Evidence map›Paper›PMID 39829744›Full record

ArticlebioRxiv : the preprint server for biology2025

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 readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Gechlang TangInstitute for Systems Biology, Seattle, WA 98109, USA.
Alex V CarrInstitute for Systems Biology, Seattle, WA 98109, USA.
Crystal PerezInstitute for Systems Biology, Seattle, WA 98109, USA.
Katherine Ramos SarmientoInstitute for Systems Biology, Seattle, WA 98109, USA.
Lisa LevyFred Hutchinson Cancer Center, Seattle, WA 98109, USA.
Johanna W LampeFred Hutchinson Cancer Center, Seattle, WA 98109, 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, WA 98109, 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
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
NCI NIH HHS P30 CA015704NIDDK NIH HHS R01 DK133468
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, qPCR, or spike-ins (i.e., adding cells or DNA from an organism not normally found in a sample), 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 ratios. We compare 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. We show how B:H ratios can be used to track antibiotic treatment response and recovery in both mice and humans, which showed 403-fold and 45-fold reductions in bacterial biomass during antibiotic treatment, respectively. Our results indicate that host and bacterial metagenomic DNA fractions in human stool fluctuate longitudinally around a stable mean in healthy individuals, and the average host read fraction varies across healthy individuals by < 8-9 fold. 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 algorithms, enabling retrospective absolute biomass estimates from existing stool metagenomic data.

Identifiers

PMID39829744
PMCPMC11741328

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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.