Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Mar 23;118(12):e2016810118.
doi: 10.1073/pnas.2016810118.

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns

J L Weissman  1 , Shengwei Hou  2 , Jed A Fuhrman  2
Affiliations

Estimating maximal microbial growth rates from cultures, metagenomes, and single cells via codon usage patterns

J L Weissman et al. Proc Natl Acad Sci U S A. .

Abstract

Maximal growth rate is a basic parameter of microbial lifestyle that varies over several orders of magnitude, with doubling times ranging from a matter of minutes to multiple days. Growth rates are typically measured using laboratory culture experiments. Yet, we lack sufficient understanding of the physiology of most microbes to design appropriate culture conditions for them, severely limiting our ability to assess the global diversity of microbial growth rates. Genomic estimators of maximal growth rate provide a practical solution to survey the distribution of microbial growth potential, regardless of cultivation status. We developed an improved maximal growth rate estimator and predicted maximal growth rates from over 200,000 genomes, metagenome-assembled genomes, and single-cell amplified genomes to survey growth potential across the range of prokaryotic diversity; extensions allow estimates from 16S rRNA sequences alone as well as weighted community estimates from metagenomes. We compared the growth rates of cultivated and uncultivated organisms to illustrate how culture collections are strongly biased toward organisms capable of rapid growth. Finally, we found that organisms naturally group into two growth classes and observed a bias in growth predictions for extremely slow-growing organisms. These observations ultimately led us to suggest evolutionary definitions of oligotrophy and copiotrophy based on the selective regime an organism occupies. We found that these growth classes are associated with distinct selective regimes and genomic functional potentials.

Keywords: codon usage bias; copiotrophy; microbial growth; oligotrophy.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
Predictions from gRodon accurately reflect prokaryotic growth rates, with the caveat that (A) gRodon underestimates doubling times when growth is very slow due to (B) a floor on CUB reached in slow-growth regimes. Vertical dashed red lines at 5 h indicate where the CUB vs. doubling-time relationship appears to flatten. The black dashed line in A is the x=y reference line.
Fig. 2.
Fig. 2.
Prokaryotes with sequenced genomes span a broad range of predicted growth rates. (A) Predicted growth rates for assemblies in NCBI’s RefSeq database. Growth rates were averaged over genera to produce this distribution since the sampling of taxa in RefSeq is highly uneven (SI Appendix, Fig. S14 has full distribution) (a small number of genera had inferred doubling times over 100 h, 6 of 2,984). Clusters correspond to the components of a Gaussian mixture model, with area under each curve scaled to the relative likelihood of an observation being drawn from that cluster. (B and C) Growth rate distributions for individual (B) fast- and (C) slow-growing phyla (only showing phyla with ≥30 genera represented in RefSeq). Vertical dashed red lines in A–C are at 5 h for reference.
Fig. 3.
Fig. 3.
Predicted maximal growth rates in marine environments. Observe that (A and B) genomes from fully sequenced isolates (MarRef) have shorter predicted doubling times on average than MAGs (from the Global Ocean Reference Genomes Tropics [GORG-tropics] database) and SAGs and fail to capture the slow-growing fraction of the community. Additionally, SAGs showed a lower overall growth rate than MAGs, with very few doubling times predicted to be under 5 h, likely due in part to how SAGs were sampled (only at the ocean surface rather than at multiple depths). MAGs generated by distinct research groups showed surprisingly consistent maximal growth rate distributions. (C) Fully sequenced isolates from MarRef are more likely to be copiotrophs (d<5), independent of phylogeny. The tree shown includes one tip sampled per genera, and the corresponding heatmap summarizes whether the mean doubling time was less than 5 h for that genus and whether any representatives of that genus are represented in MarRef (full dataset used for analysis, genus-level summary for visualization only). Phylogenetic logistic regression between isolate status and copiotrophy is robust to (D) the removal of individual species from the analysis, (E) the removal of entire clades from the analysis (the removal of Proteobacteria, the most abundant phylum in the dataset, leads to a weaker but still positive relationship), and (F) the removal of large fractions of the data (up to 50%).
Fig. 4.
Fig. 4.
Copiotroph and oligotroph genomes are enriched for different functions. (A) The difference between the average proportion of genes in copiotroph genomes (ECopiotrophs) and the average proportion of genes in oligotroph genomes (EOligotrophs) assigned to various classes of genes [COG classifications from eggnogmapper (107)]. Positive numbers indicate a functional class is enriched as a percentage of total genes in copiotrophs relative to oligotrophs, and negative values are the opposite. Only significantly differentially enriched classes are shown (with red bars emphasizing classes with larger differences). (B) Volcano plot showing differential prevalence across copiotroph (PCopiotrophs) and oligotroph (POligotrophs) genomes of specific gene families belonging to the most differentially enriched gene classes. (C) Table of differentially prevalent gene families from the most commonly differentially prevalent classes (SI Appendix, Fig. S24 has a full table).
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Eagon R. G., Pseudomonas natriegens, a marine bacterium with a generation time of less than 10 minutes. J. Bacteriol. 83, 736–737 (1962). - PMC - PubMed
    1. Monod J., The growth of bacterial cultures. Annu. Rev. Microbiol. 3, 371–394 (1949).
    1. Rappé M. S., Connon S. A., Vergin K. L., Giovannoni S. J., Cultivation of the ubiquitous sar11 marine bacterioplankton clade. Nature 418, 630–633 (2002). - PubMed
    1. Colwell F. S., D’Hondt S., Nature and extent of the deep biosphere. Rev. Mineral. Geochem. 75, 547–574 (2013).
    1. Starnawski P., et al. , Microbial community assembly and evolution in subseafloor sediment. Proc. Natl. Acad. Sci. U.S.A. 114, 2940–2945 (2017). - PMC - PubMed

Publication types

LinkOut - more resources