The Peripheral Blood Transcriptome Identifies the Presence and Extent of Disease in Idiopathic Pulmonary Fibrosis

<div><h3>Rationale</h3><p>Peripheral blood biomarkers are needed to identify and determine the extent of idiopathic pulmonary fibrosis (IPF). Current physiologic and radiographic prognostic indicators diagnose IPF too late in the course of disease. We hypothesize that peripheral blood biomarkers will identify disease in its early stages, and facilitate monitoring for disease progression.</p> <h3>Methods</h3><p>Gene expression profiles of peripheral blood RNA from 130 IPF patients were collected on Agilent microarrays. Significance analysis of microarrays (SAM) with a false discovery rate (FDR) of 1% was utilized to identify genes that were differentially-expressed in samples categorized based on percent predicted D_LCO and FVC.</p> <h3>Main Measurements and Results</h3><p>At 1% FDR, 1428 genes were differentially-expressed in mild IPF (D_LCO >65%) compared to controls and 2790 transcripts were differentially- expressed in severe IPF (D_LCO >35%) compared to controls. When categorized by percent predicted D_LCO, SAM demonstrated 13 differentially-expressed transcripts between mild and severe IPF (< 5% FDR). These include CAMP, CEACAM6, CTSG, DEFA3 and A4, OLFM4, HLTF, PACSIN1, GABBR1, IGHM, and 3 unknown genes. Principal component analysis (PCA) was performed to determine outliers based on severity of disease, and demonstrated 1 mild case to be clinically misclassified as a severe case of IPF. No differentially-expressed transcripts were identified between mild and severe IPF when categorized by percent predicted FVC.</p> <h3>Conclusions</h3><p>These results demonstrate that the peripheral blood transcriptome has the potential to distinguish normal individuals from patients with IPF, as well as extent of disease when samples were classified by percent predicted D_LCO, but not FVC.</p> </div

Stat1 Phosphorylation Determines Ras Oncogenicity by Regulating p27Kip1

Inactivation of p27Kip1 is implicated in tumorigenesis and has both prognostic and treatment-predictive values for many types of human cancer. The transcription factor Stat1 is essential for innate immunity and tumor immunosurveillance through its ability to act downstream of interferons. Herein, we demonstrate that Stat1 functions as a suppressor of Ras transformation independently of an interferon response. Inhibition of Ras transformation and tumorigenesis requires the phosphorylation of Stat1 at tyrosine 701 but is independent of Stat1 phosphorylation at serine 727. Stat1 induces p27Kip1 expression in Ras transformed cells at the transcriptional level through mechanisms that depend on Stat1 phosphorylation at tyrosine 701 and activation of Stat3. The tumor suppressor properties of Stat1 in Ras transformation are reversed by the inactivation of p27Kip1. Our work reveals a novel functional link between Stat1 and p27Kip1, which act in coordination to suppress the oncogenic properties of activated Ras. It also supports the notion that evaluation of Stat1 phosphorylation in human tumors may prove a reliable prognostic factor for patient outcome and a predictor of treatment response to anticancer therapies aimed at activating Stat1 and its downstream effectors

Early life child micronutrient status, maternal reasoning, and a nurturing household environment have persistent influences on child cognitive development at age 5 years: Results from MAL-ED

Background: Child cognitive development is influenced by early-life insults and protective factors. To what extent these factors have a long-term legacy on child development and hence fulfillment of cognitive potential is unknown. Objective: The aim of this study was to examine the relation between early-life factors (birth to 2 y) and cognitive development at 5 y. Methods: Observational follow-up visits were made of children at 5 y, previously enrolled in the community-based MAL-ED longitudinal cohort. The burden of enteropathogens, prevalence of illness, complementary diet intake, micronutrient status, and household and maternal factors from birth to 2 y were extensively measured and their relation with the Wechsler Preschool Primary Scales of Intelligence at 5 y was examined through use of linear regression. Results: Cognitive T-scores from 813 of 1198 (68%) children were examined and 5 variables had significant associations in multivariable models: mean child plasma transferrin receptor concentration (β: −1.81, 95% CI: −2.75, −0.86), number of years of maternal education (β: 0.27, 95% CI: 0.08, 0.45), maternal cognitive reasoning score (β: 0.09, 95% CI: 0.03, 0.15), household assets score (β: 0.64, 95% CI: 0.24, 1.04), and HOME child cleanliness factor (β: 0.60, 95% CI: 0.05, 1.15). In multivariable models, the mean rate of enteropathogen detections, burden of illness, and complementary food intakes between birth and 2 y were not significantly related to 5-y cognition. Conclusions: A nurturing home context in terms of a healthy/clean environment and household wealth, provision of adequate micronutrients, maternal education, and cognitive reasoning have a strong and persistent influence on child cognitive development. Efforts addressing aspects of poverty around micronutrient status, nurturing caregiving, and enabling home environments are likely to have lasting positive impacts on child cognitive development.publishedVersio

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Contribution of Microbe-Mediated Processes in Nitrogen Cycle to Attain Environmental Equilibrium

Nitrogen (N), the most important element, is required by all living organisms for the synthesis of complex organic molecules like amino acids, proteins, lipids etc. Nitrogen cycle is considered to be the most complex yet arguably important cycle next to carbon cycle. Nitrogen cycle includes oxic and anoxic reactions like organic N mineralization, ammonia assimilation, nitrification denitrification, anaerobic ammonium oxidation (anammox), dissimilatory nitrate reduction to ammonium (DNRA), comammox, codenitrification etc. Nitrogen cycling is one of the most crucial processes required for the recycling of essential chemical requirements on the planet. Soil microorganisms not only improve N-cycle balance but also pave the way for sustainable agricultural practices, leading to improved soil properties and crop productivity as most plants are opportunistic in the uptake of soluble or available forms of N from soil. Microbial N transformations are influenced by plants to improve their nutrition and vice versa. Diverse microorganisms, versatile metabolic activities, and varied biotic and abiotic conditions may result in the shift in the equilibrium state of different N-cycling processes. This chapter is an overview of the mechanisms and genes involved in the diverse microorganisms associated in the operation of nitrogen cycle and the roles of such microorganisms in different agroecosystems