Stanislaw Cebrat

The relationships between the isoelectric point and: length of proteins, taxonomy and ecology of organisms

BackgroundThe distribution of isoelectric point (pI) of proteins in a proteome is universal for all organisms. It is bimodal dividing the proteome into two sets of acidic and basic proteins. Different species however have different abundance of acidic and basic proteins that may be correlated with taxonomy, subcellular localization, ecological niche of organisms and proteome size.ResultsWe have analysed 1784 proteomes encoded by chromosomes of Archaea, Bacteria, Eukaryota, and also mitochondria, plastids, prokaryotic plasmids, phages and viruses. We have found significant correlation in more than 95% of proteomes between the protein length and pI in proteomes – positive for acidic proteins and negative for the basic ones. Plastids, viruses and plasmids encode more basic proteomes while chromosomes of Archaea, Bacteria, Eukaryota, mitochondria and phages more acidic ones. Mitochondrial proteomes of Viridiplantae, Protista and Fungi are more basic than Metazoa. It results from the presence of basic proteins in the former proteomes and their absence from the latter ones and is related with reduction of metazoan genomes. Significant correlation was found between the pI bias of proteomes encoded by prokaryotic chromosomes and proteomes encoded by plasmids but there is no correlation between eukaryotic nuclear-coded proteomes and proteomes encoded by organelles. Detailed analyses of prokaryotic proteomes showed significant relationships between pI distribution and habitat, relation to the host cell and salinity of the environment, but no significant correlation with oxygen and temperature requirements. The salinity is positively correlated with acidicity of proteomes. Host-associated organisms and especially intracellular species have more basic proteomes than free-living ones. The higher rate of mutations accumulation in the intracellular parasites and endosymbionts is responsible for the basicity of their tiny proteomes that explains the observed positive correlation between the decrease of genome size and the increase of basicity of proteomes. The results indicate that even conserved proteins subjected to strong selectional constraints follow the global trend in the pI distribution.ConclusionThe distribution of pI of proteins in proteomes shows clear relationships with length of proteins, subcellular localization, taxonomy and ecology of organisms. The distribution is also strongly affected by mutational pressure especially in intracellular organisms.

Flip-flop around the origin and terminus of replication in prokaryotic genomes

A response to Evidence for symmetric chromosomal inversions around the replication origin in bacteria by JA Eisen, JF Heidelberg, O White, SL Salzberg. Genome Biology 2000, 1:research0011.1-0011.9.

High correlation between the turnover of nucleotides under mutational pressure and the DNA composition

BackgroundAny DNA sequence is a result of compromise between the selection and mutation pressures exerted on it during evolution. It is difficult to estimate the relative influence of each of these pressures on the rate of accumulation of substitutions. However, it is important to discriminate between the effect of mutations, and the effect of selection, when studying the phylogenic relations between taxa.ResultsWe have tested in computer simulations, and analytically, the available substitution matrices for many genomes, and we have found that DNA strands in equilibrium under mutational pressure have unique feature: the fraction of each type of nucleotide is linearly dependent on the time needed for substitution of half of nucleotides of a given type, with a correlation coefficient close to 1. Substitution matrices found for sequences under selection pressure do not have this property. A substitution matrix for the leading strand of the Borrelia burgdorferi genome, having reached equilibrium in computer simulation, gives a DNA sequence with nucleotide composition and asymmetry corresponding precisely to the third positions in codons of protein coding genes located on the leading strand.ConclusionsParameters of mutational pressure allow us to count DNA composition in equilibrium with this mutational pressure. Comparing any real DNA sequence with the sequence in equilibrium it is possible to estimate the distance between these sequences, which could be used as a measure of the selection pressure. Furthermore, the parameters of the mutational pressure enable direct estimation of the relative mutation rates in any DNA sequence in the studied genome.

Random Deaths in a Computational Model for Age-Structured Populations

Summary The concept of random deaths in a computational model for population dynamics is critically examined. We claim that it is just an artifact, albeit useful, of computational models to limit the size of the populations through the use of the so-called Verhulst factor and has no biological foundation. Alternative implementations of random deaths strategies are discussed and compared. PACS numbers: 07.05.Tp, 87.23.Cc

