Systems Mapping for Hematopoietic Progenitor Cell Heterogeneity

Cells with the same genotype growing under the same conditions can show different phenotypes, which is known as “population heterogeneity”. The heterogeneity of hematopoietic progenitor cells has an effect on their differentiation potential and lineage choices. However, the genetic mechanisms governing population heterogeneity remain unclear. Here, we present a statistical model for mapping the quantitative trait locus (QTL) that affects hematopoietic cell heterogeneity. This strategy, termed systems mapping, integrates a system of differential equations into the framework for systems mapping, allowing hypotheses regarding the interplay between genetic actions and cell heterogeneity to be tested. A simulation approach based on cell heterogeneity dynamics has been designed to test the statistical properties of the model. This model not only considers the traditional QTLs, but also indicates the methylated QTLs that can illustrate non-genetic individual differences. It has significant implications for probing the molecular, genetic and epigenetic mechanisms of hematopoietic progenitor cell heterogeneity.     

DNA deposition on carbon electrodes under controlled dc potentials

The native calf-thymus DNA molecule fully dispersed in solution was deposited onto highly oriented pyrolytic graphite, carbon fiber column and disk electrodes under controlled dc potentials. X-ray photoelectron spectroscopy, atomic force microscopy and electrochemical investigations indicated that network structures of DNA could be formed on various carbon electrode surfaces resulting in significant surface enlargement. The conformation, conductivity and stability of the deposited DNA layer largely depended on the concentration of the DNA deposition solution, the applied dc potential and the mode of electric field. The optimal condition for deposition of the DNA on carbon fiber disk electrode was determined as a deposition potential of 1.8 +/- 0.3 V versus 50 mM NaCl-Ag/AgCl and a deposition DNA solution of 0.1 mg ml(-1). Under this condition, the DNA was covalently bonded on the electrode surface forming a three-dimensional modified layer, generating a 500-fold enlarged effective electrode surface area and similarly enlarged current sensitivity for redox species, such as Co(phen)3(3+). A possible mechanism for the formation of DNA networks is proposed.     

Demographic trade-offs determine species abundance and diversity

Aims Much recent theory has focused on the role of neutral processes in assembling communities, but the basic assumption that all species are demographically identical has found little empirical support. Here, we show that the framework of the current neutral theory can easily be generalized to incorporate species differences so long as fitness equivalence among individuals is maintained through trade-offs between birth and death.Methods Our theory development is based on a careful reformulation of the Moran model of metacommunity dynamics in terms of a non-linear one-step stochastic process, which is described by a master equation.Important findings We demonstrate how fitness equalization through demographic trade-offs can generate significant macroecological diversity patterns, leading to a very different interpretation of the relation between Fisher's α and Hubbell's fundamental biodiversity number. Our model shows that equal fitness (not equal demographics) significantly promotes species diversity through strong selective sieving of community membership against high-mortality species, resulting in a positive association between species abundance and per capita death rate. An important implication of demographic trade-off is that it can partly explain the excessively high speciation rates predicted by the neutral theory of the stronger symmetry. Fitness equalization through demographic trade-offs generalizes neutral theory by considering heterospecific demographic difference, thus representing a significant step toward integrating the neutral and niche paradigms of biodiversity.     

ABCG2: A potential marker of stem cells and novel target in stem cell and cancer therapy

ABCG2 is a member of the ATP binding cassette (ABC) transporters, which can pump a wide variety of endogenous and exogenous compounds out of cells. Widely expressed in stem cells, ABCG2 is also found to confer the side population phenotype and is recognized as a universal marker of stem cells. Although the precise physiological role of ABCG2 in stem cells is still unclear, existing data strongly suggest that ABCG2 plays an important role in promoting stem cell proliferation and the maintenance of the stem cell phenotype. In addition, ABCG2 is also found to be expressed in a number of cancer cells and appears to be a marker of cancer stem cells. Moreover, ABCG2 expression in tumors may contribute to their formation and progression. Thus, ABCG2 has potential applications in stem cell and tumor therapy.     

