Paneth cell dysfunction in radiation injury and radio-mitigation by human α-defensin 5

IntroductionThe mechanism underlying radiation-induced gut microbiota dysbiosis is undefined. This study examined the effect of radiation on the intestinal Paneth cell α-defensin expression and its impact on microbiota composition and mucosal tissue injury and evaluated the radio-mitigative effect of human α-defensin 5 (HD5).MethodsAdult mice were subjected to total body irradiation, and Paneth cell α-defensin expression was evaluated by measuring α-defensin mRNA by RT-PCR and α-defensin peptide levels by mass spectrometry. Vascular-to-luminal flux of FITC-inulin was measured to evaluate intestinal mucosal permeability and endotoxemia by measuring plasma lipopolysaccharide. HD5 was administered in a liquid diet 24 hours before or after irradiation. Gut microbiota was analyzed by 16S rRNA sequencing. Intestinal epithelial junctions were analyzed by immunofluorescence confocal microscopy and mucosal inflammatory response by cytokine expression. Systemic inflammation was evaluated by measuring plasma cytokine levels.ResultsIonizing radiation reduced the Paneth cell α-defensin expression and depleted α-defensin peptides in the intestinal lumen. α-Defensin down-regulation was associated with the time-dependent alteration of gut microbiota composition, increased gut permeability, and endotoxemia. Administration of human α-defensin 5 (HD5) in the diet 24 hours before irradiation (prophylactic) significantly blocked radiation-induced gut microbiota dysbiosis, disruption of intestinal epithelial tight junction and adherens junction, mucosal barrier dysfunction, and mucosal inflammatory response. HD5, administered 24 hours after irradiation (treatment), reversed radiation-induced microbiota dysbiosis, tight junction and adherens junction disruption, and barrier dysfunction. Furthermore, HD5 treatment also prevents and reverses radiation-induced endotoxemia and systemic inflammation.ConclusionThese data demonstrate that radiation induces Paneth cell dysfunction in the intestine, and HD5 feeding prevents and mitigates radiation-induced intestinal mucosal injury, endotoxemia, and systemic inflammation

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Rif1 Supports the Function of the CST Complex in Yeast Telomere Capping

Telomere integrity in budding yeast depends on the CST (Cdc13-Stn1-Ten1) and shelterin-like (Rap1-Rif1-Rif2) complexes, which are thought to act independently from each other. Here we show that a specific functional interaction indeed exists among components of the two complexes. In particular, unlike RIF2 deletion, the lack of Rif1 is lethal for stn1ΔC cells and causes a dramatic reduction in viability of cdc13-1 and cdc13-5 mutants. This synthetic interaction between Rif1 and the CST complex occurs independently of rif1Δ-induced alterations in telomere length. Both cdc13-1 rif1Δ and cdc13-5 rif1Δ cells display very high amounts of telomeric single-stranded DNA and DNA damage checkpoint activation, indicating that severe defects in telomere integrity cause their loss of viability. In agreement with this hypothesis, both DNA damage checkpoint activation and lethality in cdc13 rif1Δ cells are partially counteracted by the lack of the Exo1 nuclease, which is involved in telomeric single-stranded DNA generation. The functional interaction between Rif1 and the CST complex is specific, because RIF1 deletion does not enhance checkpoint activation in case of CST-independent telomere capping deficiencies, such as those caused by the absence of Yku or telomerase. Thus, these data highlight a novel role for Rif1 in assisting the essential telomere protection function of the CST complex

Alternative Strategies to Reduce Maternal Mortality in India: A Cost-Effectiveness Analysis

A cost-effectiveness study by Sue Goldie and colleagues finds that better family planning, provision of safe abortion, and improved intrapartum and emergency obstetrical care could reduce maternal mortality in India by 75% in 5 years

Quantitative Fitness Analysis Shows That NMD Proteins and Many Other Protein Complexes Suppress or Enhance Distinct Telomere Cap Defects