Total number of coding open reading frames in the yeast genome

At the end of 1996 we approximated the total number of protein coding ORFs in the Saccharomyces cerevisiae genome, based on their properties, as 4700–4800. The number is much smaller than the 5800 which is widely accepted. According to our calculations, there remain about 200–300 orphans—ORFs without known function or homology to already discovered genes, which is only about 5% of the total number of genes. Our results would be questionable if the analysed set of known genes was not a statistically representative sample of the whole set of protein coding genes in the S. cerevisiae genome. Therefore, we repeated our estimation using recently updated databases. In the course of the last 18 months, previously unknown functions of about 500 genes have been found. We have used these to check our method, former results and conclusions. Our previous estimation of the total number of coding ORFs was confirmed. Copyright

Evolution Rates of Genes on Leading and Lagging DNA Strands

Abstract. One of the main causes of bacterial chromosome asymmetry is replication-associated mutational pressure. Different rates of nucleotide substitution accumulation on leading and lagging strands implicate qualitative and quantitative differences in the accumulation of mutations in protein coding sequences lying on different DNA strands. We show that the divergence rate of orthologs situated on leading strands is lower than the divergence rate of those situated on lagging strands. The ratio of the mutation accumulation rate for sequences lying on lagging strands to that of sequences lying on leading strands is rather stable and time-independent. The divergence rate of sequences which changed their positions, with respect to the direction of replication fork movement, is not stable—sequences which have recently changed their positions are the most prone to mutation accumulation. This effect may influence estimations of evolutionary distances between species and the topology of phylogenetic trees.

Mechanisms generating long-range correlation in nucleotide composition of the Borrelia burgdorferi genome

We have analysed protein coding and intergenic sequences in the Borrelia burgdorferi (the Lyme disease bacterium) genome using different kinds of DNA walks. Genes occupying the leading strand of DNA have significantly different nucleotide composition from genes occupying the lagging strand. Nucleotide compositional bias of the two DNA strands reflects the aminoacid composition of proteins. 96% of genes coding for ribosomal proteins lie on the leading DNA strand, which suggests that the positions of these as well as other genes are non-random. In the B. burgdorferi genome, the asymmetry in intergenic DNA sequences is lower than the asymmetry in the third positions in codons. All these characters of the B. burgdorferi genome suggest that both replication-associated mutational pressure and recombination mechanisms have established the specific structure of the genome and now any recombination leading to inversion of a gene in respect to the direction of replication is forbidden. This property of the genome allows us to assume that it is in a steady state, which enables us to fix some parameters for simulations of DNA evolution.

How many protein-coding genes are there in the Saccharomyces cerevisiae genome?

We have compared the results of estimations of the total number of protein‐coding genes in the Saccharomyces cerevisiae genome, which have been obtained by many laboratories since the yeast genome sequence was published in 1996. We propose that there are 5300–5400 genes in the genome. This makes the first estimation of the number of intronless ORFs longer than 100 codons, based on the features of the set of genes with phenotypes known in 1997 to be correct. This estimation assumed that the set of the first 2300 genes with known phenotypes was representative for the whole set of protein‐coding genes in the genome. The same method used in this paper for the approximation of the total number of protein‐coding sequences among more than 40 000 ORFs longer than 20 codons gives a result that is only slightly higher. This suggests that there are still some non‐coding ORFs in the databases and a few dozen small ORFs, not yet annotated, which probably code for proteins. Copyright

The role of the genetic code in generating new coding sequences inside existing genes

The genetic code has a very interesting property--it generates an open reading frame (ORF) inside a coding sequence, in a specific phase of the antisense strand with much higher probability than in the random DNA sequences. Furthermore, these antisense ORFs (A-ORFs) possess the same features as real genes--the asymmetry in the nucleotide composition at the first and second positions in codons. About two thirds of the 2997 overlapping ORFs in the yeast genome possess this feature. Thus, the question arises: has this feature of the genetic code been exploited in the evolution of genes? We have searched the FASTA data bases for homologies with the antisense translation products of a specific class of genes and we have found some sequences with relatively high homology. Many of them have scores which could be randomly found in the searched data bases with a probability lower than 10(-6). We conclude that some genes could arise by positioning a copy of the original gene under a promoter in the opposite direction in such a way that both, the original gene and its copy initially use the same nucleotides in the third, degenerated positions in codons.

Housekeeping Genes And Death Genes In The Penna Aging Model

The Penna model of aging predicts the accumulation of defective genes expressed after the organism reaches the minimum reproduction age in the genetic pool of the population. The accumulation of defects in the genomes implicates the specific age structure of the modeled populations. Nevertheless, the fraction of defective alleles at loci switched on before the reproduction period does not depend on exact age when precisely they are switched on, it may be just after conception or after birth. We have modeled the mortality of a population in the period before the minimum reproduction age, even before birth, assuming that sets of genes of different size are switched on in different periods of the life span.