Evidence map›Paper›PMID 32939027›Full record

ArticleThe ISME journal2021

Benchmarking microbial growth rate predictions from metagenomes.

Andrew M Long, Shengwei Hou, J Cesar Ignacio-Espinoza, Jed A Fuhrman

Open access · hybridAbstract read
In one paragraph

Article in The ISME journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
8.7field-weighted citation impact, top 2% 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

48 citing papers in PubMed, 89 citations in OpenAlex.

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  13. Codon bias, nucleotide selection, and genome size predict in situ bacterial growth rate and transcription in rewetted soil.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  16. Soil viral-host interactions regulate microplastic-dependent carbon storage.Proceedings of the National Academy of Sciences of the United States of America · 2024
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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

4 authors at 1 institution in 1 country.

Andrew M Long *Department of Biological Sciences-Marine and Environmental Biology, University of Southern California, Los Angeles, CA, USA. andrew.mi.long@gmail.com.ORCID http://orcid.org/0000-0002-2003-4254
Shengwei Hou *Department of Biological Sciences-Marine and Environmental Biology, University of Southern California, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-4474-7443
J Cesar Ignacio-EspinozaDepartment of Biological Sciences-Marine and Environmental Biology, University of Southern California, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0001-9303-7504
Jed A FuhrmanDepartment of Biological Sciences-Marine and Environmental Biology, University of Southern California, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-2361-1985
University of Southern California · US

Funding

Gordon and Betty Moore Foundation (Gordon E. and Betty I. Moore Foundation) 3779National Science Foundation (NSF) OCE1737409Simons Foundation 549943
6 · The paper itself

Abstract

Growth rates are central to understanding microbial interactions and community dynamics. Metagenomic growth estimators have been developed, specifically codon usage bias (CUB) for maximum growth rates and "peak-to-trough ratio" (PTR) for in situ rates. Both were originally tested with pure cultures, but natural populations are more heterogeneous, especially in individual cell histories pertinent to PTR. To test these methods, we compared predictors with observed growth rates of freshly collected marine prokaryotes in unamended seawater. We prefiltered and diluted samples to remove grazers and greatly reduce virus infection, so net growth approximated gross growth. We sampled over 44 h for abundances and metagenomes, generating 101 metagenome-assembled genomes (MAGs), including Actinobacteria, Verrucomicrobia, SAR406, MGII archaea, etc. We tracked each MAG population by cell-abundance-normalized read recruitment, finding growth rates of 0 to 5.99 per day, the first reported rates for several groups, and used these rates as benchmarks. PTR, calculated by three methods, rarely correlated to growth (r ~-0.26-0.08), except for rapidly growing γ-Proteobacteria (r ~0.63-0.92), while CUB correlated moderately well to observed maximum growth rates (r = 0.57). This suggests that current PTR approaches poorly predict actual growth of most marine bacterial populations, but maximum growth rates can be approximated from genomic characteristics.

Indexed as

MetagenomeArchaeaBacteriaMetagenomics

Identifiers

PMID32939027
PMCPMC7852909
OpenAlexW3087499068

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.