Lipids,lipid metabolism and Kaposi’s sarcoma-associated herpesvirus pathogenesis

Lipids are essential for mammalian cells to maintain many physiological functions. Emerging evidence has shown that cancer cells can develop specific alterations in lipid biosynthesis and metabolism to facilitate their survival and various malignant behaviors. To date, the precise role of cellular lipids and lipid metabolism in viral oncogenesis is still largely unclear with only a handful of literature covering this topic to implicate lipid metabolism in oncogenic virus associated pathogenesis. In this review, we focus on the role of lipid biosynthesis and metabolism in the pathogenesis of the Kaposi’s sarcoma-associated herpesvirus, a common causative factor for cancers arising in the immunocompromised settings.

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Comparative transcriptional profiling and evolutionary analysis of the GRAM domain family in eukaryotes

The GRAM domain was found in glucosyltransferases, myotubularins and other membrane-associated proteins. So far, functions for majority of these proteins are yet to be uncovered. In order to address the evolutionary and functional significance of this family members, we have performed a comprehensive investigation on their genome-wide identification, phylogenetic relationship and expression divergence in five different organisms representing monocot/dicot plants, vertebrate/invertebrate animals and yeast, namely, Oryza sativa, Arabidopsis thaliana, Mus musculus, Drosophila melanogaster and Saccharomyces cerevisiae, respectively. We have identified 65 members of GRAM domain family from these organisms. Our data revealed that this family was an ancient group and various organisms had evolved into different family sizes. Large-scale genome duplication and divergence in both expression patterns and functions were significantly contributed to the expansion and retention of this family. Mouse and Drosophila members showed higher divergences in their proteins as indicated by higher Ka/Ks ratios and possessed multiple domains in various combinations. However, in plants, their protein functions were possibly retained with a relatively low divergence as signified by lower Ka/Ks ratios and only one additional domain was combined during evolution. On the other hand, this family in all five organisms exhibited high divergence in their expression patterns both at tissue level and under various biotic and abiotic stresses. These highly divergent expression patterns unraveled the complexity of functions of GRAM domain family. Each member may play specialized roles in a specific tissue or stress condition and may function as regulators of environmental and hormonal signaling.     

Atrial fibrillation is not uncommon among patients with ischemic stroke and transient ischemic stroke in China

Background

Atrial fibrillation (AF) is reported to be a less frequent cause of ischemic stroke in China than in Europe and North America, but it is not clear whether this is due to underestimation. Our aim was to define the true frequency of AF-associated stroke, to determine the yield of 6-day Holter ECG to detect AF in Chinese stroke patients, and to elucidate predictors of newly detected AF.

Methods

Patients with acute ischemic stroke or transient ischemic attack (TIA) were enrolled in a prospective, multicenter cohort study of 6-day Holter monitoring within 7 days after stroke onset at 20 sites in China between 2013 and 2015. Independent predictors of newly-detected AF were determined by multivariate analysis.

Results

Among 1511 patients with ischemic stroke and TIA (mean age 63 years, 33.1% women), 305 (20.2%) had either previously known (196, 13.0%) or AF newly-detected by electrocardiography (53, 3.5%) or by 6-day Holter monitoring (56/1262, 4.4%). A history of heart failure (OR?=?4.70, 95%CI, 1.64–13.5), advanced age (OR?=?1.06, 95%CI, 1.04–1.09), NIHSS at admission (OR?=?1.06, 95%CI, 1.02–1.10), blood high density lipoprotein (HDL) (OR?=?1.52, 95%CI, 1.09–2.13), together with blood triglycerides (OR?=?0.64, 95%CI, 0.45–0.91) were independently associated with newly-detected AF.

Conclusions

Contrary to previous reports, AF-associated stroke is frequent (20%) in China if systemically sought. Prolonged noninvasive cardiac rhythm monitoring importantly increases AF detection in patients with recent ischemic stroke and TIA in China. Advanced age, history of heart failure, and higher admission NIHSS and higher level of HDL were independent indicators of newly-detected AF.

Trial registration

NCT02156765 (June 5, 2014).

     

GeneTrack--a genomic data processing and visualization framework

MOTIVATION: High-throughput 'ChIP-chip' and 'ChIP-seq' methodologies generate sufficiently large data sets that analysis poses significant informatics challenges, particularly for research groups with modest computational support. To address this challenge, we devised a software platform for storing, analyzing and visualizing high resolution genome-wide binding data. GeneTrack automates several steps of a typical data processing pipeline, including smoothing and peak detection, and facilitates dissemination of the results via the web. Our software is freely available via the Google Project Hosting environment at http://genetrack.googlecode.com