Applying an adaptive watershed to the tissue cell quantification during T-cell migration and embryonic development

Hox proteins drive cell segregation and non-autonomous apical remodelling during hindbrain segmentation

Hox genes encode a conserved family of homeodomain transcription factors regulating development along the major body axis. During embryogenesis, Hox proteins are expressed in segment-specific patterns and control numerous different segment-specific cell fates. It has been unclear, however, whether Hox proteins drive the epithelial cell segregation mechanism that is thought to initiate the segmentation process. Here, we investigate the role of vertebrate Hox proteins during the partitioning of the developing hindbrain into lineage-restricted units called rhombomeres. Loss-of-function mutants and ectopic expression assays reveal that Hoxb4 and its paralogue Hoxd4 are necessary and sufficient for cell segregation, and for the most caudal rhombomere boundary (r6/r7). Hox4 proteins regulate Eph/ephrins and other cell-surface proteins, and can function in a non-cell-autonomous manner to induce apical cell enlargement on both sides of their expression border. Similarly, other Hox proteins expressed at more rostral rhombomere interfaces can also regulate Eph/ephrins, induce apical remodelling and drive cell segregation in ectopic expression assays. However, Krox20, a key segmentation factor expressed in odd rhombomeres (r3 and r5), can largely override Hox proteins at the level of regulation of a cell surface target, Epha4. This study suggests that most, if not all, Hox proteins share a common potential to induce cell segregation but in some contexts this is masked or modulated by other transcription factors.

Mobilized adult pituitary stem cells contribute to endocrine regeneration in response to physiological demand

Pituitary hormone deficiencies, with Growth Hormone deficiency being most frequent (1 in 3,500-10,000 births), cause significant morbidity. Regeneration of missing endocrine cells would be a significant improvement over hormone replacement therapies, which incur side effects and do not mimic physiological secretion patterns. Recent in vitro studies have identified a population of adult pituitary progenitors that express the HMG box transcription factors SOX2 and SOX9. Here, we apply cell-lineage tracing analysis to demonstrate that SOX2- and SOX9-expressing progenitors can self-renew and give rise to endocrine cells in vivo, suggesting that they are tissue stem cells. Moreover, we show that they can become mobilized and differentiate into the appropriate endocrine cell types in response to physiological stress. Our results highlight the pituitary as a model for exploring how physiological changes influence stem cell behavior and suggest that manipulation of endogenous pituitary stem cells is a potential therapeutic strategy for pituitary deficiencies.

High throughput virus plaque quantitation using a flatbed scanner

The plaque assay is a standard technique for measuring influenza virus infectivity and inhibition of virus replication. Counting plaque numbers and quantifying virus infection of cells in multiwell plates quickly, accurately and automatically remain a challenge. Visual inspection relies upon experience, is subjective, often time consuming, and has less reproducibility than automated methods. In this paper, a simple, high throughput imaging-based alternative is proposed which uses a flatbed scanner and image processing software to quantify the infected cell population and plaque formation. Quantitation results were evaluated with reference to visual counting and achieved better than 80% agreement. The method was shown to be particularly advantageous in titration of the number of plaques and infected cells when influenza viruses produce a heterogeneous population of small plaques. It was also shown to be insensitive to the densities of plaques in determination of neutralization titres and IC(50)s of drug susceptibility. In comparison to other available techniques, this approach is cost-effective, relatively accurate, and readily available.

Comparison of parameter-adapted segmentation methods for fluorescence micrographs

Interpreting images from fluorescence microscopy is often a time-consuming task with poor reproducibility. Various image processing routines that can help investigators evaluate the images are therefore useful. The critical aspect for a reliable automatic image analysis system is a robust segmentation algorithm that can perform accurate segmentation for different cell types. In this study, several image segmentation methods were therefore compared and evaluated in order to identify the most appropriate segmentation schemes that are usable with little new parameterization and robustly with different types of fluorescence-stained cells for various biological and biomedical tasks. The study investigated, compared, and enhanced four different methods for segmentation of cultured epithelial cells. The maximum-intensity linking (MIL) method, an improved MIL, a watershed method, and an improved watershed method based on morphological reconstruction were used. Three manually annotated datasets consisting of 261, 817, and 1,333 HeLa or L929 cells were used to compare the different algorithms. The comparisons and evaluations showed that the segmentation performance of methods based on the watershed transform was significantly superior to the performance of the MIL method. The results also indicate that using morphological opening by reconstruction can improve the segmentation of cells stained with a marker that exhibits the dotted surface of cells.