The microtubule-associated protein DCAMKL1 regulates osteoblast function via repression of Runx2

Osteoblasts are responsible for the formation and mineralization of the skeleton. To identify novel regulators of osteoblast differentiation, we conducted an unbiased forward genetic screen using a lentiviral-based shRNA library. This functional genomics analysis led to the identification of the microtubule-associated protein DCAMKL1 (Doublecortin-like and CAM kinase–like 1) as a novel regulator of osteogenesis. Mice with a targeted disruption of Dcamkl1 displayed elevated bone mass secondary to increased bone formation by osteoblasts. Molecular experiments demonstrated that DCAMKL1 represses osteoblast activation by antagonizing Runx2, the master transcription factor in osteoblasts. Key elements of the cleidocranial dysplasia phenotype observed in Runx2+/− mice are reversed by the introduction of a Dcamkl1-null allele. Our results establish a genetic linkage between these two proteins in vivo and demonstrate that DCAMKL1 is a physiologically relevant regulator of anabolic bone formation

Galactic Globular and Open Clusters in the Sloan Digital Sky Survey. I. Crowded Field Photometry and Cluster Fiducial Sequences in ugriz

We present photometry for globular and open cluster stars observed with the Sloan Digital Sky Survey (SDSS). In order to exploit over 100 million stellar objects with r < 22.5 mag observed by SDSS, we need to understand the characteristics of stars in the SDSS ugriz filters. While star clusters provide important calibration samples for stellar colors, the regions close to globular clusters, where the fraction of field stars is smallest, are too crowded for the standard SDSS photometric pipeline to process. To complement the SDSS imaging survey, we reduce the SDSS imaging data for crowded cluster fields using the DAOPHOT/ALLFRAME suite of programs and present photometry for 17 globular clusters and 3 open clusters in a SDSS value-added catalog. Our photometry and cluster fiducial sequences are on the native SDSS 2.5-meter ugriz photometric system, and the fiducial sequences can be directly applied to the SDSS photometry without relying upon any transformations. Model photometry for red giant branch and main-sequence stars obtained by Girardi et al. cannot be matched simultaneously to fiducial sequences; their colors differ by ~0.02-0.05 mag. Good agreement (< ~0.02 mag in colors) is found with Clem et al. empirical fiducial sequences in u'g'r'i'z' when using the transformation equations in Tucker et al.Comment: 30 pages, 25 figures. Accepted for publication in ApJS. Version with high resolution figures available at http://www.astronomy.ohio-state.edu/~deokkeun/AnJohnson.pd

Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III)-reducer Rhodoferax ferrireducens

<p>Abstract</p> <p>Background</p> <p><it>Rhodoferax ferrireducens </it>is a metabolically versatile, Fe(III)-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about <it>R. ferrireducens</it>, the complete genome sequence of this organism was further annotated and then the physiology of <it>R. ferrireducens </it>was investigated with a constraint-based, genome-scale <it>in silico </it>metabolic model and laboratory studies.</p> <p>Results</p> <p>The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why <it>R. ferrireducens </it>is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that <it>R. ferrireducens </it>is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress.</p> <p>Conclusion</p> <p>This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.</p

Overview of the Microbiome Among Nurses study (Micro-N) as an example of prospective characterization of the microbiome within cohort studies

A lack of prospective studies has been a major barrier for assessing the role of the microbiome in human health and disease on a population-wide scale. To address this significant knowledge gap, we have launched a large-scale collection targeting fecal and oral microbiome specimens from 20,000 women within the Nurses’ Health Study II cohort (the Microbiome Among Nurses study, or Micro-N). Leveraging the rich epidemiologic data that have been repeatedly collected from this cohort since 1989; the established biorepository of archived blood, urine, buccal cell, and tumor tissue specimens; the available genetic and biomarker data; the cohort’s ongoing follow-up; and the BIOM-Mass microbiome research platform, Micro-N furnishes unparalleled resources for future prospective studies to interrogate the interplay between host, environmental factors, and the microbiome in human health. These prospectively collected materials will provide much-needed evidence to infer causality in microbiome-associated outcomes, paving the way toward development of microbiota-targeted modulators, preventives, diagnostics and therapeutics. Here, we describe a generalizable, scalable and cost-effective platform used for stool and oral microbiome specimen and metadata collection in the Micro-N study as an example of how prospective studies of the microbiome may be carried out

