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Previous Article | Next Article 
Applied and Environmental Microbiology, April 2000, p. 1328-1333, Vol. 66, No. 4
Department of Microbiology and Center for
Microbial Ecology, Michigan State University, East Lansing,
Michigan 48824-1101
Received 29 October 1999/Accepted 21 January 2000
Although natural selection appears to favor the elimination of gene
redundancy in prokaryotes, multiple copies of each rRNA-encoding gene
are common on bacterial chromosomes. Despite this conspicuous deviation
from single-copy genes, no phenotype has been consistently associated
with rRNA gene copy number. We found that the number of rRNA genes
correlates with the rate at which phylogenetically diverse bacteria
respond to resource availability. Soil bacteria that formed colonies
rapidly upon exposure to a nutritionally complex medium contained an
average of 5.5 copies of the small subunit rRNA gene, whereas bacteria
that responded slowly contained an average of 1.4 copies. In soil
microcosms pulsed with the herbicide 2,4-dichlorophenoxyacetic acid
(2,4-D), indigenous populations of 2,4-D-degrading bacteria with
multiple rRNA genes ( Genes encoding the 5S, 16S, and 23S
rRNAs are typically organized into an operon in members of the domain
Bacteria. The copy number of rRNA operons per bacterial
genome varies from 1 to as many as 15 (28). For example, the
pathogenic bacteria Rickettsia prowazekii (2) and
Mycoplasma pneumoniae (4) have one rRNA operon,
while the enteric bacteria Escherichia coli (12)
and Salmonella enterica serovar Typhimurium (1)
each possess seven copies per genome. The greatest number of rRNA
operons per genome known can be found among spore-forming bacteria
isolated from soil; Bacillus subtilis (23) and
Clostridium paradoxum (28) possess 10 and 15 copies, respectively. Several hypotheses have been proposed to explain
the wide variation observed in rRNA operon copy number.
It is generally assumed that multiple copies of rRNA operons in
prokaryotic organisms are required to achieve high growth rates.
However, the short doubling time observed for certain bacteria with a
single rRNA operon (37) and the marginal impact of rRNA operon inactivation on maximal growth rate (8, 27) suggest that the capacity for rapid growth is not the sole determinant of rRNA
operon copy number. The number of transcripts that can be initiated at
an rRNA operon promoter and the transcriptional rate of RNA polymerase
set a maximum rate on the number of ribosomes that can be produced from
a single rRNA operon. Calculations including promoter initiation
efficiency and transcription rates indicate that one copy of the rRNA
operon is insufficient to supply the number of ribosomes required to
achieve maximal growth rates observed in E. coli
(5).
Given the high demand for rRNA transcription and the central role of
rRNAs in the regulation of ribosome synthesis, it is conceivable that
the number of rRNA operons may dictate the rapidity with which microbes
can synthesize ribosomes and respond to favorable changes in growth
conditions (8, 30). Transcription of the rRNA operon is
regulated to correspond with resource availability and can represent as
much as 70% of total cellular transcription during rapid periods of
growth (6). A proposed homeostatic model of ribosome
biosynthesis provides a direct link between resource availability and
the protein synthetic capacity of a bacterial cell (15). The
concentrations of resources available for growth determine
intracellular concentration of ATP and GTP, which in turn regulate the
efficiency of transcription initiation at rRNA operons. The rRNA operon
transcript is processed enzymatically to yield mature rRNAs that not
only bind ribosomal proteins during assembly of the ribosome but also
regulate translation of the ribosomal protein mRNAs (36). In
E. coli, a positive relationship exists between the number
of rRNA operons inactivated and the time required to increase growth in
response to added resources (8). Condon et al.
(8) suggested that E. coli maintains seven rRNA
operons due to selective pressure on the ability to adapt quickly to
environmental conditions. Therefore, the capacity to respond rapidly to
fluctuating growth conditions may be more relevant than maximal growth
rate for explaining the variation in rRNA operon multiplicity in
different species of bacteria.
