Using omics approaches to understand pulmonary diseases.
Ontology highlight
ABSTRACT:
SUBMITTER: Kan M
PROVIDER: S-EPMC5543452 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called "omics," are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov-Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species.
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Project description:The microbiome in fermentation has direct impacts on the quality of fermented foods and is of great scientific and commercial interest. Despite considerable effort to explain the microbial metabolism associated with food fermentation, the role of the microbiome in pu-erh tea fermentation remains unknown. Here, we applied integrated meta-omics approaches to characterize the microbiome in two repeated fermentations of pu-erh tea. Metabarcoding analysis of bacterial 16S rRNA genes showed a decrease in the proportion of Proteobacteria and an increase in the abundance of Firmicutes during fermentation. Metabarcoding analysis of fungal internal transcribed spacer (ITS) sequence demonstrated that Rasamsonia, Thermomyces, and Aspergillus were dominant at the intermediate stage, whereas Aspergillus was dominant at other stages in fermentation. Metaproteomics analysis assigned primary microbial metabolic activity to metabolism and identified microbial carbohydrate-active enzymes involved in the degradation of polysaccharides including cellulose, xylan, xyloglucan, pectin, starch, lignin, galactomannan, and chitin. Metabolomics and high-performance liquid chromatography analysis revealed that levels of phenolic compounds, including gallates, decreased whereas contents of gallic acid and ellagic acid significantly increased after fermentation (P?<?0.05). The changes in levels of gallates and gallic acid were associated with the hydrolysis of tannase. Glycoside hydrolases, phenol 2-monooxygenase, salicylaldehyde dehydrogenase, salicylate 1-monooxygenase, catechol O-methyltransferase, catechol dioxygenase, and quercetin 2,3-dioxygenases were hypothesized to be related to oxidation, conversion, or degradation of phenolic compounds. We demonstrated microbiota in fermentation and their function in the production of enzymes related to the degradation of polysaccharides, and metabolism of phenolic compounds, resulting in changes in metabolite contents and the quality of pu-erh tea.IMPORTANCE Fermented foods play important roles in diets worldwide and account for approximately one-third of all foods and beverages consumed. To date, traditional fermentation has used spontaneous fermentation. The microbiome in fermentation has direct impacts on the quality and safety of fermented foods and contributes to the preservation of traditional methods. Here, we used an integrated meta-omics approach to study the microbiome in the fermentation of pu-erh tea, which is a well-known Chinese fermented food with a special flavor and healthful benefits. This study advanced the knowledge of microbiota, metabolites, and enzymes in the fermentation of pu-erh tea. These novel insights shed light onto the complex microbiome in pu-erh fermentation and highlight the power of integrated meta-omics approaches in understanding the microbiome in food fermentation ecosystems.
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Project description:Potato early blight (PEB), a foliar disease of potato during the growing period, caused by Alternaria sp., is common in major potato-producing areas worldwide. Effective agents to control this disease or completely resistant potato varieties are absent. Large-scale use of fungicides is limited due to possibility of increase in pathogen resistance and the requirements of ecological agriculture. In this study, we focused on the composition and infection characteristics of early blight pathogens in Yunnan Province and screened candidate pathogenesis-related pathways and genes. We isolated 85 strains of Alternaria sp. fungi from typical early blight spots in three potato-growing regions in Yunnan Province from 2018 to 2022, and identified 35 strains of Alternaria solani and 50 strains of Alternaria alternata by morphological characterization and ITS sequence comparison, which were identified as the main and conditional pathogens causing early blight in potato, respectively. Scanning electron microscope analysis confirmed only A. solani producing appressorium at 4 h after inoculation successfully infected the leaf cells. Via genome assembly and annotation, combine transcriptome and proteomic analysis, the following pathogenicity-related unit, transcription factors and metabolic pathway were identified: (1) cell wall-degrading enzymes, such as pectinase, keratinase, and cellulase; (2) genes and pathways related to conidia germination and pathogenicity, such as ubiquitination and peroxisomes; and (3) transcription factors, such as Zn-clus, C2H2, bZIP, and bHLH. These elements were responsible for PEB epidemic in Yunnan.
