Implications of streamlining theory for microbial ecology - PubMed (original) (raw)

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Implications of streamlining theory for microbial ecology

Stephen J Giovannoni et al. ISME J. 2014 Aug.

Abstract

Whether a small cell, a small genome or a minimal set of chemical reactions with self-replicating properties, simplicity is beguiling. As Leonardo da Vinci reportedly said, 'simplicity is the ultimate sophistication'. Two diverging views of simplicity have emerged in accounts of symbiotic and commensal bacteria and cosmopolitan free-living bacteria with small genomes. The small genomes of obligate insect endosymbionts have been attributed to genetic drift caused by small effective population sizes (Ne). In contrast, streamlining theory attributes small cells and genomes to selection for efficient use of nutrients in populations where Ne is large and nutrients limit growth. Regardless of the cause of genome reduction, lost coding potential eventually dictates loss of function. Consequences of reductive evolution in streamlined organisms include atypical patterns of prototrophy and the absence of common regulatory systems, which have been linked to difficulty in culturing these cells. Recent evidence from metagenomics suggests that streamlining is commonplace, may broadly explain the phenomenon of the uncultured microbial majority, and might also explain the highly interdependent (connected) behavior of many microbial ecosystems. Streamlining theory is belied by the observation that many successful bacteria are large cells with complex genomes. To fully appreciate streamlining, we must look to the life histories and adaptive strategies of cells, which impose minimum requirements for complexity that vary with niche.

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Figures

Figure 1

Figure 1

Alternate pathways of genome reduction. The mechanisms leading to small genomes in symbiotic and commensal organisms (for example, mycoplasmas) are fundamentally different from the process that lead to the small genomes that have recently been discovered in many free-living organisms from natural systems.

Figure 2

Figure 2

Average microbial genome sizes estimated from metagenomic data, adapted from Angly et al. (2009), with additional data from Frank and Sorensen (2011), Oh et al. (2011), Quaiser et al. (2011), Xia et al. (2011), Eiler et al. (2013).

Figure 3

Figure 3

The % of noncoding (spacer) DNA versus genome length for all published bacterial genomes in IMG v400 and estimated genome size for single-amplified genomes (SAGs) from Swan et al. (2013). Streamlined (SAR11, Prochlorococcus, symbionts) and non-streamlined important marine taxa (Vibrionaceae, Rhodobacteraceae, Alteromonadaceae) have been highlighted (legend). Organisms where streamlining is driven by nutrient-limitation, such as SAR11 and those represented by the uncultured single-amplified genomes from Swan et al. (2013), have low % noncoding DNA and tend to fall at the extremes of the distribution of residuals from the linear regression line (black line). Conversely, organisms where streamlining is driven by symbiosis tend to maintain a broad range of % noncoding DNA, despite their small genomes. Histograms (top, right) show the distribution of points across each axis. The distribution of genome lengths (top) was significantly different to a unimodal distribution (Hartigan's Dip Test; Hartigan and Hartigan, 1985), _N_=5689, _D_=0.01, _P_=7.56 × 10−5) with a separation of the two modes at ∼3.7 Mbp.

Figure 4

Figure 4

The number of σ-factor homologs versus genome length for published bacterial genomes in IMG v400 (grey), up to 5 Mbp in length with important marine microbial taxa highlighted (legend). Fitting the data across all genome lengths (inset) with a Poisson distribution showed evidence of overdispersion (Φ=5.50) therefore regression was performed using a negative binomial generalized linear model with a log-link (green line main figure, black line inset. Lighter green ribbon represents 95% confidence intervals of the model). The explained deviance of the negative binomial model was 0.73. Uncultured SAG representatives from Swan et al. (2013), SAR11, Prochlorococcus and symbionts fell below the regression line, supporting the hypothesis that low numbers of σ-factors are a consistent feature of streamlined genomes. SAGs from Verrucomicrobia fell above and below the regression line, supporting the findings of Swan et al. (2013) that these genomes can be found in both streamlined and non-streamlined varieties.

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