While multiple rRNA operons may provide an advantage under fluctuating
conditions, constitutive expression from multiple rRNA operons would
confer a metabolic expense on slower-growing cells due to the
overproduction of ribosomes. Extra copies of plasmid-borne rRNA operons
increase stable RNA concentrations while concomitantly decreasing
growth rates in E. coli, indicating a potential cost associated with constitutive expression from multiple rRNA operons at
low growth rates (30). The immediate degradation of
ribosomes in starved cells of E. coli and
Salmonella spp. also suggests that excess translation
capacity is metabolically unfavorable in conditions of low nutrient
availability (9, 20). For these reasons, we postulate that
fewer rRNA operons represent a competitive advantage at low growth rates.
The observations above led us to question whether the number of rRNA
operons in phylogenetically diverse bacteria reflected ecological
strategies characterized by either rapid response to resource input
(high copy number) or efficient allocation of resources under constant,
slow-growth environments (low copy number). To determine whether the
number of rRNA operons is of adaptive significance to bacteria rather
than the result of genetic drift or coincidence, we explored the
relationship between rRNA operon copy number, organismal phylogeny, and
the capacity of bacteria to respond to added resources. Microbes
isolated from soil were selected for this study because soils are
inhabited by a rich diversity of microbes (33) and the soil
matrix provides an array of microenvironments that can vary
considerably with regard to resource availability. If rRNA operon copy
number reflects the ecological strategy of bacteria in response to
resource availability, bacterial populations with different numbers of
rRNA operons are likely to coexist in soils and respond
differently to perturbations.
Colony response curves of soil bacteria.
Soil samples used
for experimentation were obtained from the Long Term Ecological
Research (LTER) site at Kellogg Biological Station, Hickory Corners,
Mich., in May 1997. Soil cores (10-cm depth by 2.5-cm diameter) were
removed from five locations within a conventional-till agricultural
plot (plot T1; descriptions of plots may be accessed at
http://lter.kbs.msu.edu). Sample cores were sieved (2-mm mesh),
homogenized, and stored on wet ice for no more than 6 h before
use. A 100-g portion of homogenized soil was suspended in 1.0 liter of
5 mM K2HPO4 buffer (pH 7.0) and shaken (22°C,
150 rpm, 15 min), and a 1-ml portion of the suspension was serially
diluted. Aliquots from the dilution series were plated on 1.5% agar
medium containing a 100-fold dilution of nutrient broth (Difco Inc.);
bacterial colonies were enumerated at periodic time intervals and
marked for subsequent isolation upon completion of the colony response
curve. Hattori's laboratory has demonstrated that the pattern of
colony formation by soil bacteria is reproducible and can be modeled by
the superimposition of several (typically four) first-order reaction
curves (16, 19). Bacteria from the time intervals designated
I and IV (Fig. 1; groups described in
reference 16) were isolated and characterized for
rRNA operon copy number. Single colonies were picked and streaked for
isolation a minimum of six times on dilute nutrient agar plates
(Difco); culture purity was also confirmed via light microscopy and PCR amplification of the 16S rRNA gene (rDNA; see below). Isolates from
rice paddy soils were obtained from Tsutomu Hattori (Institute of
Genetic Ecology, Tohoku University, Sendai, Japan) (16, 26).
0099-2240/00/$04.00+0
Copyright © 2000, American Society for Microbiology. All rights reserved.
rRNA Operon Copy Number Reflects Ecological
Strategies of Bacteria
and
ABSTRACT
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
References
= 5.4) became dominant,
whereas populations with fewer rRNA genes ( = 2.7) were favored in unamended controls. These findings demonstrate phenotypic effects associated with rRNA gene copy number that are
indicative of ecological strategies influencing the structure of
natural microbial communities.
INTRODUCTION
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
References
MATERIALS AND METHODS
Top
Abstract
Introduction
Materials and Methods
Results and Discussion
References
View larger version (15K):
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FIG. 1.
Correlation between time of colony appearance and rRNA
operon copy number. (A) Colony appearance curve for isolates from
conventional-tilled agricultural soil in Michigan ( 
) and from rice
paddy soils in Japan (adapted from reference 16)
(
). Each point represents the arithmetic average of colonies
observed on a minimum of three agar plates at that time interval.
