A computational study of lambda-lac mutants

Biological Sources of Intrinsic and Extrinsic Noise in cI Expression of Lysogenic Phage Lambda

Genetically identical cells exposed to homogeneous environment can show remarkable phenotypic difference. To predict how phenotype is shaped, understanding of how each factor contributes is required. During gene expression processes, noise could arise either intrinsically in biochemical processes of gene expression or extrinsically from other cellular processes such as cell growth. In this work, important noise sources in gene expression of phage λ lysogen are quantified using models described by stochastic differential equations (SDEs). Results show that DNA looping has sophisticated impacts on gene expression noise: When DNA looping provides autorepression, like in wild type, it reduces noise in the system; When the autorepression is defected as it is in certain mutants, DNA looping increases expression noise. We also study how each gene operator affects the expression noise by changing the binding affinity between the gene and the transcription factor systematically. We find that the system shows extraordinarily large noise when the binding affinity is in certain range, which changes the system from monostable to bistable. In addition, we find that cell growth causes non-negligible noise, which increases with gene expression level. Quantification of noise and identification of new noise sources will provide deeper understanding on how stochasticity impacts phenotype.

Taking into account nucleosomes for predicting gene expression

The eukaryotic genome is organized in a chain of nucleosomes that consist of 145-147 bp of DNA wrapped around a histone octamer protein core. Binding of transcription factors (TF) to nucleosomal DNA is frequently impeded, which makes it a challenging task to calculate TF occupancy at a given regulatory genomic site for predicting gene expression. Here, we review methods to calculate TF binding to DNA in the presence of nucleosomes. The main theoretical problems are (i) the computation speed that is becoming a bottleneck when partial unwrapping of DNA from the nucleosome is considered, (ii) the perturbation of the binding equilibrium by the activity of ATP-dependent chromatin remodelers, which translocate nucleosomes along the DNA, and (iii) the model parameterization from high-throughput sequencing data and fluorescence microscopy experiments in living cells. We discuss strategies that address these issues to efficiently compute transcription factor binding in chromatin.

Predicting gene-regulation functions: lessons from temperate bacteriophages

Gene-regulation functions (GRF) provide a unique characteristic of a cis-regulatory module (CRM), relating the concentrations of transcription factors (input) to the promoter activities (output). The challenge is to predict GRFs from the sequence. Here we systematically consider the lysogeny-lysis CRMs of different temperate bacteriophages such as the Lactobacillus casei phage A2, Escherichia coli phages lambda, and 186 and Lactococcal phage TP901-1. This study allowed explaining a recent experimental puzzle on the role of Cro protein in the lambda switch. Several general conclusions have been drawn: 1), long-range interactions, multilayer assembly and DNA looping may lead to complex GRFs that cannot be described by linear functions of binding site occupancies; 2), in general, GRFs cannot be described by the Boolean logic, whereas a three-state non-Boolean logic suffices for the studied examples; 3), studied CRMs of the intact phages seemed to have a similar GRF topology (the number of plateaus and peaks corresponding to different expression regimes); we hypothesize that functionally equivalent CRMs might have topologically equivalent GRFs for a larger class of genetic systems; and 4) within a given GRF class, a set of mechanistic-to-mathematical transformations has been identified, which allows shaping the GRF before carrying out a system-level analysis.