Evidence map›Paper›PMID 40742180›Full record

ArticlemSystems2025

Metagenomic estimation of absolute bacterial biomass in the mammalian gut through host-derived read normalization.

Gechlang Tang, Alex V Carr, Crystal Perez, Katherine Ramos Sarmiento, Lisa Levy, Johanna W Lampe, Christian Diener, Sean M Gibbons

Abstract read
In one paragraph

Article in mSystems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Improving immune-related health outcomes post-cesarean birth with a gut microbiome-based program: A randomized controlled trial.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2025
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  10. A foundation model for microbial growth dynamics.bioRxiv : the preprint server for biology · 2025
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Gechlang TangInstitute for Systems Biology, Seattle, Washington, USA.ORCID 0009-0007-2745-7114
Alex V CarrInstitute for Systems Biology, Seattle, Washington, USA.
Crystal PerezInstitute for Systems Biology, Seattle, Washington, USA.
Katherine Ramos SarmientoInstitute for Systems Biology, Seattle, Washington, USA.
Lisa LevyFred Hutchinson Cancer Center, Seattle, Washington, USA.
Johanna W LampeFred Hutchinson Cancer Center, Seattle, Washington, USA.
Christian DienerDiagnostic and Research Institute of Hygiene, Microbiology and Environmental Medicine, Medical University of Graz, Graz, Austria.
Sean M GibbonsInstitute for Systems Biology, Seattle, Washington, USA.ORCID 0000-0002-8724-7916

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Eric Collisson · 1985 to 2026
$296.4M
University of Washington Medical Scientist Training Program: MD/PhDT32GM007266 · NIGMS · UNIVERSITY OF WASHINGTON · PI HORWITZ, MARSHALL S. · 1985 to 2023
$30.4M
CyberGut: towards personalized human-microbiome metabolic modeling for precision health and nutritionR01DK133468 · NIDDK · INSTITUTE FOR SYSTEMS BIOLOGY · PI Sean Michael Gibbons · 2022 to 2026
$3.6M
HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) R01DK133468NCI NIH HHS P30 CA015704NIDDK NIH HHS R01 DK133468NIGMS NIH HHS T32 GM007266
6 · The paper itself

Abstract

Absolute bacterial biomass estimation in the human gut is crucial for understanding microbiome dynamics and host-microbe interactions. Current methods for quantifying bacterial biomass in stool, such as flow cytometry, quantitative polymerase chain reaction (qPCR), or spike-ins, can be labor-intensive, costly, and confounded by factors like water content, DNA extraction efficiency, PCR inhibitors, and other technical challenges that add bias and noise. We propose a simple, cost-effective approach that circumvents some of these technical challenges: directly estimating bacterial biomass from metagenomes using bacterial-to-host (B:H) read count ratios. We compared B:H ratios to the standard methods outlined above, demonstrating that B:H ratios are useful proxies for bacterial biomass in stool and possibly in other host-associated substrates. B:H ratios in stool were correlated with bacterial-to-diet (B:D) read count ratios, but B:D ratios exhibited a substantial number of outlier points. Host read depletion methods reduced the total number of human reads in a given sample, but B:H ratios were strongly correlated before and after host read depletion, indicating that host read depletion did not reduce the utility of B:H ratios. B:H ratios showed expected variation between health and disease states and were generally stable in healthy individuals over time. Finally, we showed how B:H and B:D ratios can be used to track antibiotic treatment response and recovery. B:H ratios offer a convenient alternative to other absolute biomass quantification methods, without the need for additional measurements, experimental design considerations, or machine learning, enabling robust absolute biomass estimates directly from stool metagenomic data.IMPORTANCEIn this study, we asked whether normalization by host reads alone was sufficient to estimate absolute bacterial biomass directly from stool metagenomic data, without the need for synthetic spike-ins, additional experimental biomass measurements, or training data. The approach assumes that the contribution of host DNA to stool is more constant or stable than biologically relevant fluctuations in bacterial biomass. We find that host read normalization is an effective method for detecting variation in gut bacterial biomass. Absolute bacterial biomass is a key metric that often gets left out of gut microbiome studies, and empowering researchers to include this measure more broadly in their metagenomic analyses should serve to improve our understanding of host-microbiota interactions.

Indexed as

BacteriaGastrointestinal MicrobiomeMetagenomeMetagenomicsAnimalsBiomassFecesHost Microbial InteractionsHumansabsolute biomassdiet DNAgut microbiomehost DNAhuman microbiomemetagenomics

Identifiers

PMID40742180
PMCPMC12363224

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.