Pathway evolution, structurally speaking.

Small-molecule metabolism forms the core of the metabolic processes of all living organisms. As early as 1945, possible mechanisms for the evolution of such a complex metabolic system were considered. The problem is to explain the appearance and development of a highly regulated complex network of interacting proteins and substrates from a limited structural and functional repertoire. By permitting the co-analysis of phylogeny and metabolism, the combined exploitation of pathway and structural databases, as well as the use of multiple-sequence alignment search algorithms, sheds light on this problem. Much of the current research suggests a chemistry-driven 'patchwork' model of pathway evolution, but other mechanisms may play a role. In the future, as metabolic structure and sequence space are further explored, it should become easier to trace the finer details of pathway development and understand how complexity has evolved.

A universally applicable method of operon map prediction on minimally annotated genomes using conserved genomic context.

An important step in understanding the regulation of a prokaryotic genome is the generation of its transcription unit map. The current strongest operon predictor depends on the distributions of intergenic distances (IGD) separating adjacent genes within and between operons. Unfortunately, experimental data on these distance distributions are limited to Escherichia coli and Bacillus subtilis. We suggest a new graph algorithmic approach based on comparative genomics to identify clusters of conserved genes independent of IGD and conservation of gene order. As a consequence, distance distributions of operon pairs for any arbitrary prokaryotic genome can be inferred. For E.coli, the algorithm predicts 854 conserved adjacent pairs with a precision of 85%. The IGD distribution for these pairs is virtually identical to the E.coli operon pair distribution. Statistical analysis of the predicted pair IGD distribution allows estimation of a genome-specific operon IGD cut-off, obviating the requirement for a training set in IGD-based operon prediction. We apply the method to a representative set of eight genomes, and show that these genome-specific IGD distributions differ considerably from each other and from the distribution in E.coli.

A GAF domain in the hypoxia/NO-inducible Mycobacterium tuberculosis DosS protein binds haem.

The majority of the Mycobacterium tuberculosis response to hypoxia and nitric oxide is through the DosRS (DevRS) two-component regulatory system. The N-terminal input domain of the DosS sensor contains two GAF domains. We demonstrate here that the proximal GAF domain binds haem, and identified histidine 149 of DosS as critical to haem-binding; the location of this histidine residue is similar to the cGMP-binding site in a crystal structure of cyclic nucleotide phosphodiesterase 2A. GAF domains are frequently involved in binding cyclic nucleotides, but this is the first GAF domain to be identified that binds haem. In contrast, PAS domains (similar to GAF domains in structure but not primary sequence) frequently use haem cofactors, and these findings further illustrate how the functions of these domains overlap. We propose that the activation of the DosS sensor is controlled through the haem binding of molecular oxygen or nitric oxide.

Gene3D: structural assignments for the biologist and bioinformaticist alike.

The Gene3D database (http://www.biochem.ucl.ac.uk/bsm/cath_new/Gene3D/) provides structural assignments for genes within complete genomes. These are available via the internet from either the World Wide Web or FTP. Assignments are made using PSI-BLAST and subsequently processed using the DRange protocol. The DRange protocol is an empirically benchmarked method for assessing the validity of structural assignments made using sequence searching methods where appropriate assignment statistics are collected and made available. Gene3D links assignments to their appropriate entries in relevent structural and classification resources (PDBsum, CATH database and the Dictionary of Homologous Superfamilies). Release 2.0 of Gene3D includes 62 genomes, 2 eukaryotes, 10 archaea and 40 bacteria. Currently, structural assignments can be made for between 30 and 40 percent of any given genome. In any genome, around half of those genes assigned a structural domain are assigned a single domain and the other half of the genes are assigned multiple structural domains. Gene3D is linked to the CATH database and is updated with each new update of CATH.

What do microarrays really tell us about M. tuberculosis?

Bacterial pathogens adapt to their host environments to a large extent through switching on complex transcriptional programmes, and whole-genome microarray experiments promise to reveal this complexity. There has been a recent burst of articles reporting transcriptome analyses of Mycobacterium tuberculosis, including for the first time studies in macrophages and mice. We review gene expression reports, and compare them with each other and with microarray-based gene essentiality studies, revealing at times a startling lack of correlation. Additionally, we suggest a standardization format for the submission of processed data for publication, to facilitate cross-experiment analyses.

Homology, pathway distance and chromosomal localization of the small molecule metabolism enzymes in Escherichia coli.

