Evidence map›Paper›PMID 27306663›Full record

ArticleScience translational medicine2016

Natural history of the infant gut microbiome and impact of antibiotic treatment on bacterial strain diversity and stability.

Moran Yassour, Tommi Vatanen, Heli Siljander, Anu-Maaria Hämäläinen, Taina Härkönen, Samppa J Ryhänen, Eric A Franzosa, Hera Vlamakis, Curtis Huttenhower, Dirk Gevers and 4 more

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In one paragraph

Article in Science translational medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 600 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
600citing papers in PubMed, 7 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

600 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  7. Vitamin DBMC infectious diseases · 2023
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540 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Moran YassourBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Cambridge, MA 02142, USA. Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.
Tommi VatanenBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Cambridge, MA 02142, USA. Department of Computer Science, Aalto University School of Science, 02150 Espoo, Finland.
Heli SiljanderChildren's Hospital, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland. Research Programs Unit, Diabetes and Obesity, University of Helsinki, 00290 Helsinki, Finland. Department of Pediatrics, Tampere University Hospital, 33521 Tampere, Finland.
Anu-Maaria HämäläinenDepartment of Pediatrics, Jorvi Hospital, Helsinki University Hospital, 02740 Espoo, Finland.
Taina HärkönenChildren's Hospital, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland. Research Programs Unit, Diabetes and Obesity, University of Helsinki, 00290 Helsinki, Finland.
Samppa J RyhänenChildren's Hospital, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland. Research Programs Unit, Diabetes and Obesity, University of Helsinki, 00290 Helsinki, Finland.
Eric A FranzosaDepartment of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.
Hera VlamakisBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Cambridge, MA 02142, USA.
Curtis HuttenhowerBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Cambridge, MA 02142, USA. Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.
Dirk GeversBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Cambridge, MA 02142, USA.
Eric S LanderBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Cambridge, MA 02142, USA. Department of Biology, MIT, Cambridge, MA 02139, USA. Department of Systems Biology, Harvard Medical School, Boston, MA 02114, USA.
Mikael KnipChildren's Hospital, University of Helsinki and Helsinki University Hospital, 00290 Helsinki, Finland. Research Programs Unit, Diabetes and Obesity, University of Helsinki, 00290 Helsinki, Finland. Department of Pediatrics, Tampere University Hospital, 33521 Tampere, Finland. Folkhälsan Research Center, 00290 Helsinki, Finland.
DIABIMMUNE Study Group
Ramnik J XavierBroad Institute of Massachusetts Institute of Technology (MIT) and Harvard University, Cambridge, MA 02142, USA. Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA. Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA. Center for Microbiome Informatics and Therapeutics, MIT, Cambridge, MA 02139, USA. xavier@molbio.mgh.harvard.edu.

Funding

Large Scale Sequencing and Analysis of GenomesU54HG003067 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GABRIEL, STACEY, LANDER, ERIC S · 2004 to 2015
$568.6M
Pilot & Feasibility ProgramP30DK043351 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI RAYMOND T CHUNG · 1991 to 2026
$35.3M
Characterizing the gut microbial ecosystem for diagnosis and therapy in IBDU54DK102557 · NIDDK · BROAD INSTITUTE, INC. · PI HUTTENHOWER, CURTIS, XAVIER, RAMNIK J · 2014 to 2015
$7.7M
Toll-like Receptors and the Intestinal EpitheliumR01DK060049 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI XAVIER, RAMNIK J · 2002 to 2011
$3.5M
Autophagy genes and the microbiome in Crohn's DiseaseR01DK092405 · NIDDK · BROAD INSTITUTE, INC. · PI XAVIER, RAMNIK J · 2012 to 2014
$2.0M
Genomic Approaches to Host-Pathogen InteractionsR01AI062773 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI XAVIER, RAMNIK J · 2006 to 2009
$1.4M
NHGRI NIH HHS U54 HG003067NIAID NIH HHS R01 AI062773NIDDK NIH HHS P30 DK043351NIDDK NIH HHS R01 DK060049NIDDK NIH HHS R01 DK092405NIDDK NIH HHS U54 DK102557
6 · The paper itself

Abstract

The gut microbial community is dynamic during the first 3 years of life, before stabilizing to an adult-like state. However, little is known about the impact of environmental factors on the developing human gut microbiome. We report a longitudinal study of the gut microbiome based on DNA sequence analysis of monthly stool samples and clinical information from 39 children, about half of whom received multiple courses of antibiotics during the first 3 years of life. Whereas the gut microbiome of most children born by vaginal delivery was dominated by Bacteroides species, the four children born by cesarean section and about 20% of vaginally born children lacked Bacteroides in the first 6 to 18 months of life. Longitudinal sampling, coupled with whole-genome shotgun sequencing, allowed detection of strain-level variation as well as the abundance of antibiotic resistance genes. The microbiota of antibiotic-treated children was less diverse in terms of both bacterial species and strains, with some species often dominated by single strains. In addition, we observed short-term composition changes between consecutive samples from children treated with antibiotics. Antibiotic resistance genes carried on microbial chromosomes showed a peak in abundance after antibiotic treatment followed by a sharp decline, whereas some genes carried on mobile elements persisted longer after antibiotic therapy ended. Our results highlight the value of high-density longitudinal sampling studies with high-resolution strain profiling for studying the establishment and response to perturbation of the infant gut microbiome.

Indexed as

Anti-Bacterial AgentsBacteroidesCesarean SectionChild, PreschoolDrug Resistance, MicrobialFemaleGastrointestinal MicrobiomeGastrointestinal TractHumansInfantInfant, NewbornLongitudinal StudiesMaleAnti-Bacterial Agents

Identifiers

PMID27306663
PMCPMC5032909

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.