Percolation, Morphogenesis, and Burgers Dynamics in Blood Vessels Formation

Experiments of in vitro formation of blood vessels show that cells randomly spread on a gel matrix autonomously organize to form a connected vascular network. We propose a simple model which reproduces many features of the biological system. We show that both the model and the real system exhibit a fractal behavior at small scales, due to the process of migration and dynamical aggregation, followed at large scale by a random percolation behavior due to the coalescence of aggregates. The results are in good agreement with the analysis performed on the experimental data.Comment: 4 pages, 11 eps figure

Direct observation of mammalian cell growth and size regulation

We introduce a microfluidic system for simultaneously measuring single cell mass and cell cycle progression over multiple generations. We use this system to obtain over 1,000 hours of growth data from mouse lymphoblast and pro-B-cell lymphoid cell lines. Cell lineage analysis revealed a decrease in the growth rate variability at the G1/S phase transition, which suggests the presence of a growth rate threshold for maintaining size homeostasis

GMASS ultradeep spectroscopy of galaxies at z~2 - VII. Sample selection and spectroscopy

The populations of both quiescent and actively star-forming galaxies at 1<z<2 are still under-represented in our spectroscopic census of galaxies throughout the history of the Universe. In the light of galaxy formation models, however, the evolution of galaxies at these redshifts is of pivotal importance and merits further investigation. We therefore designed a spectroscopic observing campaign of a sample of both massive, quiescent and star-forming galaxies at z>1.4, called Galaxy Mass Assembly ultra-deep Spectroscopic Survey (GMASS). To determine redshifts and physical properties, such as metallicity, dust content, dynamical masses, and star formation history, we performed ultra-deep spectroscopy with the red-sensitive optical spectrograph FORS2 at the VLT. Our sample consists of objects, within the CDFS/GOODS area, detected at 4.5 micron, to be sensitive to stellar mass rather than star formation intensity. The spectroscopic targets were selected with a photometric redshift constraint (z>1.4) and magnitude constraints (B(AB)<26, I(AB)<26.5), which should ensure that these are faint, distant, and fairly massive galaxies. We present the sample selection, survey design, observations, data reduction, and spectroscopic redshifts. Up to 30 hours of spectroscopy of 174 spectroscopic targets and 70 additional objects enabled us to determine 210 redshifts, of which 145 are at z>1.4. From the redshifts and photometry, we deduce that the BzK selection criteria are efficient (82%) and suffer low contamination (11%). Several papers based on the GMASS survey show its value for studies of galaxy formation and evolution. We publicly release the redshifts and reduced spectra. In combination with existing and on-going additional observations in CDFS/GOODS, this data set provides a legacy for future studies of distant galaxies.Comment: Accepted by A&A in August 2012, 45 pages, public release of reduced spectra currently on www.mpe.mpg.de/~kurk/gmas

Control of Transcription by Cell Size

Cell size increases significantly with increasing ploidy. Differences in cell size and ploidy are associated with alterations in gene expression, although no direct connection has been made between cell size and transcription. Here we show that ploidy-associated changes in gene expression reflect transcriptional adjustment to a larger cell size, implicating cellular geometry as a key parameter in gene regulation. Using RNA-seq, we identified genes whose expression was altered in a tetraploid as compared with the isogenic haploid. A significant fraction of these genes encode cell surface proteins, suggesting an effect of the enlarged cell size on the differential regulation of these genes. To test this hypothesis, we examined expression of these genes in haploid mutants that also produce enlarged size. Surprisingly, many genes differentially regulated in the tetraploid are identically regulated in the enlarged haploids, and the magnitude of change in gene expression correlates with the degree of size enlargement. These results indicate a causal relationship between cell size and transcription, with a size-sensing mechanism that alters transcription in response to size. The genes responding to cell size are enriched for those regulated by two mitogen-activated protein kinase pathways, and components in those pathways were found to mediate size-dependent gene regulation. Transcriptional adjustment to enlarged cell size could underlie other cellular changes associated with polyploidy. The causal relationship between cell size and transcription suggests that cell size homeostasis serves a regulatory role in transcriptome maintenance.National Institutes of Health (U.S.) (grant GM035010)National Institutes of Health (U.S.) (grant GM040266

Cell-Cycle Dependence of Transcription Dominates Noise in Gene Expression

The large variability in mRNA and protein levels found from both static and dynamic measurements in single cells has been largely attributed to random periods of transcription, often occurring in bursts. The cell cycle has a pronounced global role in affecting transcriptional and translational output, but how this influences transcriptional statistics from noisy promoters is unknown and generally ignored by current stochastic models. Here we show that variable transcription from the synthetic tetO promoter in S. cerevisiae is dominated by its dependence on the cell cycle. Real-time measurements of fluorescent protein at high expression levels indicate tetO promoters increase transcription rate ~2-fold in S/G2/M similar to constitutive genes. At low expression levels, where tetO promoters are thought to generate infrequent bursts of transcription, we observe random pulses of expression restricted to S/G2/M, which are correlated between homologous promoters present in the same cell. The analysis of static, single-cell mRNA measurements at different points along the cell cycle corroborates these findings. Our results demonstrate that highly variable mRNA distributions in yeast are not solely the result of randomly switching between periods of active and inactive gene expression, but instead largely driven by differences in transcriptional activity between G1 and S/G2/M.GM095733BBBE 103316MIT Startup Fun

Phenotypic heterogeneity in fungi: importance and methodology

Phenotypic heterogeneity describes the variation that exists between individual cells, spores or other biological entities within genetically-uniform populations of fungi or other organisms. Studies over the last 10-15 years have successfully used laboratory- and modelling-based approaches to demonstrate the prevalence of phenotypic heterogeneity and characterise the molecular bases of the phenomenon (primarily centred around heterogeneous gene expression). In contrast to progress in these areas, the relevance of phenotypic heterogeneity for the competitive success of organisms in different natural scenarios, although widely speculated upon, has only recently begun to be investigated. This focus review addresses this latter question as tackled in recent studies with yeasts and filamentous fungi. We concentrate on the relevance to fungal activities such as survival against environmental stressors, pathogenesis, and spoilage. We also discuss methodologies for interrogating phenotypic heterogeneity in fungi. The emerging prevalence and apparent importance of fungal phenotypic heterogeneity provides a timely reminder that certain, potentially core aspects of fungal biology still remain widely under-explored

Origin of Irreversibility of Cell Cycle Start in Budding Yeast

In budding yeast, the commitment to entry into a new cell division cycle is made irreversible by positive feedback-driven expression of the G1 cyclins Cln1,2

Optimizing Optical Flow Cytometry for Cell Volume-Based Sorting and Analysis

Cell size is a defining characteristic central to cell function and ultimately to tissue architecture. The ability to sort cell subpopulations of different sizes would facilitate investigation at genomic and proteomic levels of mechanisms by which cells attain and maintain their size. Currently available cell sorters, however, cannot directly measure cell volume electronically, and it would therefore be desirable to know which of the optical measurements that can be made in such instruments provide the best estimate of volume. We investigated several different light scattering and fluorescence measurements in several different cell lines, sorting cell fractions from the high and low end of distributions, and measuring volume electronically to determine which sorting strategy yielded the best separated volume distributions. Since we found that different optical measurements were optimal for different cell lines, we suggest that following this procedure will enable other investigators to optimize their own cell sorters for volume-based separation of the cell types with which they work