Metabolic modeling of microbial strains in silico.

The large volume of genome-scale data that is being produced and made available in databases on the World Wide Web is demanding the development of integrated mathematical models of cellular processes. The analysis of reconstructed metabolic networks as systems leads to the development of an in silico or computer representation of collections of cellular metabolic constituents, their interactions and their integrated function as a whole. The use of quantitative analysis methods to generate testable hypotheses and drive experimentation at a whole-genome level signals the advent of a systemic modeling approach to cellular and molecular biology.

Functional analysis of gapped microbial genomes: amino acid metabolism of Thiobacillus ferrooxidans.

A gapped genome sequence of the biomining bacterium Thiobacillus ferrooxidans strain ATCC23270 was assembled from sheared DNA fragments (3.2-times coverage) into 1,912 contigs. A total of 2,712 potential genes (ORFs) were identified in 2.6 Mbp (megabase pairs) of Thiobacillus genomic sequence. Of these genes, 2,159 could be assigned functions by using the WIT-Pro/EMP genome analysis system, most with a high degree of certainty. Nine hundred of the genes have been assigned roles in metabolic pathways, producing an overview of cellular biosynthesis, bioenergetics, and catabolism. Sequence similarities, relative gene positions on the chromosome, and metabolic reconstruction (placement of gene products in metabolic pathways) were all used to aid gene assignments and for development of a functional overview. Amino acid biosynthesis was chosen to demonstrate the analytical capabilities of this approach. Only 10 expected enzymatic activities, of the nearly 150 involved in the biosynthesis of all 20 amino acids, are currently unassigned in the Thiobacillus genome. This result compares favorably with 10 missing genes for amino acid biosynthesis in the complete Escherichia coli genome. Gapped genome analysis can therefore give a decent picture of the central metabolism of a microorganism, equivalent to that of a complete sequence, at significantly lower cost.

WIT: integrated system for high-throughput genome sequence analysis and metabolic reconstruction.

The WIT (What Is There) (http://wit.mcs.anl.gov/WIT2/) system has been designed to support comparative analysis of sequenced genomes and to generate metabolic reconstructions based on chromosomal sequences and metabolic modules from the EMP/MPW family of databases. This system contains data derived from about 40 completed or nearly completed genomes. Sequence homologies, various ORF-clustering algorithms, relative gene positions on the chromosome and placement of gene products in metabolic pathways (metabolic reconstruction) can be used for the assignment of gene functions and for development of overviews of genomes within WIT. The integration of a large number of phylogenetically diverse genomes in WIT facilitates the understanding of the physiology of different organisms.

Mathematical simulation and analysis of cellular metabolism and regulation.

MOTIVATION: A better understanding of the biological phenomena observed in cells requires the creation and analysis of mathematical models of cellular metabolism and physiology. The formulation and study of such models must also be simplified as far as possible to cope with the increasing complexity demanded and exponential accumulation of the metabolic reconstructions computed from sequenced genomes. RESULTS: A mathematical simulation workbench, DBsolve, has been developed to simplify the derivation and analysis of mathematical models. It combines: (i) derivation of large-scale mathematical models from metabolic reconstructions and other data sources; (ii) solving and parameter continuation of non-linear algebraic equations (NAEs), including metabolic control analysis; (iii) solving the non-linear stiff systems of ordinary differential equations (ODEs); (iv) bifurcation analysis of ODEs; (v) parameter fitting to experimental data or functional criteria based on constrained optimization. The workbench has been successfully used for dynamic metabolic modeling of some typical biochemical networks (Dolgacheva et al., Biochemistry (Moscow), 6, 1063-1068, 1996; Goldstein and Goryanin, Mol. Biol. (Moscow), 30, 976-983, 1996), including microbial glycolytic pathways, signal transduction pathways and receptor-ligand interactions. AVAILABILITY: DBsolve 5. 00 is freely available from http://websites.ntl.com/ approximately igor.goryanin. CONTACT: gzz78923@ggr.co.uk

MPW: the Metabolic Pathways Database.

