Evidence map›Paper›PMID 33980856›Full record

ArticleNature communications2021

Feeding-induced resistance to acute lethal sepsis is dependent on hepatic BMAL1 and FXR signalling.

Sarah S Geiger, Javier Traba, Nathan Richoz, Taylor K Farley, Stephen R Brooks, Franziska Petermann, Lingdi Wang, Frank J Gonzalez, Michael N Sack, Richard M Siegel

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

23 citing papers in PubMed, 31 citations in OpenAlex.

  1. Review
  2. Circadian clock and cancer.Military Medical Research · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 3 countries.

Sarah S GeigerImmunoregulation Section, Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health, Bethesda, MD, USA. sarah.geiger@dkfz-heidelberg.de.
Javier TrabaLaboratory of Mitochondrial Biology and Metabolism, National Heart Lung and Blood Institute (NHLBI), National Institutes of Health, Bethesda, MD, USA.
Nathan RichozImmunoregulation Section, Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health, Bethesda, MD, USA.
Taylor K FarleyImmunoregulation Section, Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health, Bethesda, MD, USA.
Stephen R BrooksBiodata Mining and Discovery Section, Office of Science and Technology, NIAMS, NIH, Bethesda, MD, USA.
Franziska PetermannLymphocyte Cell Biology Section, Molecular Immunology and Inflammation Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health, Bethesda, MD, USA.
Lingdi WangLaboratory of Mitochondrial Biology and Metabolism, National Heart Lung and Blood Institute (NHLBI), National Institutes of Health, Bethesda, MD, USA.
Frank J GonzalezLaboratory of Metabolism, National Cancer Institute (NCI), National Institutes of Health, Bethesda, MD, USA.ORCID 0000-0002-7990-2140
Michael N SackLaboratory of Mitochondrial Biology and Metabolism, National Heart Lung and Blood Institute (NHLBI), National Institutes of Health, Bethesda, MD, USA.
Richard M SiegelImmunoregulation Section, Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institutes of Health, Bethesda, MD, USA. richard.siegel@novartis.com.
National Institutes of Health · USOffice of Science · US

Funding

Xenobiotic receptorsZIABC005562 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI GONZALEZ, FRANK J · 2009 to 2025
$26.9M
Xenobiotic ReceptorsZIABC005708 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI GONZALEZ, FRANK J · 2009 to 2025
$16.4M
Applying Bioinformatics to Research in Immune, Muscle, and Bone DiseasesZICAR041173 · NIAMS · NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES · PI SUN, HONG-WEI · 2021 to 2025
$10.3M
Wellcome Trust
6 · The paper itself

Abstract

In mice, time of day strongly influences lethality in response to LPS, with survival greatest at the beginning compared to the end of the light cycle. Here we show that feeding, rather than light, controls time-of-day dependent LPS sensitivity. Mortality following LPS administration is independent of cytokine production and the clock regulator BMAL1 expressed in myeloid cells. In contrast, deletion of BMAL1 in hepatocytes globally disrupts the transcriptional response to the feeding cycle in the liver and results in constitutively high LPS sensitivity. Using RNAseq and functional validation studies we identify hepatic farnesoid X receptor (FXR) signalling as a BMAL1 and feeding-dependent regulator of LPS susceptibility. These results show that hepatocyte-intrinsic BMAL1 and FXR signalling integrate nutritional cues to regulate survival in response to innate immune stimuli. Understanding hepatic molecular programmes operational in response to these cues could identify novel pathways for targeting to enhance endotoxemia resistance.

Indexed as

AnimalsARNTL Transcription FactorsCircadian RhythmDisease Models, AnimalDisease ResistanceFeeding BehaviorHepatocytesHypoglycemiaLipopolysaccharidesLiverMiceMice, KnockoutReceptor, Farnesoid X-ActivatedReceptors, Cytoplasmic and NuclearSepsisSignal TransductionARNTL Transcription FactorsBmal1 protein, mouseLipopolysaccharidesReceptor, Farnesoid X-ActivatedReceptors, Cytoplasmic and Nuclear

Identifiers

PMID33980856
PMCPMC8115055
OpenAlexW3160256011

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.