Cell-cycle-dependent transcriptional and translational DNA-damage response of 2 ribonucleotide reductase genes in S. cerevisiae

The ribonucleotide reductase (RNR) enzyme catalyzes an essential step in the production of deoxyribonucleotide triphosphates (dNTPs) in cells. Bulk biochemical measurements in synchronized Saccharomyces cerevisiae cells suggest that RNR mRNA production is maximal in late G1 and S phases; however, damaged DNA induces RNR transcription throughout the cell cycle. But such en masse measurements reveal neither cell-to-cell heterogeneity in responses nor direct correlations between transcript and protein expression or localization in single cells which may be central to function. We overcame these limitations by simultaneous detection of single RNR transcripts and also Rnr proteins in the same individual asynchronous S. cerevisiae cells, with and without DNA damage by methyl methanesulfonate (MMS). Surprisingly, RNR subunit mRNA levels were comparably low in both damaged and undamaged G1 cells and highly induced in damaged S/G2 cells. Transcript numbers became correlated with both protein levels and localization only upon DNA damage in a cell cycle-dependent manner. Further, we showed that the differential RNR response to DNA damage correlated with variable Mec1 kinase activity in the cell cycle in single cells. The transcription of RNR genes was found to be noisy and non-Poissonian in nature. Our results provide vital insight into cell cycle-dependent RNR regulation under conditions of genotoxic stress.Massachusetts Institute of Technology. Center for Environmental Health Sciences (deriving from NIH P30-ES002109)National Institutes of Health (U.S.) (grant R01-CA055042)National Institutes of Health (U.S.) (grant DP1-OD006422)Massachusetts Institute of Technology (CSBi Merck-MIT Fellowship

Cognitive testing of physical activity and acculturation questions in recent and long-term Latino immigrants

<p>Abstract</p> <p>Background</p> <p>We ascertained the degree to which language (English versus Spanish), and residence time in the US influence responses to survey questions concerning two topics: self-reported acculturation status, and recent physical activity (PA). This topic is likely to be of general interest because of growing numbers of immigrants in countries worldwide.</p> <p>Methods</p> <p>We carried out qualitative (cognitive) interviews of survey items on acculturation and physical activity on 27 Latino subjects from three groups: (a) In Spanish, of those of low residence time (less than five years living in the U.S.) (n = 9); (b) In Spanish, of those of high residence time (15 or more years in the U.S) (n = 9); and (c) in English, of those of high residence time (n = 9).</p> <p>Results</p> <p>There were very few language translation problems; general question design defects and socio-cultural challenges to survey responses were more common. Problems were found for both acculturation and PA questions, with distinct problem types for the two question areas. Residence time/language group was weakly associated with overall frequency of problems observed: low residence time/Spanish (86%), high residence time/Spanish (67%), and English speaking groups (62%).</p> <p>Conclusions</p> <p>Standardized survey questions related to acculturation and physical activity present somewhat different cognitive challenges. For PA related questions, problems with such questions were similar regardless of subject residence time or language preference. For acculturation related questions, residence time/language or education level influenced responses to such questions. These observations should help in the interpretation of survey results for culturally diverse populations.</p

A Critical Analysis of Atoh7 (Math5) mRNA Splicing in the Developing Mouse Retina

The Math5 (Atoh7) gene is transiently expressed during retinogenesis by progenitors exiting mitosis, and is essential for ganglion cell (RGC) development. Math5 contains a single exon, and its 1.7 kb mRNA encodes a 149-aa polypeptide. Mouse Math5 mutants have essentially no RGCs or optic nerves. Given the importance of this gene in retinal development, we thoroughly investigated the possibility of Math5 mRNA splicing by Northern blot, 3′RACE, RNase protection assays, and RT-PCR, using RNAs extracted from embryonic eyes and adult cerebellum, or transcribed in vitro from cDNA clones. Because Math5 mRNA contains an elevated G+C content, we used graded concentrations of betaine, an isostabilizing agent that disrupts secondary structure. Although ∼10% of cerebellar Math5 RNAs are spliced, truncating the polypeptide, our results show few, if any, spliced Math5 transcripts exist in the developing retina (<1%). Rare deleted cDNAs do arise via RT-mediated RNA template switching in vitro, and are selectively amplified during PCR. These data differ starkly from a recent study (Kanadia and Cepko 2010), which concluded that the vast majority of Math5 and other bHLH transcripts are spliced to generate noncoding RNAs. Our findings clarify the architecture of the Math5 gene and its mechanism of action. These results have implications for all members of the bHLH gene family, for any gene that is alternatively spliced, and for the interpretation of all RT-PCR experiments

Crk and CrkL adaptor proteins: networks for physiological and pathological signaling

The Crk adaptor proteins (Crk and CrkL) constitute an integral part of a network of essential signal transduction pathways in humans and other organisms that act as major convergence points in tyrosine kinase signaling. Crk proteins integrate signals from a wide variety of sources, including growth factors, extracellular matrix molecules, bacterial pathogens, and apoptotic cells. Mounting evidence indicates that dysregulation of Crk proteins is associated with human diseases, including cancer and susceptibility to pathogen infections. Recent structural work has identified new and unusual insights into the regulation of Crk proteins, providing a rationale for how Crk can sense diverse signals and produce a myriad of biological responses

Sampling strategies to capture single-cell heterogeneity.

Advances in single-cell technologies have highlighted the prevalence and biological significance of cellular heterogeneity. A critical question researchers face is how to design experiments that faithfully capture the true range of heterogeneity from samples of cellular populations. Here we develop a data-driven approach, illustrated in the context of image data, that estimates the sampling depth required for prospective investigations of single-cell heterogeneity from an existing collection of samples