The Metabolic Pathwasy Database (MPW) (www.biobase.com/emphome.html/homepage. html.pags/pathways.html) a derivative of EMP (www.biobase.com/EMP) plays a fundamental role in the technology of metabolic reconstructions from sequenced genomes under the PUMA (www.mcs.anl.gov/home/compbio/PUMA/Production/ ReconstructedMetabolism/reconstruction.html), WIT (www.mcs.anl.gov/home/compbio/WIT/wit.html ) and WIT2 (beauty.isdn.msc.anl.gov/WIT2.pub/CGI/user.cgi) systems. In October 1997, it included some 2800 pathway diagrams covering primary and secondary metabolism, membrane transport, signal transduction pathways, intracellular traffic, translation and transcription. In the current public release of MPW (beauty.isdn.mcs.anl.gov/MPW), the encoding is based on the logical structure of the pathways and is represented by the objects commonly used in electronic circuit design. This facilitates drawing and editing the diagrams and makes possible automation of the basic simulation operations such as deriving stoichiometric matrices, rate laws, and, ultimately, dynamic models of metabolic pathways. Individual pathway diagrams, automatically derived from the original ASCII records, are stored as SGML instances supplemented by relational indices. An auxiliary database of compound names and structures, encoded in the SMILES format, is maintained to unambiguously connect the pathways to the chemical structures of their intermediates.

A reconstruction of the metabolism of Methanococcus jannaschii from sequence data.

The interpretation of the Methanococcus jannaschii genome will inevitably require many years of effort. This initial attempt to connect the sequence data to aspects of known biochemistry and to provide an overview of what is already apparent from the sequence data will be refined. Numerous issues remain that can be resolved only by direct biochemical analysis. Let us draw the reader's attention to just a few that might be considered central: (1) We are still missing key enzymes from the glycolytic pathway, and the conjecture is that this is due to ADP-dependency. The existence of glycolytic activity in the cell-free extract should be tested. (2) The issue of whether the Calvin cycle is present needs to be examined. (3) We need to determine whether the 2-oxoglutarate synthase (ferredoxin-dependent) (EC 1.2.7.3) activity is present. (4) The issue of whether cyclic 2,3-bisphosphate is detectable in the cell-free extracts needs to be checked. If it is, this result would confirm our assertion of the two pathways controlling synthesis and degradation of cyclic 2,3-bisphosphate.

The metabolic pathway collection: an update.

The Metabolic Pathway Collection from EMP is an extraction of data from the larger Enzymes and Metabolic Pathways database (EMP). This extraction has been made publicly available in the hope that others will find it useful for a variety of purposes. The original release in October 1995 contained 1814 distinct pathways. The current collection contains 2180. Metabolic reconstructions for the first completely sequenced organisms-Haemophilus influenzae,Mycoplasma genitalium,Saccharomyces cerevisiaeandMethanococcus janaschii-are all included in the current release. All of the pathways in the collections are available as ASCII files in the form generated by the main curator, Evgeni Selkov. In addition, we are offering a more structured encoding of a subset of the collection; our initial release of this subcollection includes all of the pathways inMycoplasma genitalium, and we ultimately intend to offer the entire collection in this form as well.

The metabolic pathway collection from EMP: the enzymes and metabolic pathways database.

The Enzymes and Metabolic Pathways database (EMP) is an encoding of the contents of over 10 000 original publications on the topics of enzymology and metabolism. This large body of information has been transformed into a queryable database. An extraction of over 1800 pictorial representations of metabolic pathways from this collection is freely available on the World Wide Web. We believe that this collection will play an important role in the interpretation of genetic sequence data, as well as offering a meaningful framework for the integration of many other forms of biological data.

Reconstruction of metabolic networks using incomplete information.

This paper describes an approach that uses methods for automated sequence analysis (Gaasterland et al. August 1994) and multiple databases accessed through an object+attribute view of the data (Baehr et al. 1992), together with metabolic pathways, reaction equations, and compounds parsed into a logical representation from the Enzyme and Metabolic Pathway Database (Selkov, Yunus, & et.al. 1994), as the sources of data for automatically reconstructing a weighted partial metabolic network for a prokaryotic organism. Additional information can be provided interactively by the expert user to guide reconstruction.