Bacteria from the time intervals designated I and IV (groups described
in reference 16) were isolated and characterized for
rRNA operon copy number. (B) Mean number of rRNA operons for bacterial
isolates from group I (early colony formers) and group IV (late colony
formers) are presented as rice paddy isolates (filled bars;
n = 6 [early] or 7 [late]), conventional-tilled
soil isolates (open bars; n = 5 [early] or 6 [late]). Error bars are 1 standard deviation above the sample mean.
Statistical analyses of early- and late-appearing sample populations
were performed using Student's t test, assuming unequal
sample variances (
= 0.05, df = 10).
rRNA operon copy number determination for soil isolates. Genomic DNA was obtained from each soil isolate, independently digested with at least three different restriction enzymes (AccI, BstEII, PinA1, PvuII, PstI, or SacI; Gibco/BRL Co.), and separated on a 1.0% agarose gel using standard methods (3, 25). rRNA operon copy numbers were determined by Southern hybridization analysis of gel-separated restriction digests using a digoxigenin-dUTP-labeled DNA probe complementary to a conserved region (positions 8 to 536) of the E. coli 16S rDNA. Alternative arrangements of rRNA genes into operons are known, but individual rRNA genes are usually present in stoichiometric quantities. Therefore, the number of 16S rDNA copies (number of bands with equal intensity hybridizing to the 16S rDNA probe) was considered to be a reasonable estimator of the number of rRNA operon equivalents per genome. In cases where enzymatic digestion failed to resolve hybridized fragments or bands of equal intensity could not be discriminated, results were discarded and additional analyses were performed with different restriction endonucleases. Genomic DNA isolated from E. coli and digested with PvuII was included on each Southern hybridization gel as a positive control.
Phylogenetic analyses. The 16S rDNA was amplified from early- and late-appearing soil isolates using primers 8f (5'-AGAGTTTGATCCTGGCTCAG-3') and 1492r (5'-GGTTACCTTGTTACGACTT-3') with reaction conditions described previously (22, 35). Partial sequences were obtained from soil isolates with an automated DNA sequencer (ABI 373A) using fluorescent dideoxy dye terminator chemistry and overlapping sequencing primers 8f and 519r (5'-GTATTACCGCGGCTGCTGG-3'). Sequences were initially aligned using the ARB software package (http://www.biol.chemie.tu-muenchen.de) automated aligner and then verified manually against known secondary structures (31). Soil isolate partial sequences (between positions 28 and 519 of the E. coli 16S rDNA consensus) were added to a Ribosomal Database Project (24) subtree, using parsimony with the ARB software package (31). Branch lengths were right aligned for presentation purposes in ARB and therefore do not necessarily represent the actual evolutionary distance, but the branching topology is preserved.
Soil microcosm amendment experimentation. Soil microcosms were established from homogenized soil collected from the top 10 cm of a fallow agricultural plot (LTER, Kellogg Biological Station) which had no previous documented exposure to the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D). Ten to fifteen soil samples from a 6-m2 area were pooled and sieved (2-mm mesh). For each microcosm, 243 g of soil (8% moisture content) was transferred to a polyethylene bag, while 27-g samples of soil was dried (100°C, overnight) to serve as a carrier for liquid amendments. Each 27-g portion of carrier soil was mixed with 2,4-D dissolved in 0.1 M Na2HPO4 buffer (pH 7.0) or buffer alone such that each microcosm received identical concentrations of sodium phosphate but either 0, 10, or 100 µg of 2,4-D per g of soil (final concentration). Final moisture content of soil in each microcosm was adjusted to 25% (wt/wt) with sterile, distilled water. Microcosms were incubated for 1 week, during which samples were periodically removed for isolation of 2,4-D-degrading bacteria. Colonies able to degrade 2,4-D were identified by autoradiography based on the ability to incorporate 14C from 14C-ring-labeled 2,4-D into biomass (10). rRNA operon copy numbers were determined as described above with Southern hybridization analysis of genomic DNA digested with EcoRI or PvuII.
