How to Regulate a Gene: To Repress or to Activate?

Gene-expression responses to an input can depend on growth conditions; in this issue, Sasson et al. (2012) show that this dependence is lower when the input results in a high degree of promoter occupancy

Карти роботи Йогана Баптиста Гомана в збірці Національного музею історії України

Стаття присвячена відомому німецькому картографу XVIII ст. Й.Б.Гоману і його роботам, що зберігаються в фондах Національного музею історії України. Ці карти мають виняткове значення як для дослідників, що займаються вивченням проблем з історії України та Європи, так і для тих вчених, які досліджують питання історії картографічної науки на теренах Європи.The article is dedicated to a famous German cartographer of the 18th century J.B. Homanno and his works, that belong to the fund collections of National Museum of the History of Ukraine. These maps are of exceptional importance for the researchers who deal with the history of Ukraine and Europe, and equally for those scientists who study the problems of the history of European cartography

Single molecule fluorescent in situ hybridization (smFISH) of C. elegans worms and embryos

In C. elegans, the expression pattern of a gene provides important clues to understanding its biological function. To accurately depict endogenous transcriptional activity, a highly sensitive method is required to measure transcript levels in the intact tissue across various developmental stages. Conventional RNA in situ hybridization methods using hapten- (biotin or digoxygenin) labeled RNA probes rely on antibody binding for visualization, and are thus only semi-quantitative at best (Raap et al. 1995; Levsky et al. 2003). Additionally, hapten-labeled probes are prone to diffuse localization (when conjugated with alkaline phosphatase), low sensitivity (when conjugated with fluorescent molecules), and non-specific probe binding. Here, we introduce a recently developed mRNA in situ hybridization method (Raj et al. 2008) that circumvents the above difficulties to give single molecule resolution of transcript detection

Allele-specific detection of single mRNA molecules in situ

We describe a method for fluorescent in situ identification of individual mRNA molecules, allowing quantitative and accurate measurements of allele-specific transcripts that differ by only a few nucleotides, in single cells. By using a combination of allele-specific and non-allele-specific probe libraries, we achieve over 95% detection accuracy. We investigate the allele-specific stochastic expression of the pluripotency factor Nanog in murine embryonic stem cells

Differential stoichiometry among core ribosomal proteins

Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its deregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.Comment: 31 pages, 8 figure

Single-Cell Expression Analyses during Cellular Reprogramming Reveal an Early Stochastic and a Late Hierarchic Phase

SummaryDuring cellular reprogramming, only a small fraction of cells become induced pluripotent stem cells (iPSCs). Previous analyses of gene expression during reprogramming were based on populations of cells, impeding single-cell level identification of reprogramming events. We utilized two gene expression technologies to profile 48 genes in single cells at various stages during the reprogramming process. Analysis of early stages revealed considerable variation in gene expression between cells in contrast to late stages. Expression of Esrrb, Utf1, Lin28, and Dppa2 is a better predictor for cells to progress into iPSCs than expression of the previously suggested reprogramming markers Fbxo15, Fgf4, and Oct4. Stochastic gene expression early in reprogramming is followed by a late hierarchical phase with Sox2 being the upstream factor in a gene expression hierarchy. Finally, downstream factors derived from the late phase, which do not include Oct4, Sox2, Klf4, c-Myc, and Nanog, can activate the pluripotency circuitry

A systems-level analysis of perfect adaptation in yeast osmoregulation

available in PMC 2011 June 7.Negative feedback can serve many different cellular functions, including noise reduction in transcriptional networks and the creation of circadian oscillations. However, only one special type of negative feedback (“integral feedback”) ensures perfect adaptation, where steady-state output is independent of steady-state input. Here we quantitatively measure single-cell dynamics in the Saccharomyces cerevisiae hyperosmotic shock network, which regulates membrane turgor pressure. Importantly, we find that the nuclear enrichment of the MAP kinase Hog1 perfectly adapts to changes in external osmolarity, a feature robust to signaling fidelity and operating with very low noise. By monitoring multiple system quantities (e.g., cell volume, Hog1, glycerol) and using varied input waveforms (e.g., steps and ramps), we assess in a minimally invasive manner the network location of the mechanism responsible for perfect adaptation. We conclude that the system contains only one effective integrating mechanism, which requires Hog1 kinase activity and regulates glycerol synthesis but not leakage.National Science Foundation (U.S.) (Graduate Research Fellowship)Massachusetts Institute of Technology (MIT-Merck Graduate Fellowship)National Institutes of Health (U.S.) (NIH grant R01-GM068957)National Institutes of Health (U.S.) (NIH grant 5 R90 DK071511-01