Differences in codon bias cannot explain differences in translational power among microbes

BACKGROUND: Translational power is the cellular rate of protein synthesis normalized to the biomass invested in translational machinery. Published data suggest a previously unrecognized pattern: translational power is higher among rapidly growing microbes, and lower among slowly growing microbes. One factor known to affect translational power is biased use of synonymous codons. The correlation within an organism between expression level and degree of codon bias among genes of Escherichia coli and other bacteria capable of rapid growth is commonly attributed to selection for high translational power. Conversely, the absence of such a correlation in some slowly growing microbes has been interpreted as the absence of selection for translational power. Because codon bias caused by translational selection varies between rapidly growing and slowly growing microbes, we investigated whether observed differences in translational power among microbes could be explained entirely by differences in the degree of codon bias. Although the data are not available to estimate the effect of codon bias in other species, we developed an empirically-based mathematical model to compare the translation rate of E. coli to the translation rate of a hypothetical strain which differs from E. coli only by lacking codon bias. RESULTS: Our reanalysis of data from the scientific literature suggests that translational power can differ by a factor of 5 or more between E. coli and slowly growing microbial species. Using empirical codon-specific in vivo translation rates for 29 codons, and several scenarios for extrapolating from these data to estimates over all codons, we find that codon bias cannot account for more than a doubling of the translation rate in E. coli, even with unrealistic simplifying assumptions that exaggerate the effect of codon bias. With more realistic assumptions, our best estimate is that codon bias accelerates translation in E. coli by no more than 60% in comparison to microbes with very little codon bias. CONCLUSIONS: While codon bias confers a substantial benefit of faster translation and hence greater translational power, the magnitude of this effect is insufficient to explain observed differences in translational power among bacterial and archaeal species, particularly the differences between slowly growing and rapidly growing species. Hence, large differences in translational power suggest that the translational apparatus itself differs among microbes in ways that influence translational performance

The pervasive effects of an antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing

© 2008 Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in PLoS Biology 6 (2008): e280, doi:10.1371/journal.pbio.0060280.The intestinal microbiota is essential to human health, with effects on nutrition, metabolism, pathogen resistance, and other processes. Antibiotics may disrupt these interactions and cause acute disease, as well as contribute to chronic health problems, although technical challenges have hampered research on this front. Several recent studies have characterized uncultured and complex microbial communities by applying a new, massively parallel technology to obtain hundreds of thousands of sequences of a specific variable region within the small subunit rRNA gene. These shorter sequences provide an indication of diversity. We used this technique to track changes in the intestinal microbiota of three healthy humans before and after treatment with the antibiotic ciprofloxacin, with high sensitivity and resolution, and without sacrificing breadth of coverage. Consistent with previous results, we found that the microbiota of these individuals was similar at the genus level, but interindividual differences were evident at finer scales. Ciprofloxacin reduced the diversity of the intestinal microbiota, with significant effects on about one-third of the bacterial taxa. Despite this pervasive disturbance, the membership of the communities had largely returned to the pretreatment state within 4 weeks

Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing

© 2008 Huse et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS Genetics 4 (2008): e1000255, doi:10.1371/journal.pgen.1000255.Massively parallel pyrosequencing of hypervariable regions from small subunit ribosomal RNA (SSU rRNA) genes can sample a microbial community two or three orders of magnitude more deeply per dollar and per hour than capillary sequencing of full-length SSU rRNA. As with full-length rRNA surveys, each sequence read is a tag surrogate for a single microbe. However, rather than assigning taxonomy by creating gene trees de novo that include all experimental sequences and certain reference taxa, we compare the hypervariable region tags to an extensive database of rRNA sequences and assign taxonomy based on the best match in a Global Alignment for Sequence Taxonomy (GAST) process. The resulting taxonomic census provides information on both composition and diversity of the microbial community. To determine the effectiveness of using only hypervariable region tags for assessing microbial community membership, we compared the taxonomy assigned to the V3 and V6 hypervariable regions with the taxonomy assigned to full-length SSU rRNA sequences isolated from both the human gut and a deep-sea hydrothermal vent. The hypervariable region tags and full-length rRNA sequences provided equivalent taxonomy and measures of relative abundance of microbial communities, even for tags up to 15% divergent from their nearest reference match. The greater sampling depth per dollar afforded by massively parallel pyrosequencing reveals many more members of the “rare biosphere” than does capillary sequencing of the full-length gene. In addition, tag sequencing eliminates cloning bias and the sequences are short enough to be completely sequenced in a single read, maximizing the number of organisms sampled in a run while minimizing chimera formation. This technique allows the cost-effective exploration of changes in microbial community structure, including the rare biosphere, over space and time and can be applied immediately to initiatives, such as the Human Microbiome Project.Woods Hole Center for Oceans and Human Health from the National Institutes of Health and National Science Foundation (NIH/NIEHS 1 P50 ES012742-01 and NSF/OCE 0430724-J Stegeman PI to MLS). NIH Director's Pioneer Award and Doris Duke Distinguished Clinical Scientist Award to DAR

Performance of the Translational Apparatus Varies with the Ecological Strategies of Bacteria

Protein synthesis is the predominant activity of growing bacteria; the protein synthesis system accounts for more than one-half the cell's dry mass and consumes most of the cell's energy during rapid growth. Translation has been studied extensively using model organisms, and the translational apparatus is qualitatively similar in terms of structure and function across all known forms of life. However, little is known about variation between organisms in translational performance. Using measurements of macromolecular content in a phylogenetically diverse collection of bacteria with contrasting ecological strategies, we found that the translational power (the rate of protein synthesis normalized to the mass of the protein synthesis system) is three- to fourfold higher among bacteria that respond rapidly to nutrient availability than among bacteria that respond slowly. An analysis of codon use in completely sequenced bacterial genomes confirmed that the selective forces acting on translation vary with the ecological strategy. We propose that differences in translational power result from ecologically based variation among microbes in the relative importance of two competing benefits: reducing the biomass invested in the protein synthesis system and reducing the energetic expense of protein synthesis

Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment

Our work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers following this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods