In silico detection of control signals: mRNA 3′-end-processing sequences in diverse species

We have investigated mRNA 3′-end-processing signals in each of six eukaryotic species (yeast, rice, arabidopsis, fruitfly, mouse, and human) through the analysis of more than 20,000 3′-expressed sequence tags. The use and conservation of the canonical AAUAAA element vary widely among the six species and are especially weak in plants and yeast. Even in the animal species, the AAUAAA signal does not appear to be as universal as indicated by previous studies. The abundance of single-base variants of AAUAAA correlates with their measured processing efficiencies. As found previously, the plant polyadenylation signals are more similar to those of yeast than to those of animals, with both common content and arrangement of the signal elements. In all species examined, the complete polyadenylation signal appears to consist of an aggregate of multiple elements. In light of these and previous results, we present a broadened concept of 3′-end-processing signals in which no single exact sequence element is universally required for processing. Rather, the total efficiency is a function of all elements and, importantly, an inefficient word in one element can be compensated for by strong words in other elements. These complex patterns indicate that effective tools to identify 3′-end-processing signals will require more than consensus sequence identification.

The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities

The Escherichia coli MG1655 genome has been completely sequenced. The annotated sequence, biochemical information, and other information were used to reconstruct the E. coli metabolic map. The stoichiometric coefficients for each metabolic enzyme in the E. coli metabolic map were assembled to construct a genome-specific stoichiometric matrix. The E. coli stoichiometric matrix was used to define the system's characteristics and the capabilities of E. coli metabolism. The effects of gene deletions in the central metabolic pathways on the ability of the in silico metabolic network to support growth were assessed, and the in silico predictions were compared with experimental observations. It was shown that based on stoichiometric and capacity constraints the in silico analysis was able to qualitatively predict the growth potential of mutant strains in 86% of the cases examined. Herein, it is demonstrated that the synthesis of in silico metabolic genotypes based on genomic, biochemical, and strain-specific information is possible, and that systems analysis methods are available to analyze and interpret the metabolic phenotype.

Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes

We created a simulation based on experimental data from bacteriophage T7 that computes the developmental cycle of the wild-type phage and also of mutants that have an altered genome order. We used the simulation to compute the fitness of more than 105 mutants. We tested these computations by constructing and experimentally characterizing T7 mutants in which we repositioned gene 1, coding for T7 RNA polymerase. Computed protein synthesis rates for ectopic gene 1 strains were in moderate agreement with observed rates. Computed phage-doubling rates were close to observations for two of four strains, but significantly overestimated those of the other two. Computations indicate that the genome organization of wild-type T7 is nearly optimal for growth: only 2.8% of random genome permutations were computed to grow faster, the highest 31% faster, than wild type. Specific discrepancies between computations and observations suggest that a better understanding of the translation efficiency of individual mRNAs and the functions of qualitatively “nonessential” genes will be needed to improve the T7 simulation. In silico representations of biological systems can serve to assess and advance our understanding of the underlying biology. Iteration between computation, prediction, and observation should increase the rate at which biological hypotheses are formulated and tested.

Mutators and sex in bacteria: Conflict between adaptive strategies

Bacterial mutation rates can increase and produce genetic novelty, as shown by in vitro and in silico experiments. Despite the cost due to a heavy deleterious mutation load, mutator alleles, which increase the mutation rate, can spread in asexual populations during adaptation because they remain associated with the rare favorable mutations they generate. This indirect selection for a genetic system generating diversity (second-order selection) is expected to be highly sensitive to changes in the dynamics of adaptation. Here we show by a simulation approach that even rare genetic exchanges, such as bacterial conjugation or transformation, can dramatically reduce the selection of mutators. Moreover, drift or competition between the processes of mutation and recombination in the course of adaptation reveal how second-order selection is unable to optimize the rate of generation of novelty.

Predicting crossover generation in DNA shuffling

We introduce a quantitative framework for assessing the generation of crossovers in DNA shuffling experiments. The approach uses free energy calculations and complete sequence information to model the annealing process. Statistics obtained for the annealing events then are combined with a reassembly algorithm to infer crossover allocation in the reassembled sequences. The fraction of reassembled sequences containing zero, one, two, or more crossovers and the probability that a given nucleotide position in a reassembled sequence is the site of a crossover event are estimated. Comparisons of the predictions against experimental data for five example systems demonstrate good agreement despite the fact that no adjustable parameters are used. An in silico case study of a set of 12 subtilases examines the effect of fragmentation length, annealing temperature, sequence identity and number of shuffled sequences on the number, type, and distribution of crossovers. A computational verification of crossover aggregation in regions of near-perfect sequence identity and the presence of synergistic reassembly in family DNA shuffling is obtained.

Complete genomic sequence of Pasteurella multocida,Pm70

We present here the complete genome sequence of a common avian clone of Pasteurella multocida, Pm70. The genome of Pm70 is a single circular chromosome 2,257,487 base pairs in length and contains 2,014 predicted coding regions, 6 ribosomal RNA operons, and 57 tRNAs. Genome-scale evolutionary analyses based on pairwise comparisons of 1,197 orthologous sequences between P. multocida, Haemophilus influenzae, and Escherichia coli suggest that P. multocida and H. influenzae diverged ≈270 million years ago and the γ subdivision of the proteobacteria radiated about 680 million years ago. Two previously undescribed open reading frames, accounting for ≈1% of the genome, encode large proteins with homology to the virulence-associated filamentous hemagglutinin of Bordetella pertussis. Consistent with the critical role of iron in the survival of many microbial pathogens, in silico and whole-genome microarray analyses identified more than 50 Pm70 genes with a potential role in iron acquisition and metabolism. Overall, the complete genomic sequence and preliminary functional analyses provide a foundation for future research into the mechanisms of pathogenesis and host specificity of this important multispecies pathogen.

GenEST, a powerful bidirectional link between cDNA sequence data and gene expression profiles generated by cDNA-AFLP

The release of vast quantities of DNA sequence data by large-scale genome and expressed sequence tag (EST) projects underlines the necessity for the development of efficient and inexpensive ways to link sequence databases with temporal and spatial expression profiles. Here we demonstrate the power of linking cDNA sequence data (including EST sequences) with transcript profiles revealed by cDNA-AFLP, a highly reproducible differential display method based on restriction enzyme digests and selective amplification under high stringency conditions. We have developed a computer program (GenEST) that predicts the sizes of virtual transcript-derived fragments (TDFs) of in silico-digested cDNA sequences retrieved from databases. The vast majority of the resulting virtual TDFs could be traced back among the thousands of TDFs displayed on cDNA-AFLP gels. Sequencing of the corresponding bands excised from cDNA-AFLP gels revealed no inconsistencies. As a consequence, cDNA sequence databases can be screened very efficiently to identify genes with relevant expression profiles. The other way round, it is possible to switch from cDNA-AFLP gels to sequences in the databases. Using the restriction enzyme recognition sites, the primer extensions and the estimated TDF size as identifiers, the DNA sequence(s) corresponding to a TDF with an interesting expression pattern can be identified. In this paper we show examples in both directions by analyzing the plant parasitic nematode Globodera rostochiensis. Various novel pathogenicity factors were identified by combining ESTs from the infective stage juveniles with expression profiles of ∼4000 genes in five developmental stages produced by cDNA-AFLP.