Single-cell data reveal heterogeneity of investment in ribosomes across a bacterial population

Consider whether you would read an article that reached a conclusion like this: “Our results thus reveal a range of strategies for investing resources in the most expensive machines at the heart of this process.” I probably wouldn’t, since words like “invest” and “expensive” are—shall we say—unattractive to me. But what if the sentence is actually this: “Our results thus reveal a range of strategies for investing resources in the molecular machines at the heart of cellular self-replication.” That’s a sentence from the abstract of this interesting paper in Nature Communications, “Single-cell data reveal heterogeneity of investment in ribosomes across a bacterial population.” The authors looked at ribosome numbers and synthesis in individual bacterial cells and found surprising diversity in ribosomal mass and in the timing of responses of individual cells to challenges. Populations are known to respond to metabolic challenges with corresponding shifts in allocation of resources to ribosomal synthesis, but the new paper shows that individual cells vary dramatically in how they do this.

The authors end their paper with this clear and compelling overview, brimming with great metaphors:

…we thus quantified, using a combination of reporter genes and statistical inference algorithms, dynamic investment in ribosomes on the single-cell level. The results reveal a surprising variability in the allocation of resources to ribosomes, the most costly molecular machine in bacterial cells, during both balanced and unbalanced growth. This raises fundamental questions on the role of the variability of ribosome concentrations in shaping the growth of a bacterial population and its adaptation to changing environments. Given the importance of growth and adaptation in biomedical and biotechnological applications, we expect our findings to have practical implications as well.


Single-cell data reveal heterogeneity of investment in ribosomes across a bacterial population
Nature Communications 2 Jan 2025
From the labs of Johannes Geiselmann and Hidde de Jong.

Snippet by Stephen Matheson

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