Identification of sulfation sites of metabolites and prediction of the compounds’ biological effects

Characterizing the biological effects of metabolic transformations (or biotransformation) is one of the key steps in developing safe and effective pharmaceuticals. Sulfate conjugation, one of the major phase II biotransformations, is the focus of this study. While this biotransformation typically facilitates excretion of metabolites by making the compounds more water soluble, sulfation may also lead to bioactivation, producing carcinogenic products. The end result, excretion or bioactivation, depends on the structural features of the sulfation sites, so obtaining the structure of the sulfated metabolites is critically important. We describe herein a very simple, high-throughput procedure for using mass spectrometry to identify the structure—and thus the biological fate—of sulfated metabolites. We have chemically synthesized and analyzed libraries of compounds representing all the biologically relevant types of sulfation products, and using the mass spectral data, the structural features present in these analytes can be reliably determined, with a 97% success rate. This work represents the first example of a high-throughput analysis that can identify the structure of sulfated metabolites and predict their biological effects

Computational Micromodel for Epigenetic Mechanisms

Characterization of the epigenetic profile of humans since the initial breakthrough on the human genome project has strongly established the key role of histone modifications and DNA methylation. These dynamic elements interact to determine the normal level of expression or methylation status of the constituent genes in the genome. Recently, considerable evidence has been put forward to demonstrate that environmental stress implicitly alters epigenetic patterns causing imbalance that can lead to cancer initiation. This chain of consequences has motivated attempts to computationally model the influence of histone modification and DNA methylation in gene expression and investigate their intrinsic interdependency. In this paper, we explore the relation between DNA methylation and transcription and characterize in detail the histone modifications for specific DNA methylation levels using a stochastic approach

Urinary levels of N-nitroso compounds in relation to risk of gastric cancer: Findings from the Shanghai cohort study

Background: N-Nitroso compounds are thought to play a significant role in the development of gastric cancer. Epidemiological data, however, are sparse in examining the associations between biomarkers of exposure to N-nitroso compounds and the risk of gastric cancer. Methods: A nested case-control study within a prospective cohort of 18,244 middle-aged and older men in Shanghai, China, was conducted to examine the association between urinary level of N-nitroso compounds and risk of gastric cancer. Information on demographics, usual dietary intake, and use of alcohol and tobacco was collected through in-person interviews at enrollment. Urinary levels of nitrate, nitrite, N-nitroso-2-methylthiazolidine-4-carboxylic acid (NMTCA), N-nitrosoproline (NPRO), N-nitrososarcosine (NSAR), N-nitrosothiazolidine-4-carboxylic acid (NTCA), as well as serum H. pylori antibodies were quantified in 191 gastric cancer cases and 569 individually matched controls. Logistic regression method was used to assess the association between urinary levels of N-nitroso compounds and risk of gastric cancer. Results: Compared with controls, gastric cancer patients had overall comparable levels of urinary nitrate, nitrite, and N-nitroso compounds. Among individuals seronegative for antibodies to H. pylori, elevated levels of urinary nitrate were associated with increased risk of gastric cancer. The multivariate-adjusted odds ratios for the second and third tertiles of nitrate were 3.27 (95% confidence interval = 0.76-14.04) and 4.82 (95% confidence interval = 1.05-22.17), respectively, compared with the lowest tertile (P for trend = 0.042). There was no statistically significant association between urinary levels of nitrite or N-nitroso compounds and risk of gastric cancer. Urinary NMTCA level was significantly associated with consumption of alcohol and preserved meat and fish food items. Conclusion: The present study demonstrates that exposure to nitrate, a precursor of N-nitroso compounds, may increase the risk of gastric cancer among individuals without a history of H. pylori infection