the intestinal epithelium to refeeding in the rat and relationship to plasma gastrin, enteroglucagon, and PYY concentrations. _Gut_ 28,


171–180 (1987). Article  Google Scholar  * Lewis, S. J. & Heaton, K. W. Increasing butyrate concentration in the distal colon by accelerating intestinal transit. _Gut_ 41, 245–251


(1997). Article  Google Scholar  * Timmons, J., Chang, E. T., Wang, J.-Y. & Rao, J. N. Polyamines and gut mucosal homeostasis. _J. Gastrointest. Dig. Syst._ 2(Suppl 7), 001 (2012).


PubMed  PubMed Central  Google Scholar  * Earle, K. A. _et al._ Quantitative imaging of gut microbiota spatial organization. _Cell Host Microbe_ 18, 478–488 (2015). Article  Google Scholar 


* Guérin, A. _et al._ Risk of developing colorectal cancer and benign colorectal neoplasm in patients with chronic constipation. _Aliment. Pharmacol. Ther._ 40, 83–92 (2014). Article  Google


Scholar  * Schadt, S., Chen, L.-Z. & Bischoff, D. Evaluation of relative LC/MS response of metabolites to parent drug in LC/nanospray ionization mass spectrometry: potential


implications in MIST assessment. _J. Mass Spectrom._ 46, 1281–1286 (2011). Article  Google Scholar  * McKeown, C., Hisle-Gorman, E., Eide, M., Gorman, G. H. & Nylund, C. M. Association


of constipation and fecal incontinence with attention-deficit/hyperactivity disorder. _Pediatrics_ 132, e1210-5 (2013). Article  Google Scholar  * Pang, K. H. & Croaker, G. D. H.


Constipation in children with autism and autistic spectrum disorder. _Pediatr. Surg. Int._ 27, 353–358 (2011). Article  Google Scholar  * Wu, M.-J. _et al._ Colonic transit time in long-term


dialysis patients. _Am. J. Kidney Dis._ 44, 322–327 (2004). Article  Google Scholar  * Waller, P. A. _et al._ Dose–response effect of _Bifidobacterium lactis_ HN019 on whole gut transit


time and functional gastrointestinal symptoms in adults. _Scand. J. Gastroenterol._ 46, 1057–1064 (2011). Article  Google Scholar  * Abrahamsson, H. & Antov, S. Accuracy in assessment of


colonic transit time with particles: how many markers should be used? _Neurogastroenterol. Motil._ 22, 1164–1169 (2010). Article  Google Scholar  * Wesolowska-Andersen, A. _et al._ Choice


of bacterial DNA extraction method from fecal material influences community structure as evaluated by metagenomic analysis. _Microbiome_ 2, 19 (2014). Article  Google Scholar  * Godon, J.


J., Zumstein, E., Dabert, P., Habouzit, F. & Moletta, R. Molecular microbial diversity of an anaerobic digestor as determined by small-subunit rDNA sequence analysis. _Appl. Environ.


Microbiol._ 63, 2802–2813 (1997). Google Scholar  * 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._ 41, e1 (2013). Article  Google Scholar  * Edgar, R. C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. _Nature Methods_ 10,


996–998 (2013). Article  Google Scholar  * Haas, B. J. _et al._ Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. _Genome Res._ 21, 494–504


(2011). Article  Google Scholar  * Caporaso, J. G. _et al._ QIIME allows analysis of high-throughput community sequencing data. _Nature Methods_ 7, 335–336 (2010). Article  Google Scholar  *


Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. _Bioinformatics_ 26, 2460–2461 (2010). Article  Google Scholar  * McDonald, D. _et al._ An improved Greengenes


taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. _ISME J._ 6, 610–618 (2012). Article  Google Scholar  * Caporaso, J. G. _et al._ PyNAST: a


flexible tool for aligning sequences to a template alignment. _Bioinformatics_ 26, 266–267 (2010). Article  Google Scholar  * Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree:


computing large minimum evolution trees with profiles instead of a distance matrix. _Mol. Biol. Evol._ 26, 1641–1650 (2009). Article  Google Scholar  * Chen, Y. _et al._ Combination of


injection volume calibration by creatinine and MS signals’ normalization to overcome urine variability in LC-MS-based metabolomics studies. _Anal. Chem._ 85, 7659–7665 (2013). Article 


Google Scholar  * Want, E. J. _et al._ Global metabolic profiling procedures for urine using UPLC-MS. _Nature Protoc._ 5, 1005–1018 (2010). Article  Google Scholar  * Smith, C. A., Want, E.


J., O'Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. _Anal.


Chem._ 78, 779–787 (2006). Article  Google Scholar  * Wishart, D. S. _et al._ HMDB 3.0—The human metabolome database in 2013. _Nucleic Acids Res._ 41, D801–D807 (2013). Article  Google


Scholar  * Kim, S. ppcor: an R package for a fast calculation to semi-partial correlation coefficients. _Commun. Stat. Appl. Methods_ 22, 665–674 (2015). Google Scholar  * Benjamini, Y.


