Always talking to some purpose

AbstractDistinguished molecular biologist, Sydney Brenner, has said he won't write an autobiography. Mark Ptashne reviews the next best thing

Transcription: A Mechanism for Short-Term Memory

SummaryYeast growing for a considerable time in glucose ‘remember’ a previous exposure to galactose, the inducer of its galactose-utilization (GAL) genes. This memory is conveyed by a cytoplasmically transmitted galactokinase working as a signal transducer

Lambda's Switch: Lessons from a Module Swap

A recent experiment has replaced Cro, a crucial component of lambda's genetic switch, with the lac repressor (plus two lac operators). The resulting hybrid phage is viable, but a subtle phenotypic defect explains a puzzle concerning the workings of the switch

Activator Control of Nucleosome Occupancy in Activation and Repression of Transcription

The relationship between chromatin structure and gene expression is a subject of intense study. The universal transcriptional activator Gal4 removes promoter nucleosomes as it triggers transcription, but how it does so has remained obscure. The reverse process, repression of transcription, has often been correlated with the presence of nucleosomes. But it is not known whether nucleosomes are required for that effect. A new quantitative assay describes, for any given location, the fraction of DNA molecules in the population that bears a nucleosome at any given instant. This allows us to follow the time courses of nucleosome removal and reformation, in wild-type and mutant cells, upon activation (by galactose) and repression (by glucose) of the GAL genes of yeast. We show that upon being freed of its inhibitor Gal80 by the action of galactose, Gal4 quickly recruits SWI/SNF to the genes, and that nucleosome “remodeler” rapidly removes promoter nucleosomes. In the absence of SWI/SNF, Gal4′s action also results in nucleosome removal and the activation of transcription, but both processes are significantly delayed. Addition of glucose to cells growing in galactose represses transcription. But if galactose remains present, Gal4 continues to work, recruiting SWI/SNF and maintaining the promoter nucleosome-free despite it being repressed. This requirement for galactose is obviated in a mutant in which Gal4 works constitutively. These results show how an activator's recruiting function can control chromatin structure both during gene activation and repression. Thus, both under activating and repressing conditions, the activator can recruit an enzymatic machine that removes promoter nucleosomes. Our results show that whereas promoter nucleosome removal invariably accompanies activation, reformation of nucleosomes is not required for repression. The finding that there are two routes to nucleosome removal and activation of transcription—one that requires the action of SWI/SNF recruited by the activator, and a slower one that does not—clarifies our understanding of the early events of gene activation, and in particular corrects earlier reports that SWI/SNF plays no role in GAL gene induction. Our finding that chromatin structure is irrelevant for repression as studied here—that is, repression sets in as efficiently whether or not promoter nucleosomes are allowed to reform—contradicts the widely held, but little tested, idea that nucleosomes are required for repression. These findings were made possible by our nucleosome occupancy assay. The assay, we believe, will prove useful in studying other outstanding issues in the field

Nonparametric identification of regulatory interactions from spatial and temporal gene expression data

<p>Abstract</p> <p>Background</p> <p>The correlation between the expression levels of transcription factors and their target genes can be used to infer interactions within animal regulatory networks, but current methods are limited in their ability to make correct predictions.</p> <p>Results</p> <p>Here we describe a novel approach which uses nonparametric statistics to generate ordinary differential equation (ODE) models from expression data. Compared to other dynamical methods, our approach requires minimal information about the mathematical structure of the ODE; it does not use qualitative descriptions of interactions within the network; and it employs new statistics to protect against over-fitting. It generates spatio-temporal maps of factor activity, highlighting the times and spatial locations at which different regulators might affect target gene expression levels. We identify an ODE model for <it>eve </it>mRNA pattern formation in the <it>Drosophila melanogaster </it>blastoderm and show that this reproduces the experimental patterns well. Compared to a non-dynamic, spatial-correlation model, our ODE gives 59% better agreement to the experimentally measured pattern. Our model suggests that protein factors frequently have the potential to behave as both an activator and inhibitor for the same <it>cis</it>-regulatory module depending on the factors' concentration, and implies different modes of activation and repression.</p> <p>Conclusions</p> <p>Our method provides an objective quantification of the regulatory potential of transcription factors in a network, is suitable for both low- and moderate-dimensional gene expression datasets, and includes improvements over existing dynamic and static models.</p

Somitogenesis Clock-Wave Initiation Requires Differential Decay and Multiple Binding Sites for Clock Protein

Somitogenesis is a process common to all vertebrate embryos in which repeated blocks of cells arise from the presomitic mesoderm (PSM) to lay a foundational pattern for trunk and tail development. Somites form in the wake of passing waves of periodic gene expression that originate in the tailbud and sweep posteriorly across the PSM. Previous work has suggested that the waves result from a spatiotemporally graded control protein that affects the oscillation rate of clock-gene expression. With a minimally constructed mathematical model, we study the contribution of two control mechanisms to the initial formation of this gene-expression wave. We test four biologically motivated model scenarios with either one or two clock protein transcription binding sites, and with or without differential decay rates for clock protein monomers and dimers. We examine the sensitivity of wave formation with respect to multiple model parameters and robustness to heterogeneity in cell population. We find that only a model with both multiple binding sites and differential decay rates is able to reproduce experimentally observed waveforms. Our results show that the experimentally observed characteristics of somitogenesis wave initiation constrain the underlying genetic control mechanisms