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

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

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

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

Oscillatory Dynamics of Cell Cycle Proteins in Single Yeast Cells Analyzed by Imaging Cytometry

Progression through the cell division cycle is orchestrated by a complex network of interacting genes and proteins. Some of these proteins are known to fluctuate periodically during the cell cycle, but a systematic study of the fluctuations of a broad sample of cell-cycle proteins has not been made until now. Using time-lapse fluorescence microscopy, we profiled 16 strains of budding yeast, each containing GFP fused to a single gene involved in cell cycle regulation. The dynamics of protein abundance and localization were characterized by extracting the amplitude, period, and other indicators from a series of images. Oscillations of protein abundance could clearly be identified for Cdc15, Clb2, Cln1, Cln2, Mcm1, Net1, Sic1, and Whi5. The period of oscillation of the fluorescently tagged proteins is generally in good agreement with the inter-bud time. The very strong oscillations of Net1 and Mcm1 expression are remarkable since little is known about the temporal expression of these genes. By collecting data from large samples of single cells, we quantified some aspects of cell-to-cell variability due presumably to intrinsic and extrinsic noise affecting the cell cycle

Daughter-Specific Transcription Factors Regulate Cell Size Control in Budding Yeast

The asymmetric localization of cell fate determinants results in asymmetric cell cycle control in budding yeast