Respiratory viral infection alters the gut microbiota by inducing inappetence

ABSTRACT Respiratory viral infections are extremely common, but their impacts on the composition and function of the gut microbiota are poorly understood. We previously observed a significant change in the gut microbiota after viral lung infection. Here, we show that weight loss during respiratory syncytial virus (RSV) or influenza virus infection was due to decreased food consumption, and that the fasting of mice altered gut microbiota composition independently of infection. While the acute phase tumor necrosis factor alpha (TNF-α) response drove early weight loss and inappetence during RSV infection, this was not sufficient to induce changes in the gut microbiota. However, the depletion of CD8+ cells increased food intake and prevented weight loss, resulting in a reversal of the gut microbiota changes normally observed during RSV infection. Viral infection also led to changes in the fecal gut metabolome, with a significant shift in lipid metabolism. Sphingolipids, polyunsaturated fatty acids (PUFAs), and the short-chain fatty acid (SCFA) valerate were all increased in abundance in the fecal metabolome following RSV infection. Whether this and the impact of infection-induced anorexia on the gut microbiota are part of a protective anti-inflammatory response during respiratory viral infections remains to be determined. IMPORTANCE The gut microbiota has an important role in health and disease: gut bacteria can generate metabolites that alter the function of immune cells systemically. Understanding the factors that can lead to changes in the gut microbiome may help to inform therapeutic interventions. This is the first study to systematically dissect the pathway of events from viral lung infection to changes in gut microbiota. We show that the cellular immune response to viral lung infection induces inappetence, which in turn alters the gut microbiome and metabolome. Strikingly, there was an increase in lipids that have been associated with the resolution of disease. This opens up new paths of investigation: first, what is the (presumably secreted) factor made by the T cells that can induce inappetence? Second, is inappetence an adaptation that accelerates recovery from infection, and if so, does the microbiome play a role in this

Using eQTL weights to improve power for genome-wide association studies: a genetic study of childhood asthma

Increasing evidence suggests that single nucleotide polymorphisms (SNPs) associated with complex traits are more likely to be expression quantitative trait loci (eQTLs). Incorporating eQTL information hence has potential to increase power of genome-wide association studies (GWAS). In this paper, we propose using eQTL weights as prior information in SNP based association tests to improve test power while maintaining control of the family-wise error rate (FWER) or the false discovery rate (FDR). We apply the proposed methods to the analysis of a GWAS for childhood asthma consisting of 1296 unrelated individuals with German ancestry. The results confirm that eQTLs are enriched for previously reported asthma SNPs. We also find that some SNPs are insignificant using procedures without eQTL weighting, but become significant using eQTL-weighted Bonferroni or Benjamini–Hochberg procedures, while controlling the same FWER or FDR level. Some of these SNPs have been reported by independent studies in recent literature. The results suggest that the eQTL-weighted procedures provide a promising approach for improving power of GWAS. We also report the results of our methods applied to the large-scale European GABRIEL consortium data

Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.

BACKGROUND: The study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents. RESULTS: In this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR-based 16S rRNA gene surveys and shotgun metagenomics. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination. CONCLUSIONS: These results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. Concurrent sequencing of negative control samples is strongly advised

A Polymorphism Affecting MYB Binding within the Promoter of the PDCD4 Gene is Associated with Severe Asthma in Children

A previous genome-wide association study in asthma revealed putative associations that merit further investigation. In this study, the genome-wide significant associations of SNPs at the 5% false discovery rate were examined in independent groups of severe asthmatics. The panel consisted of 397 severe asthmatic adults, 116 severe asthmatic children, and a collection of 207 family-trios with an asthmatic proband. Three SNPs in the PDCD4 gene (rs6585018:G>A, rs1322997:C>A, and rs34104444:G>A) were significantly associated with severe childhood asthma (P values: 0.003, 0.002, 0.004) and total immunoglobulin E (IgE) levels (P values: 0.034, 0.041, 0.052). In an independent group of 234 asthmatic children and 652 controls, PDCD4 SNPs rs1407696:T>G and rs11195360:T>C were associated with total IgE levels (P values: 0.006, 0.014). In silico analysis of PDCD4 locus showed that rs6585018:G>A had the potential to affect MYB transcription factor binding, shown to act as a PDCD4-transcription inducer. Electromobility shift assays and reporter assays revealed that rs6585018:G>A alters MYB binding thereby influencing the expression of PDCD4. SNPs within MYB itself confer susceptibility to eosinophilia and asthma. Our association between a variant MYB binding site in PDCD4 and the severest form of childhood asthma therefore suggests that PDCD4 is a novel molecule of importance to asthmatic inflammatory responses