Here, we analyse Escherichia coli enzymes involved in small molecule metabolism (SMM). We introduce the concept of pathway distance as a measure of the number of distinct metabolic steps separating two SMM enzymes, and we consider protein homology (as determined by assigning enzymes to structural and sequence families) and gene interval (the number of genes separating two genes on the E. coli chromosome). The relationships between these three contexts (pathway distance, homology and chromosomal localisation) is investigated extensively. We make use of these relationships to suggest possible SMM evolution mechanisms. Homology between enzyme pairs close in the SMM was higher than expected by chance but was still rare. When observed, homologues usually conserved their reaction mechanism and/or co-factor binding rather than shared substrate binding. The correlation between pathway distance and gene intervals was clear. Enzymes catalysing nearby SMM reactions were usually encoded by genes close by on the E. coli chromosome. We found many co-regulated blocks of three to four genes (usually non-homologous) encoding enzymes occurring within four metabolic steps of one another; nearly all of these blocks formed part of known or predicted operons. The "inline reuse" of enzymes (i.e. the use of the same enzyme to catalyse two or more different steps of a metabolic pathway) is also discussed: of these enzymes, four were multifunctional (i.e. catalysed a different reaction in each instance), nine had multiple substrate specificity (i.e. catalysed the same reaction on different substrates in each instance) and one catalysed the same reaction on the same substrate but as part of two different complexes. We also identified 59 sets of isozymic proteins most commonly duplicated to function under different conditions, or with a different preferred substrate or minor substrate. In addition to transcriptional units, isozymes and inline reuse of enzymes provide mechanisms for controlling the SMM network. Our data suggest that several pathway evolution mechanisms may occur in concert, although chemistry-driven duplication/recruitment is favoured. SMM exploits regulatory strategies involving chromosomal location, isozymes and the reuse of enzymes.

Experimental determination of translational starts using peptide mass mapping and tandem mass spectrometry within the proteome of Mycobacterium tuberculosis.

Identification of protein translation start sites is largely a bioinformatics exercise, with relatively few confirmed by N-terminal sequencing. Translation start site determination is critical for defining both the protein sequence and the upstream DNA which may contain regulatory motifs. It is demonstrated here that translation start sites can be determined during routine protein identification, using MALDI-MS and MS/MS data to select the correct N-terminal sequence from a list of alternatives generated in silico. Applying the method to 13 proteins from Mycobacterium tuberculosis, 11 predicted translational start sites were confirmed, and two reassigned. The authors suggest that these data (be they confirmation or reassignments) are important for the annotation of both this genome and those of organisms with related genes. It was also shown that N-acetylation, reported to be rare in prokaryotes, was present in three of the 13 proteins (23 %), suggesting that in the mycobacteria this modification may be common, and an important regulator of protein function, although more proteins need to be analysed. This method can be performed with little or no additional experimental work during proteomics investigations.

Analysis of metabolic networks using a pathway distance metric through linear programming.

The solution of the shortest path problem in biochemical systems constitutes an important step for studies of their evolution. In this paper, a linear programming (LP) algorithm for calculating minimal pathway distances in metabolic networks is studied. Minimal pathway distances are identified as the smallest number of metabolic steps separating two enzymes in metabolic pathways. The algorithm deals effectively with circularity and reaction directionality. The applicability of the algorithm is illustrated by calculating the minimal pathway distances for Escherichia coli small molecule metabolism enzymes, and then considering their correlations with genome distance (distance separating two genes on a chromosome) and enzyme function (as characterised by enzyme commission number). The results illustrate the effectiveness of the LP model. In addition, the data confirm that propinquity of genes on the genome implies similarity in function (as determined by co-involvement in the same region of the metabolic network), but suggest that no correlation exists between pathway distance and enzyme function. These findings offer insight into the probable mechanism of pathway evolution.

Gene3D: structural assignment for whole genes and genomes using the CATH domain structure database.

We present a novel web-based resource, Gene3D, of precalculated structural assignments to gene sequences and whole genomes. This resource assigns structural domains from the CATH database to whole genes and links these to their curated functional and structural annotations within the CATH domain structure database, the functional Dictionary of Homologous Superfamilies (DHS) and PDBsum. Currently Gene3D provides annotation for 36 complete genomes (two eukaryotes, six archaea, and 28 bacteria). On average, between 30% and 40% of the genes of a given genome can be structurally annotated. Matches to structural domains are found using the profile-based method (PSI-BLAST). and a novel protocol, DRange, is used to resolve conflicts in matches involving different homologous superfamilies.

A practical and robust sequence search strategy for structural genomics target selection.

MOTIVATION: Target selection strategies for structural genomic projects must be able to prioritize gene regions on the basis of significant sequence similarity with proteins that have already been structurally determined. With the rapid development of protein comparison software a robust prioritization scheme should be independent of the choice of algorithm and be able to incorporate different sequence similarity thresholds. RESULTS: A robust target selection strategy has been developed that can assign a priority level to all genes in any genome. Structural assignments to genome sequences are calculated at two thresholds and six levels (1-6) describe the prioritization of all whole genes and partial gene regions. This simple two-threshold approach can be implemented with any fold recognition or homology detection algorithms. The results for 10 genomes are presented using the SSEARCH and PSI-BLAST programs. AVAILABILITY: Programs are available on request from the authors.

The Mycobacterium tuberculosis ino1 gene is essential for growth and virulence.

Inositol is utilized by Mycobacterium tuberculosis in the production of its major thiol and of essential cell wall lipoglycans. We have constructed a mutant lacking the gene encoding inositol-1-phosphate synthase (ino1), which catalyses the first committed step in inositol synthesis. This mutant is only viable in the presence of extremely high levels of inositol. Mutant bacteria cultured in inositol-free medium for four weeks showed a reduction in levels of mycothiol, but phosphatidylinositol mannoside, lipomannan and lipoarabinomannan levels were not altered. The ino1 mutant was attenuated in resting macrophages and in SCID mice. We used site-directed mutagenesis to alter four putative active site residues; all four alterations resulted in a loss of activity, and we demonstrated that a D310N mutation caused loss of the active site Zn2+ ion and a conformational change in the NAD+ cofactor.