Evidence map›Paper›PMID 26280120›Full record

ArticleNature medicine2015

In vivo imaging and tracking of host-microbiota interactions via metabolic labeling of gut anaerobic bacteria.

Naama Geva-Zatorsky, David Alvarez, Jason E Hudak, Nicola C Reading, Deniz Erturk-Hasdemir, Suryasarathi Dasgupta, Ulrich H von Andrian, Dennis L Kasper

Abstract read
In one paragraph

Article in Nature medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers.

0numbers the graph read from it
0cells of the map it votes in
124citing papers in PubMed
–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

124 citing papers in PubMed.

  1. Article
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  5. Article
  6. AssessingACS infectious diseases · 2026
    Article
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  10. Gut microbes · 2025
    Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review

64 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Naama Geva-ZatorskyDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA.
David AlvarezDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA.
Jason E HudakDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA.
Nicola C ReadingDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA.
Deniz Erturk-HasdemirDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA.
Suryasarathi DasguptaDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA.
Ulrich H von AndrianDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA.
Dennis L KasperDepartment of Microbiology and Immunobiology, Harvard Medical School, Boston, Massachusetts, USA.

Funding

STRUCTURE-FUNCTION RELATIONSHIPS IN THE ALIMENTARY TRACTP30DK034854 · NIDDK · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI Scott B Snapper · 1986 to 2026
$32.4M
INFECTIOUS DISEASE AND BASIC MICROBIOLOGICAL MECHANISMST32AI007061 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI Marcia B Goldberg · 1985 to 2026
$12.1M
Tetramer CoreU19AI095261 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI HAMILOS, DANIEL L. · 2011 to 2015
$10.8M
TRANSFUSION BIOLOGY AND MEDICINET32HL066987 · NHLBI · CHILDREN'S HOSPITAL BOSTON · PI JOHN P MANIS · 2001 to 2026
$10.2M
P3: Chemokine-Mediated T Cell Trafficking in HIV Transmission and Immune ResponseP01AI112521 · NIAID · HARVARD MEDICAL SCHOOL · PI VON ANDRIAN, ULRICH H · 2014 to 2018
$9.8M
Super-Resolution ImagingP30NS072030 · NINDS · HARVARD MEDICAL SCHOOL · PI SABATINI, BERNARDO L · 2011 to 2020
$5.8M
Generation and Function of NK Cell MemoryR01AI111595 · NIAID · HARVARD MEDICAL SCHOOL · PI VON ANDRIAN, ULRICH H · 2013 to 2017
$4.1M
IVIS Spectrum for In Vivo ImagingS10OD016401 · OD · BOSTON CHILDREN'S HOSPITAL · PI LIEBERMAN, JUDY · 2013 to 2013
$418k
NHLBI NIH HHS 5T32 HL066987NHLBI NIH HHS T32 HL066987NIAID NIH HHS P01 AI1112521NIAID NIH HHS P01 AI112521NIAID NIH HHS R01 AI111595NIAID NIH HHS T32 AI007061NIAID NIH HHS U19 AI095261NIAID NIH HHS U19AI095261NIDDK NIH HHS P30 DK034854NIH HHS 1 S10 OD016401NIH HHS S10 OD016401NINDS NIH HHS P30 NS072030
6 · The paper itself

Abstract

The intestine is densely populated by anaerobic commensal bacteria. These microorganisms shape immune system development, but understanding of host-commensal interactions is hampered by a lack of tools for studying the anaerobic intestinal environment. We applied metabolic oligosaccharide engineering and bioorthogonal click chemistry to label various commensal anaerobes, including Bacteroides fragilis, a common and immunologically important commensal. We studied the dissemination of B. fragilis after acute peritonitis and characterized the interactions of the intact microbe and its polysaccharide components in myeloid and B cell lineages. We were able to assess the distribution and colonization of labeled B. fragilis along the intestine, as well as niche competition after coadministration of multiple species of the microbiota. We also fluorescently labeled nine additional commensals (eight anaerobic and one microaerophilic) from three phyla common in the gut--Bacteroidetes, Firmicutes and Proteobacteria--as well as one aerobic pathogen (Staphylococcus aureus). This strategy permits visualization of the anaerobic microbial niche by various methods, including intravital two-photon microscopy and non-invasive whole-body imaging, and can be used to study microbial colonization and host-microbe interactions in real time.

Indexed as

MicrobiotaAnimalsBacteria, AnaerobicBacteroides fragilisFemaleFluorescent DyesGlycocalyxIntestinesMaleMiceMice, Inbred C57BLPeritonitisFluorescent Dyes

Identifiers

PMID26280120
PMCPMC4694768

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.