Metal worker’s lung: spatial association with Mycobacterium avium

Background Outbreaks of hypersensitivity pneumonitis (HP) are not uncommon in workplaces where metal working fluid (MWF) is used to facilitate metal turning. Inhalation of microbe-contaminated MWF has been assumed to be the cause, but previous investigations have failed to establish a spatial relationship between a contaminated source and an outbreak. Objectives After an outbreak of five cases of HP in a UK factory, we carried out blinded, molecular-based microbiological investigation of MWF samples in order to identify potential links between specific microbial taxa and machines in the outbreak zone. Methods Custom-quantitative PCR assays, microscopy and phylogenetic analyses were performed on blinded MWF samples to quantify microbial burden and identify potential aetiological agents of HP in metal workers. Measurements and main results MWF from machines fed by a central sump, but not those with an isolated supply, was contaminated by mycobacteria. The factory sump and a single linked machine at the centre of the outbreak zone, known to be the workstation of the index cases, had very high levels of detectable organisms. Phylogenetic placement of mycobacterial taxonomic marker genes generated from these samples indicated that the contaminating organisms were closely related to Mycobacterium avium. Conclusions We describe, for the first time, a close spatial relationship between the abundance of a mycobacterium-like organism, most probably M. avium, and a localised outbreak of MWF-associated HP. The further development of sequence-based analytic techniques should assist in the prevention of this important occupational disease

Imputation of KIR Types from SNP Variation Data.

Large population studies of immune system genes are essential for characterizing their role in diseases, including autoimmune conditions. Of key interest are a group of genes encoding the killer cell immunoglobulin-like receptors (KIRs), which have known and hypothesized roles in autoimmune diseases, resistance to viruses, reproductive conditions, and cancer. These genes are highly polymorphic, which makes typing expensive and time consuming. Consequently, despite their importance, KIRs have been little studied in large cohorts. Statistical imputation methods developed for other complex loci (e.g., human leukocyte antigen [HLA]) on the basis of SNP data provide an inexpensive high-throughput alternative to direct laboratory typing of these loci and have enabled important findings and insights for many diseases. We present KIR∗IMP, a method for imputation of KIR copy number. We show that KIR∗IMP is highly accurate and thus allows the study of KIRs in large cohorts and enables detailed investigation of the role of KIRs in human disease.This work was supported by the Australian National Health and Medical Research Council (NHMRC), Career Development Fellowship ID 1053756 (S.L.); by a Victorian Life Sciences Computation Initiative (VLSCI) grant number VR0240 on its Peak Computing Facility at the University of Melbourne, an initiative of the Victorian Government, Australia (S.L.); by the UK Multiple Sclerosis Society, grant 894/08 (S.S.); and by the Wellcome Trust and the MRC with partial funding from the National Institute of Health Cambridge Biomedical Research Centre (J.T., J.A.T.). Research at the Murdoch Childrens Research Institute was supported by the Victorian Government's Operational Infrastructure Support Program.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ajhg.2015.09.00

Predicting DNA methylation level across human tissues

Differences in methylation across tissues are critical to cell differentiation and are key to understanding the role of epigenetics in complex diseases. In this investigation, we found that locus-specific methylation differences between tissues are highly consistent across individuals. We developed a novel statistical model to predict locus-specific methylation in target tissue based on methylation in surrogate tissue. The method was evaluated in publicly available data and in two studies using the latest IlluminaBeadChips: a childhood asthma study with methylation measured in both peripheral blood leukocytes (PBL) and lymphoblastoid cell lines; and a study of postoperative atrial fibrillation with methylation in PBL, atrium and artery. We found that our method can greatly improve accuracy of cross-tissue prediction at CpG sites that are variable in the target tissue [R2 increases from 0.38 (original R2 between tissues) to 0.89 for PBL-to-artery prediction; from 0.39 to 0.95 for PBL-to-atrium; and from 0.81 to 0.98 for lymphoblastoid cell line-to-PBL based on cross-validation, and confirmed using cross-study prediction]. An extended model with multiple CpGs further improved performance. Our results suggest that large-scale epidemiology studies using easy-to-access surrogate tissues (e.g. blood) could be recalibrated to improve understanding of epigenetics in hard-to-access tissues (e.g. atrium) and might enable non-invasive disease screening using epigenetic profiles

Genome-wide interaction study of early-life smoking exposure on time-to-asthma onset in childhood

Background: Asthma, a heterogeneous disease with variable age of onset, results from the interplay between genetic and environmental factors. Early-life tobacco smoke (ELTS) exposure is a major asthma risk factor. Only a few genetic loci have been reported to interact with ELTS exposure in asthma. Objective: Our aim was to identify new loci interacting with ELTS exposure on time-to-asthma onset (TAO) in childhood.Methods: We conducted genome-wide interaction analyses of ELTS exposure on time-to-asthma onset in childhood in five European-ancestry studies (totaling 8,273 subjects) using Cox proportional-hazard model. The results of all five genome-wide analyses were meta-analyzed.Results: The 13q21 locus showed genome-wide significant interaction with ELTS exposure (P=4.3x10-8 for rs7334050 within KLHL1 with consistent results across the five studies). Suggestive interactions (P<5x10-6) were found at three other loci: 20p12 (rs13037508 within MACROD2; P=4.9x10-7), 14q22 (rs7493885 near NIN; P=2.9x10-6) and 2p22 (rs232542 near CYP1B1; P=4.1x10-6). Functional annotations and the literature showed that the lead SNPs at these four loci influence DNA methylation in the blood and are located nearby CpG sites reported to be associated with exposure to tobacco smoke components, which strongly support our findings.Conclusion and Clinical Relevance: We identified novel candidate genes interacting with ELTS exposure on time-to-asthma onset in childhood. These genes have plausible biological relevance related to tobacco smoke exposure. Further epigenetic and functional studies are needed to confirm these findings and to shed light on the underlying mechanisms