argC Orthologs from Rhizobiales show diverse profiles of transcriptional efficiency and functionality in Sinorhizobium meliloti

Microbial genome analysis: the COG approach

For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis.

Polyamine biosynthesis and biological roles in rhizobia

Polyamines are ubiquitous molecules containing two or more amino groups that fulfill varied and often essential physiological and regulatory roles in all organisms. In the symbiotic nitrogen-fixing bacteria known as rhizobia, putrescine and homospermidine are invariably produced while spermidine and norspermidine synthesis appears to be restricted to the alfalfa microsymbiont Sinorhizobium meliloti. Studies with rhizobial mutants deficient in the synthesis of one or more polyamines have shown that these compounds are important for growth, stress resistance, motility, exopolysaccharide production and biofilm formation. In this review, we describe these studies and examine how polyamines are synthesized and regulated in rhizobia.

Overproduction of Sinorhizobium meliloti ArgC (N-acetyl-gamma-glutamyl phosphate reductase) promotes growth delay and inefficient nodules

argC encodes N-acetyl-gamma-glutamyl phosphate reductase, the enzyme that catalyzes the high-energy-consuming third step in the arginine synthesis pathway. A comparative analysis revealed two translation start sites in argC from Sinorhizobium meliloti. To determine whether both protein versions are synthesized in the organism and their functional role, we obtained genetic constructs with one (1S) or two (2S) start sites, with promoters of low (pspeB) or high (plac) transcriptional rate. The constructs were transferred to the S. meliloti 1021 derivative argC mutant strain. Both protein versions were found in the free-living proteomes, but only ArgC 1S showed post-translational modification. Expression levels from argC 1S were five times higher than those of 2S, when transcribed by plac, and in concordance, its protein activity was 3-fold greater. The overexpression of both versions under plac delayed cellular growth. Inoculation of Medicago sativa plants with the S. meliloti strain harboring the argC 1S under plac induced nodulation but not nitrogen fixation. However, the strain with the argC 2S under the same promoter had a positive phenotype. Overproduction of ArgC protein for the synthesis of arginine induced physiological and symbiotic effects.

Key roles of microsymbiont amino acid metabolism in rhizobia-legume interactions

Rhizobia are bacteria in the α-proteobacterial genera Rhizobium, Sinorhizobium, Mesorhizobium, Azorhizobium and Bradyrhizobium that reduce (fix) atmospheric nitrogen in symbiotic association with a compatible host plant. In free-living and/or symbiotically associated rhizobia, amino acids may, in addition to their incorporation into proteins, serve as carbon, nitrogen or sulfur sources, signals of cellular nitrogen status and precursors of important metabolites. Depending on the rhizobia-host plant combination, microsymbiont amino acid metabolism (biosynthesis, transport and/or degradation) is often crucial to the establishment and maintenance of an effective nitrogen-fixing symbiosis and is intimately interconnected with the metabolism of the plant. This review summarizes past findings and current research directions in rhizobial amino acid metabolism and evaluates the genetic, biochemical and genome expression studies from which these are derived. Specific sections deal with the regulation of rhizobial amino acid metabolism, amino acid transport, and finally the symbiotic roles of individual amino acids in different plant-rhizobia combinations.

Cumulative effect of prophage burden on Shiga toxin production in Escherichia coli

Shigatoxigenic Escherichia coli (STEC) such as E. coli O157 are significant human pathogens, capable of producing severe, systemic disease outcomes. The more serious symptoms associated with STEC infection are primarily the result of Shiga toxin (Stx) production, directed by converting Stx bacteriophages. During phage-mediated replication and host cell lysis, the toxins are released en masse from the bacterial cells, and the severity of disease is linked inexorably to toxin load. It is common for a single bacterial host to harbour more than one heterogeneous Stx prophage, and it has also been recently proven that multiple isogenic prophage copies can exist in a single cell, contrary to the lambda immunity model. It is possible that in these multiple lysogens there is an increased potential for production of Stx. This study investigated the expression profiles of single and double isogenic lysogens of Stx phage 24(B) using quantitative PCR to examine transcription levels, and a reporter gene construct as a proxy for the translation levels of stx transcripts. Toxin gene expression in double lysogens was in excess of the single lysogen counterpart, both in the prophage state and after induction of the lytic life cycle. In addition, double lysogens were found to be more sensitive to an increased induction stimulus than single lysogens, suggesting that maintenance of a stable prophage is less likely when multiple phage genome copies are present. Overall, these data demonstrate that the phenomenon of multiple lysogeny in STEC has the potential to impact upon disease pathology through increased toxin load.