& Hochberg, Y. Controlling the false discovery rate—a practical and powerful approach to multiple testing. _J. R. Stat. Soc. Ser. B_ 57, 289–300 (1995). Google Scholar  * Warnes, G. R.


_et al._ gplots: various R programming tools for plotting data. R package version 2.16.0 (CRAN, 2015); http://cran.r-project.org/package=gplots * Oksanen, J. _et al._ vegan: community


ecology package. R package version 2.3.1 (CRAN, 2015); https://cran.r-project.org/package=vegan * Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R


language. _Bioinformatics_ 20, 289–290 (2004). Article  Google Scholar  Download references ACKNOWLEDGEMENTS The authors thank K.V. Vibefelt for helping out with DNA extraction and N. Bicen


for performing the PCR and sequencing. The sequencing was carried out by the DTU in-house facility (DTU Multi-Assay Core, DMAC), Technical University of Denmark. This work was funded by the


Danish Council for Strategic Research (grant no. 11-116163; Center for Gut, Grain and Greens), by the Technical University of Denmark and by the personal Danisco Award (to T.R.L.). The Novo


Nordisk Foundation Center for Basic Metabolic Research is an independent research centre at the University of Copenhagen and is partly funded by an unrestricted donation from the Novo


Nordisk Foundation. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * National Food Institute, Technical University of Denmark, DK-2860 Søborg, Denmark Henrik M. Roager, Martin I. Bahl, Henrik


L. Frandsen, Vera Carvalho & Tine R. Licht * Department of Systems Biology, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark Lea B. S. Hansen, Marlene D. Dalgaard, Damian R.


Plichta, Thomas Sicheritz-Pontén, H. Bjørn Nielsen & Ramneek Gupta * The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of


Copenhagen, DK-2200 København N, Denmark Rikke J. Gøbel, Henrik Vestergaard, Torben Hansen & Oluf Pedersen * Department of Radiology, Bispebjerg Hospital, DK-2400 København NV, Denmark


Morten H. Sparholt * Department of Nutrition, Exercise and Sport, University of Copenhagen, DK-1958 Frederiksberg C, Denmark Lotte Lauritzen & Mette Kristensen Authors * Henrik M. Roager


View author publications You can also search for this author inPubMed Google Scholar * Lea B. S. Hansen View author publications You can also search for this author inPubMed Google Scholar


* Martin I. Bahl View author publications You can also search for this author inPubMed Google Scholar * Henrik L. Frandsen View author publications You can also search for this author


inPubMed Google Scholar * Vera Carvalho View author publications You can also search for this author inPubMed Google Scholar * Rikke J. Gøbel View author publications You can also search for


this author inPubMed Google Scholar * Marlene D. Dalgaard View author publications You can also search for this author inPubMed Google Scholar * Damian R. Plichta View author publications


You can also search for this author inPubMed Google Scholar * Morten H. Sparholt View author publications You can also search for this author inPubMed Google Scholar * Henrik Vestergaard


View author publications You can also search for this author inPubMed Google Scholar * Torben Hansen View author publications You can also search for this author inPubMed Google Scholar *


Thomas Sicheritz-Pontén View author publications You can also search for this author inPubMed Google Scholar * H. Bjørn Nielsen View author publications You can also search for this author


inPubMed Google Scholar * Oluf Pedersen View author publications You can also search for this author inPubMed Google Scholar * Lotte Lauritzen View author publications You can also search


for this author inPubMed Google Scholar * Mette Kristensen View author publications You can also search for this author inPubMed Google Scholar * Ramneek Gupta View author publications You


can also search for this author inPubMed Google Scholar * Tine R. Licht View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS M.I.B., R.J.G.,


H.V., T.H., T.S.-P., O.P., L.L., M.K., R.G. and T.R.L. assembled the cohort and developed protocols and infrastructure to obtain the biological samples and clinical metadata. M.H.S. measured


the colonic transit time. L.B.S.H., V.C. and M.D.D. prepared the faecal samples, extracted DNA and performed 16S rRNA gene sequencing. L.B.S.H. performed the 16S data analyses, with


contributions from V.C. H.M.R. and H.L.F. prepared the urine samples, performed the urine metabolic profiling and identified the urinary metabolites. H.M.R. performed the statistical


correlation analyses with contributions from L.B.S.H., D.R.P. and H.B.N. H.M.R., M.I.B., H.B.N., L.B.S.H., T.S.-P., R.G., M.K. and T.R.L. interpreted the data. H.M.R. and T.R.L. wrote the


manuscript and all authors read, revised and approved the final manuscript. CORRESPONDING AUTHOR Correspondence to Tine R. Licht. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare


no competing financial interests. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Tables 1-6, Supplementary Figures 1-14 and Supplementary References. (PDF 2035 kb) RIGHTS


AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Roager, H., Hansen, L., Bahl, M. _et al._ Colonic transit time is related to bacterial metabolism and mucosal


turnover in the gut. _Nat Microbiol_ 1, 16093 (2016). https://doi.org/10.1038/nmicrobiol.2016.93 Download citation * Received: 15 December 2015 * Accepted: 20 May 2016 * Published: 27 June


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