The MetaCyc Database

115

105

The genetic code has certain regularities that have resisted mechanistic interpretation. These include strong correlations between the first base of codons and the precursor from which the encoded amino acid is synthesized and between the second base of codons and the hydrophobicity of the encoded amino acid. These regularities are even more striking in a projection of the modern code onto a simpler code consisting of doublet codons encoding a set of simple amino acids. These regularities can be explained if, before the emergence of macromolecules, simple amino acids were synthesized in covalent complexes of dinucleotides with ␣-keto acids originating from the reductive tricarboxylic acid cycle or reductive acetate pathway. The bases and phosphates of the dinucleotide are proposed to have enhanced the rates of synthetic reactions leading to amino acids in a small-molecule reaction network that preceded the RNA translation apparatus but created an association between amino acids and the first two bases of their codons that was retained when translation emerged later in evolution.catalysis ͉ origin of life T he genetic code has many regularities (1), of which only a subset have explanations in terms of tRNA function (2) or robustness against deleterious effects of mutation (3, 4) or errors in translation (3, 5). There is a strong correlation between the first bases of codons and the biosynthetic pathways of the amino acids they encode (1, 6). Codons beginning with C, A, and U encode amino acids synthesized from ␣-ketoglutarate (␣-KG), oxaloacetate (OAA), and pyruvate, respectively. ¶ These correlations are especially striking in light of the structural diversity of amino acids whose codons share a first base. For example, codons for Glu and Pro both begin with C, and those for Cys and Leu begin with U. Codons beginning with G encode amino acids that can be formed by direct reductive amination of a simple ␣-keto acid. These include glycine, alanine, aspartate, and glutamate, which can be formed by reductive amination of glyoxalate, pyruvate, OAA, and ␣-KG, respectively. There is also a long-recognized relationship between the hydrophobicity of the amino acid and the second base of its codon (1). Codons having U as the second base are associated with the most hydrophobic amino acids, and those having A as the second base are associated with the most hydrophilic amino acids.We suggest that both correlations can be explained if, before the emergence of macromolecules, simple amino acids were synthesized from ␣-keto acid precursors covalently attached to dinucleotides that catalyzed the reactions required to synthesize specific amino acids (see Fig. 1). This is a significant departure from previous theories attempting to explain the regularities in the genetic code (3). The ''stereochemical'' hypothesis suggests that binding interactions between amino acids and their codons or anticodons dictated the structure of the genetic code (7-10). The ''coevolution'' hypothesis (6) suggests that the original genetic code specifi...

mentioning

confidence: 67%

A mechanism for the association of amino acids with their codons and the origin of the genetic code

Copley

Smith

Morowitz

2005

115

105

“…This effort could then progress to encompass less abundant components of the consortium, especially as new methods are developed for cultivating organisms that were previously refractory to growth ex vivo (7). Ultimately, these efforts, accompanied by careful annotation and software tools that allow in silico prediction of metabolic capabilities [e.g., KEGG (85); WIT (86), ECOCYC (87); METACYC (88); and PATHWAY TOOLS (89)] should provide a view of the degree of functional distinctiveness as well as apparent redundancy among subspecies, species, and genera within the microbiota. The resulting information could provide new molecular tools, beyond 16S rDNA, for enumeration of this and other ecosystems, new perspectives about the degree of interchange of genetic material among community members (and thus what defines a species or constitutes true extinction within a consortium), plus new genomic views of features that distinguish symbionts from pathogens.…”

Section: Symbiosis: Food For Many Disciplinesmentioning

confidence: 99%

Honor thy symbionts

Gordon

2003

759

403

Our intestine is the site of an extraordinarily complex and dynamic environmentally transmitted consortial symbiosis. The molecular foundations of beneficial symbiotic host-bacterial relationships in the gut are being revealed in part from studies of simplified models of this ecosystem, where germ-free mice are colonized with specified members of the microbial community, and in part from comparisons of the genomes of members of the intestinal microbiota. The results emphasize the contributions of symbionts to postnatal gut development and host physiology, as well as the remarkable strategies these microorganisms have evolved to sustain their alliances. These points are illustrated by the humanBacteroides thetaiotaomicron symbiosis. Interdisciplinary studies of the effects of the intestinal environment on genome structure and function should provide important new insights about how microbes and humans have coevolved mutually beneficial relationships and new perspectives about the foundations of our health.gut microbial ecology ͉ gnotobiotic mice ͉ glycobiome ͉ ecogenomics ͉ environmental sensing

“…1). The biochemical pathway database in the PlantSEED integrates biochemical data found in numerous resources (6,(28)(29)(30), with an emphasis on AraCyc (6), which served as the primary source for our initial set of pathways and gene-reaction associations. The reactions in our biochemical pathways are mapped to biological functions contained in 97 plant-specific subsystems created to support genome annotation and curation in the PlantSEED.…”

Section: Resultsmentioning

confidence: 99%

High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource

Seaver

Gerdes²,

Frelin

et al. 2014

The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for crosskingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of modelbased assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed.systems biology | computational biochemistry | plant metabolism | plant genomics