Sequence variability of Rhizobiales orthologs and relationship with physico-chemical characteristics of proteins

Background

Chromosomal orthologs can reveal the shared ancestral gene set and their evolutionary trends. Additionally, physico-chemical properties of encoded proteins could provide information about functional adaptation and ecological niche requirements.

Results

We analyzed 7080 genes (five groups of 1416 orthologs each) from Rhizobiales species (S. meliloti, R. etli, and M. loti, plant symbionts; A. tumefaciens, a plant pathogen; and B. melitensis, an animal pathogen). We evaluated their phylogenetic relationships and observed three main topologies. The first, with closer association of R. etli to A. tumefaciens; the second with R. etli closer to S. meliloti; and the third with A. tumefaciens and S. meliloti as the closest pair. This was not unusual, given the close relatedness of these three species. We calculated the synonymous (dS) and nonsynonymous (dN) substitution rates of these orthologs, and found that informational and metabolic functions showed relatively low dN rates; in contrast, genes from hypothetical functions and cellular processes showed high dN rates. An alternative measure of sequence variability, percentage of changes by species, was used to evaluate the most specific proportion of amino acid residues from alignments. When dN was compared with that measure a high correlation was obtained, revealing that much of evolutive information was extracted with the percentage of changes by species at the amino acid level. By analyzing the sequence variability of orthologs with a set of five properties (polarity, electrostatic charge, formation of secondary structures, molecular volume, and amino acid composition), we found that physico-chemical characteristics of proteins correlated with specific functional roles, and association of species did not follow their typical phylogeny, probably reflecting more adaptation to their life styles and niche preferences. In addition, orthologs with low dN rates had residues with more positive values of polarity, volume and electrostatic charge.

Conclusions

These findings revealed that even when orthologs perform the same function in each genomic background, their sequences reveal important evolutionary tendencies and differences related to adaptation.

This article was reviewed by: Dr. Purificación López-García, Prof. Jeffrey Townsend (nominated by Dr. J. Peter Gogarten), and Ms. Olga Kamneva.

Computational methods for Gene Orthology inference

Accurate inference of orthologous genes is a pre-requisite for most comparative genomics studies, and is also important for functional annotation of new genomes. Identification of orthologous gene sets typically involves phylogenetic tree analysis, heuristic algorithms based on sequence conservation, synteny analysis, or some combination of these approaches. The most direct tree-based methods typically rely on the comparison of an individual gene tree with a species tree. Once the two trees are accurately constructed, orthologs are straightforwardly identified by the definition of orthology as those homologs that are related by speciation, rather than gene duplication, at their most recent point of origin. Although ideal for the purpose of orthology identification in principle, phylogenetic trees are computationally expensive to construct for large numbers of genes and genomes, and they often contain errors, especially at large evolutionary distances. Moreover, in many organisms, in particular prokaryotes and viruses, evolution does not appear to have followed a simple 'tree-like' mode, which makes conventional tree reconciliation inapplicable. Other, heuristic methods identify probable orthologs as the closest homologous pairs or groups of genes in a set of organisms. These approaches are faster and easier to automate than tree-based methods, with efficient implementations provided by graph-theoretical algorithms enabling comparisons of thousands of genomes. Comparisons of these two approaches show that, despite conceptual differences, they produce similar sets of orthologs, especially at short evolutionary distances. Synteny also can aid in identification of orthologs. Often, tree-based, sequence similarity- and synteny-based approaches can be combined into flexible hybrid methods.