Amplified rDNA restriction analysis of 2,4-D-degrading isolates. Bacterial species able to degrade 2,4-D were identified based on restriction fragment length polymorphism (RFLP) patterns resulting from gel electrophoresis of enzymatically digested, PCR-amplified 16S rDNA. 16S rDNA was amplified using primers 8f and 1492r and reaction conditions described previously (22, 35). Amplified DNA from isolates was independently digested with MspI, CfoI, AluI, or HaeIII. Digested DNA was electrophoresed through 2.75% Metaphor agarose gels (FMC Bioproducts, Inc.), and the RFLP patterns of all isolates were compared. Isolates whose 16S rDNA restriction pattern differed with at least one enzyme were defined as different species.
Nucleotide sequence accession numbers. The nucleotide sequences for rice paddy isolates have been previously deposited in the GenBank database under accession no. D84561, D84564, D84568, D84570, D84577, D84597, D84604, D84635, D84639, D84640, D84641, D84644, and D84645. Nucleotide sequences for isolates obtained from the Kellogg Biological Station LTER site are deposited in GenBank under accession no. AF183149 to AF183159.
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RESULTS AND DISCUSSION |
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Top
Abstract
Introduction
Materials and Methods
Results and Discussion
References
|
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In environments with periodic resource fluctuations, lag time (L, the time before initiation of cell division) and maximal growth rate (µmax) are important components of fitness (21, 34). Populations that can rapidly achieve high maximal growth rates (short L, high µmax) are able to utilize available resources before competing populations. In contrast, lag time does not impose a fitness advantage in environments with a constant supply of resources (18, 32). Multiple rRNA operons allow transcriptional initiation from multiple loci, permitting a rapid increase in the intracellular concentration of rRNA, thereby effectively decreasing lag time. A potential tradeoff for a rapid up-shift capacity is the metabolic expense of rRNA overproduction at low growth rates, apparently due to inadequate regulation of rRNA operons (30). In agreement with these observations, bacteria isolated from low-nutrient aquatic environments share the characteristics of slow growth and few (typically one to two) rRNA operons (7, 13).
Response time of soil isolates and rRNA operon copy number.
To
test whether rRNA operon copy number is correlated with the response
time (a function of µmax and L) of bacterial
populations in soil to resource availability, heterotrophic bacteria
appearing early and late on agar media were isolated from soils from an agricultural research site in Michigan and a rice paddy near Sendai, Japan (16) (Fig. 1A). Early-appearing isolates possessed, on average, a significantly greater number of rRNA operons
( = 5.5 copies) than late-appearing isolates
( = 1.4 copies) (Fig. 1B). Of the
early-appearing isolates, 6 of 11 contained five or more copies of the
rRNA operon per genome, while 12 of 13 late-appearing species contained
two or fewer copies. The time required for colony formation was a
phenotype retained by isolates upon subsequent transfer on solid media
(personal observation and reference 26). The biased
distribution of diverse soil bacteria with high rRNA operon copy
numbers appearing early on two different complex culture media suggests
that the response of bacteria to favorable growth conditions reflects
ecological strategies and not solely the ability to utilize a
particular limiting resource.
Relationship of rRNA operon copy number to phylogeny and genome
size.
The phylogeny of isolates was reconstructed to preclude the
possibility that the number of rRNA operons per isolate reflected evolutionary history alone. A statistical correlation between rRNA
operon copy number and response time assumes that species were removed
independently from the same distribution (14). Since
bacteria were isolated based on the phenotypic parameter of response
time, it was possible that the correlation with rRNA operon copy number
resulted from two monophyletic groups of bacteria with either high or
low numbers of rRNA operons per genome. The distribution of rRNA operon
copy number within a collection of phylogenetically diverse bacteria
indicated no obvious evolutionary constraint on the number of rRNA
operons per genome (Fig. 2). The
occurrence of bacteria with the same number of rRNA operons in
disparate phylogenetic lineages appears to have arisen from convergent
evolution, driven by adaptation to similar selective pressures
influencing the fitness of bacteria in different environments.
|
|
Effects of selection in soil microcosms.
The potential
adaptive significance of rRNA gene copy number was tested directly in
soil microcosms by examining the dynamics of indigenous bacterial
populations competing for the herbicide 2,4-D. The relative abundance
of bacterial populations able to use 2,4-D as a sole carbon and energy
source was measured before and after selection in nine soil microcosms
(11). In unamended microcosms, there were 103
CFU of 2,4-D-degrading bacteria per g soil. Not surprisingly, the total
number of 2,4-D-degrading bacteria increased to 105 or
106 over 7 days following a one-time pulse with either 10 or 100 ppm (final concentration), respectively, of 2,4-D
(11). Although there was a dramatic change in the number of
2,4-D-degrading bacteria, the total number of readily cultured bacteria
remained at approximately 107 CFU/g of soil in each of the
nine microcosms. A total of 837 isolates representing 38 2,4-D-degrading species were isolated from the microcosms. The effect
of selection for rRNA operon copy number among 2,4-D-degrading
populations is clearly apparent between unamended and amended
microcosms (Fig. 4). The most abundant
species in unamended microcosms were minor components of microcosms
amended with 10 or 100 ppm of 2,4-D, while several species at low
abundance in the controls developed into numerically dominant
populations in the pulsed microcosms.
|
Conclusions. Experiments described above elucidate the potential role of rRNA operon multiplicity by providing a direct correlation between rRNA operon copy number and the time required for soil bacteria to form colonies (a function of µmax and L) in response to resource availability. The potential adaptive significance of rRNA operon multiplicity was demonstrated in soil microcosms by the reproductive success of diverse 2,4-D-degrading bacteria containing a significantly greater number of rRNA operons per genome during competition for a pulse of 2,4-D. We propose that the number of rRNA operons in a bacterial genome represent one trait among a group of interdependent traits that comprise a strategy for responding to the availability of resources.
As genomic information rapidly accumulates for the Bacteria from whole-genome sequencing projects, our model of bacterial competitiveness becomes increasingly complex as individual genes are considered in the context of the entire genome and, ultimately, the organism. Certainly no single gene product can determine bacterial competitiveness in all environments. However, gene products involved in the regulation of central metabolism and cellular growth may establish a basic foundation for the competitive success of a bacterial species. Genes directly involved in the response of bacteria to specific selective pressures from the environment will undoubtedly further shape the competitive fitness or life history strategy of a species. The correlation between the copy number of rRNA genes and the response rate of diverse bacteria to a variety of growth substrates indicates an evolutionary linkage between the number of rRNA genes and the basic competitive ability of bacterial species. While other genes may enhance this basic ability, the multiplicity of rRNA genes in the Bacteria provides a genetic indicator of the general ecological strategy of a bacterial species for exploitation of nutrients.| |
ACKNOWLEDGMENTS |
|---|
We thank R. E. Lenski for providing perspective on the interplay between microbial ecology and evolution, T. Hattori for providing rice paddy soil isolates, and B. Stevenson, D. Buckley, and J. Breznak for thoughtful discussion of the manuscript.
The U.S. Department of Energy and National Science Foundation (IBN-9875254), including graduate research fellowships from the NSF Center for Microbial Ecology (BIR91-20006) at Michigan State University (J.A.K. and J.M.D.), supported this research.
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FOOTNOTES |
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* Corresponding author. Mailing address: Department of Microbiology and Center for Microbial Ecology, Michigan State University, 202 Giltner Hall, East Lansing, MI 48824-1101. Phone: (517) 353-1796. Fax: (517) 353-8957. E-mail: tschmidt{at}pilot.msu.edu.
Present address: Life Sciences Division, Los Alamos National
Laboratories, Los Alamos, NM 87545.
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cyanobacteria (n = 4), spirochetes (n = 4), high-G+C gram-positive bacteria (n = 7),
low-G+C gram-positive bacteria (n = 16), and
thermophiles (n = 3). A linear regression for all data
points was calculated using the least-squares method (P < 0.01 that no relationship exists), upper and lower 95% confidence
bounds are indicated by dotted lines. The data used are available
online at the Ribosomal RNA Operon Copy Number Database
(