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Project description:Purpose of reviewNeurodegenerative diseases, neuropsychiatric disorders, and related traits have highly complex etiologies but are also highly heritable and identifying the causal genes and biological pathways underlying these traits may advance the development of treatments and preventive strategies. While many genome-wide association studies (GWAS) have successfully identified variants contributing to polygenic neurodegenerative and neuropsychiatric phenotypes including Alzheimer's disease (AD), schizophrenia (SCZ), and bipolar disorder (BPD) amongst others, interpreting the biological roles of significantly-associated variants in the genetic architecture of these traits remains a significant challenge. Here we review several 'omics' approaches which attempt to bridge the gap from associated genetic variants to phenotype by helping define the functional roles of GWAS loci in the development of neuropsychiatric disorders and traits.Recent findingsSeveral common 'omics' approaches have been applied to examine neuropsychiatric traits, such as nearest-gene mapping, trans-ethnic fine mapping, annotation enrichment analysis, transcriptomic analysis, and pathway analysis, and each of these approaches has strengths and limitations in providing insight into biological mechanisms. One popular emerging method is the examination of tissue-specific genetically-regulated gene expression (GReX), which aggregates the genetic variants' effects at the gene-level. Furthermore, proteomic, metabolomic, and microbiomic studies and phenome-wide association studies will further enhance our understanding of neuropsychiatric traits.SummaryGWAS has been applied to neuropsychiatric traits for a decade, but our understanding about the biological function of identified variants remains limited. Today, technological advancements have created analytical approaches for integrating transcriptomics, metabolomics, proteomics, pharmacology and toxicology as tools for understanding the functional roles of genetics variants. These data, as well as the broader clinical information provided by electronic health records, can provide additional insight and complement genomic analyses.
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Project description:The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). We will obtain diseased and non-diseased cartilage as well as other disease-relevant tissue following TJR, coupled with a blood sample. We will generate genotype data and will characterise the pairs of diseased and non-diseased tissue samples in terms of methylation, transcription (RNASeq) and expression (quantitative proteomics). We will apply integrative approaches to combine information across the –omics levels to characterise genes, pathways, and networks that underlie osteoarthritis progression.
This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute please see http://www.sanger.ac.uk/datasharing/
| EGAS00001002322 | EGA
Project description:The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). We will obtain diseased and non-diseased cartilage as well as other disease-relevant tissue following TJR, coupled with a blood sample. We will generate genotype data and will characterise the pairs of diseased and non-diseased tissue samples in terms of methylation, transcription (RNASeq) and expression (quantitative proteomics). We will apply integrative approaches to combine information across the –omics levels to characterise genes, pathways, and networks that underlie osteoarthritis progression.
This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
| EGAS00001002255 | EGA
Project description:BackgroundSublingual allergen-specific immunotherapy (SLIT) intervention improves the control of grass pollen allergy by maintaining allergen tolerance after cessation. Despite its widespread use, little is known about systemic effects and kinetics associated to SLIT, as well as the influence of the patient sensitization phenotype (Mono- or Poly-sensitized). In this quest, omics sciences could help to gain new insights to understand SLIT effects.Methods47 grass-pollen-allergic patients were enrolled in a double-blind, placebo-controlled, multicenter trial using GRAZAX® during 2 years. Immunological assays (sIgE, sIgG4, and ISAC) were carried out to 31 patients who finished the trial. Additionally, serum and PBMCs samples were analyzed by metabolomics and transcriptomics, respectively. Based on their sensitization level, 22 patients were allocated in Mono- or Poly-sensitized groups, excluding patients allergic to epithelia. Individuals were compared based on their treatment (Active/Placebo) and sensitization level (Mono/Poly).ResultsKinetics of serological changes agreed with those previously described. At two years of SLIT, there are scarce systemic changes that could be associated to improvement in systemic inflammation. Poly-sensitized patients presented a higher inflammation at inclusion, while Mono-sensitized patients presented a reduced activity of mast cells and phagocytes as an effect of the treatment.ConclusionsThe most relevant systemic change detected after two years of SLIT was the desensitization of effector cells, which was only detected in Mono-sensitized patients. This change may be related to the clinical improvement, as previously reported, and, together with the other results, may explain why clinical effect is lost if SLIT is discontinued at this point.
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Project description:Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal-around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients.
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