Evolution of Translational Machinery in Fast- and Slow-Growing Bacteria

Bacterial species differ dramatically in their growth rates, reflecting distinct ecological strategies and physiological constraints. Because protein synthesis is a major determinant of cellular replication, I examined how genomic investment in the translation machinery varies across bacteria with widely different doubling times. Using 20 bacterial species spanning two major bacterial kingdoms (Bacillati and Pseudomonadati), I quantified ribosomal RNA (<i>rrn</i>) operon number, total tRNA gene number, and the allocation of tRNA genes among amino acids. Rapidly replicating <i>Vibrio natriegens</i> has 11 <i>rrn</i> operons and 129 tRNA genes in its genome, whereas slowly replicating <i>Borrelia burgdorferi</i> has only one <i>rrn</i> operon and 32 tRNA genes. I show that both the <i>rrn</i> operon number and the tRNA gene number decline sharply with increasing generation time, a pattern observed independently within each bacterial kingdom. Moreover, tRNA gene allocation is highly non-uniform: amino acids that are frequently used in proteins and encoded by large synonymous codon families are supported by disproportionately more tRNA genes. This relationship is well described by a simple model incorporating amino acid usage and codon family size, as illustrated in rapidly growing species such as <i>Vibrio natriegens</i> and <i>Clostridium perfringens</i>. In contrast, slow-growing bacteria maintain relatively minimalist translation systems. Together, these results demonstrate that bacterial genomes are systematically optimized for translation in a manner tightly coupled to growth strategy, revealing how natural selection tunes both the capacity and structure of the translation machinery.

Authors

Institutions

Publication Details

Journal
Microorganisms
Published
2026-02-05
DOI
https://doi.org/10.3390/microorganisms14020377
Citations
1
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
22.24

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evolution of Translational Machinery in Fast- and Slow-Growing Bacteria

Xuhua Xia
1 citations
Microorganisms
RNA and protein synthesis mechanisms
22.24
article

Evolution of Translational Machinery in Fast- and Slow-Growing Bacteria

Xuhua Xia
article en
1 citations

Abstract

Bacterial species differ dramatically in their growth rates, reflecting distinct ecological strategies and physiological constraints. Because protein synthesis is a major determinant of cellular replication, I examined how genomic investment in the translation machinery varies across bacteria with widely different doubling times. Using 20 bacterial species spanning two major bacterial kingdoms (Bacillati and Pseudomonadati), I quantified ribosomal RNA (<i>rrn</i>) operon number, total tRNA gene number, and the allocation of tRNA genes among amino acids. Rapidly replicating <i>Vibrio natriegens</i> has 11 <i>rrn</i> operons and 129 tRNA genes in its genome, whereas slowly replicating <i>Borrelia burgdorferi</i> has only one <i>rrn</i> operon and 32 tRNA genes. I show that both the <i>rrn</i> operon number and the tRNA gene number decline sharply with increasing generation time, a pattern observed independently within each bacterial kingdom. Moreover, tRNA gene allocation is highly non-uniform: amino acids that are frequently used in proteins and encoded by large synonymous codon families are supported by disproportionately more tRNA genes. This relationship is well described by a simple model incorporating amino acid usage and codon family size, as illustrated in rapidly growing species such as <i>Vibrio natriegens</i> and <i>Clostridium perfringens</i>. In contrast, slow-growing bacteria maintain relatively minimalist translation systems. Together, these results demonstrate that bacterial genomes are systematically optimized for translation in a manner tightly coupled to growth strategy, revealing how natural selection tunes both the capacity and structure of the translation machinery.

MicroorganismsVol. 14(2)
University of Ottawa (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 1%
RNA and protein synthesis mechanisms
22.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.