To better understand telomere biology in budding yeast, we have performed systematic suppressor/enhancer analyses on yeast strains containing a point mutation in the essential telomere capping gene CDC13 (cdc13-1) or containing a null mutation in the DNA damage response and telomere capping gene YKU70 (yku70Δ). We performed Quantitative Fitness Analysis (QFA) on thousands of yeast strains containing mutations affecting telomere-capping proteins in combination with a library of systematic gene deletion mutations. To perform QFA, we typically inoculate 384 separate cultures onto solid agar plates and monitor growth of each culture by photography over time. The data are fitted to a logistic population growth model; and growth parameters, such as maximum growth rate and maximum doubling potential, are deduced. QFA reveals that as many as 5% of systematic gene deletions, affecting numerous functional classes, strongly interact with telomere capping defects. We show that, while Cdc13 and Yku70 perform complementary roles in telomere capping, their genetic interaction profiles differ significantly. At least 19 different classes of functionally or physically related proteins can be identified as interacting with cdc13-1, yku70Δ, or both. Each specific genetic interaction informs the roles of individual gene products in telomere biology. One striking example is with genes of the nonsense-mediated RNA decay (NMD) pathway which, when disabled, suppress the conditional cdc13-1 mutation but enhance the null yku70Δ mutation. We show that the suppressing/enhancing role of the NMD pathway at uncapped telomeres is mediated through the levels of Stn1, an essential telomere capping protein, which interacts with Cdc13 and recruitment of telomerase to telomeres. We show that increased Stn1 levels affect growth of cells with telomere capping defects due to cdc13-1 and yku70Δ. QFA is a sensitive, high-throughput method that will also be useful to understand other aspects of microbial cell biology

Interdisciplinary-driven hypotheses on spatial associations of mixtures of industrial air pollutants with adverse birth outcomes

Background: Adverse birth outcomes (ABO) such as prematurity and small for gestational age confer a high risk of mortality and morbidity. ABO have been linked to air pollution; however, relationships with mixtures of industrial emissions are poorly understood. The exploration of relationships between ABO and mixtures is complex when hundreds of chemicals are analyzed simultaneously, requiring the use of novel approaches. Objective: We aimed to generate robust hypotheses spatially linking mixtures and the occurrence of ABO using a spatial data mining algorithm and subsequent geographical and statistical analysis. The spatial data mining approach aimed to reduce data dimensionality and efficiently identify spatial associations between multiple chemicals and ABO. Methods: We discovered co-location patterns of mixtures and ABO in Alberta, Canada (2006–2012). An ad-hoc spatial data mining algorithm allowed the extraction of primary co-location patterns of 136 chemicals released into the air by 6279 industrial facilities (National Pollutant Release Inventory), wind-patterns from 182 stations, and 333,247 singleton live births at the maternal postal code at delivery (Alberta Perinatal Health Program), from which we identified cases of preterm birth, small for gestational age, and low birth weight at term. We selected secondary patterns using a lift ratio metric from ABO and non-ABO impacted by the same mixture. The relevance of the secondary patterns was estimated using logistic models (adjusted by socioeconomic status and ABO-related maternal factors) and a geographic-based assignment of maternal exposure to the mixtures as calculated by kernel density. Results: From 136 chemicals and three ABO, spatial data mining identified 1700 primary patterns from which five secondary patterns of three-chemical mixtures, including particulate matter, methyl-ethyl-ketone, xylene, carbon monoxide, 2-butoxyethanol, and n-butyl alcohol, were subsequently analyzed. The significance of the associations (odds ratio > 1) between the five mixtures and ABO provided statistical support for a new set of hypotheses. Conclusion: This study demonstrated that, in complex research settings, spatial data mining followed by pattern selection and geographic and statistical analyses can catalyze future research on associations between air pollutant mixtures and adverse birth outcomes

Body Mass Index and Diabetes in Asia: A Cross-Sectional Pooled Analysis of 900,000 Individuals in the Asia Cohort Consortium

10.1371/journal.pone.0019930PLoS ONE66