Symmetry in the Language of Gene Expression: A Survey of Gene Promoter Networks in Multiple Bacterial Species and Non-σ Regulons

Abstract

Abstract:The language of gene expression displays topological symmetry. An important step during gene expression is the binding of transcriptional proteins to DNA promoters adjacent to a gene. Some proteins bind to many promoters in a genome, defining a regulon of genes wherein each promoter might vary in DNA sequence relative to the average consensus. Here we examine the linguistic organization of gene promoter networks, wherein each node in the network represents a promoter and links between nodes represent the extent of base pair-sharing. Prior work revealed a fractal nucleus in several σ-factor regulons from Escherichia coli. We extend these findings to show fractal nuclei in gene promoter networks from three bacterial species, E. coli, Bacillus subtilis, and Pseudomonas aeruginosa. We surveyed several non-σ transcription factors from these species and found that many contain a nucleus that is both visually and numerically fractal. Promoter footprint size scaled as a negative power-law with both information entropy and fractal dimension, while the latter two parameters scaled positively and linearly. The fractal dimension of the diffuse networks (d B = ~1.7) was close to that expected of a diffusion limited aggregation process, confirming prior predictions as to a possible mechanism for development of this structure.

Biocomplexity and Fractality in the Search of Biomarkers of Aging and Pathology: Mitochondrial DNA Profiling of Parkinson’s Disease

“…We have recently proposed a method of lacunarity analysis of chaos game representation (CGR) of mtDNA sequences [33] able to discriminate between aging and AD on the basis of mtDNA mutation profiles. The method was developed taking into account the complexity of living beings and fractal properties of many anatomic and physiologic structures, among which is mtDNA [34][35][36][37][38][39]. In particular, the concept that aging can be considered as a "secondary product" of the temporal evolution of a dynamic nonlinear system [40][41][42], governed by the laws of deterministic chaos, can explain the variability observed in the senescent phenotype [33].…”

Complexity and Symmetries In DNA Sequences

“…In order to measure the heterogeneity of data, the entropy function has been considered and it gives a measure of the information content [1,29,50,56,57,68]. In other words, we can roughly say that less information means larger uncertainty, and vice versa, more information leads to a more deterministic model.…”

“…When this sequence is converted into a digital sequence, it can be studied as a numerical signal [35,60,66], and in some recent papers many results were obtained about its multifractality [5,9,11,19,20,41,42] and its influence on DNA [8,[47][48][49]58], the existence of long-range correlation [4, 7, 10, 12, 13, 24, 43, 45, 46, 53, 61-63, 67, 69], and the information content and measure of its complexity [1,21,22,29,44,50,56,57,68]. Almost all papers on these topics are aimed at detecting the existence of regular patterns in the genomic signal [3,6,23,27,28,30,33,34,37,39,51,54], thus speculating on a possible functional meaning.…”

On the Existence of Wavelet Symmetries in Archaea DNA

“…Another fundamental parameter, related to the information content of a sequence which measures the heterogeneity of data, is the information entropy (or Shannon entropy) [ 36 – 42 ]. Based on the axiom that less information implies a larger uncertainty and vice versa that more information leads us to a more deterministic model, the entropy concept has been recently offering some interesting interpretations about uncertainty in DNA.…”