Correction: Deep Sequencing Identifies Ethnicity-Specific Bacterial Signatures in the Oral Microbiome
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ABSTRACT:
SUBMITTER: Mason M
PROVIDER: S-EPMC4045986 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (~2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ~90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes.
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Project description:Although a considerable proportion of serum lipids loci identified in European ancestry individuals (EA) replicate in African Americans (AA), interethnic differences in the distribution of serum lipids suggest that some genetic determinants differ by ethnicity. We conducted a comprehensive evaluation of five lipid candidate genes to identify variants with ethnicity-specific effects. We sequenced ABCA1, LCAT, LPL, PON1, and SERPINE1 in 48 AA individuals with extreme serum lipid concentrations (high HDLC/low TG or low HDLC/high TG). Identified variants were genotyped in the full population-based sample of AA (n = 1694) and tested for an association with serum lipids. rs328 (LPL) and correlated variants were associated with higher HDLC and lower TG. Interestingly, a stronger effect was observed on a "European" vs. "African" genetic background at this locus. To investigate this effect, we evaluated the region among West Africans (WA). For TG, the effect size among WA was the same in AA with only African local ancestry (2-3% lower TG), while the larger association among AA with local European ancestry matched previous reports in EA (10%). For HDLC, there was no association with rs328 in AA with only African local ancestry or in WA, while the association among AA with European local ancestry was much greater than what has been observed for EA (15 vs. ∼ 5 mg/dl), suggesting an interaction with an environmental or genetic factor that differs by ethnicity. Beyond this ancestry effect, the importance of African ancestry-focused, sequence-based work was also highlighted by serum lipid associations of variants that were in higher frequency (or present only) among those of African ancestry. By beginning our study with the sequence variation present in AA individuals, investigating local ancestry effects, and seeking replication in WA, we were able to comprehensively evaluate the role of a set of candidate genes in serum lipids in AA.
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Project description:Oral bacterial microbiome Targeted loci
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Project description:Irritable bowel syndrome (IBS) is a chronic gastrointestinal disorder characterized by abdominal pain or discomfort. Previous studies have illustrated that the gut microbiota might play a critical role in IBS, but the conclusions of these studies, based on various methods, were almost impossible to compare, and reproducible microorganism signatures were still in question. To cope with this problem, previously published 16S rRNA gene sequencing data from 439 fecal samples, including 253 IBS samples and 186 control samples, were collected and processed with a uniform bioinformatic pipeline. Although we found no significant differences in community structures between IBS and healthy controls at the amplicon sequence variants (ASV) level, machine learning (ML) approaches enabled us to discriminate IBS from healthy controls at genus level. Linear discriminant analysis effect size (LEfSe) analysis was subsequently used to seek out 97 biomarkers across all studies. Then, we quantified the standardized mean difference (SMDs) for all significant genera identified by LEfSe and ML approaches. Pooled results showed that the SMDs of nine genera had statistical significance, in which the abundance of Lachnoclostridium, Dorea, Erysipelatoclostridium, Prevotella 9, and Clostridium sensu stricto 1 in IBS were higher, while the dominant abundance genera of healthy controls were Ruminococcaceae UCG-005, Holdemanella, Coprococcus 2, and Eubacterium coprostanoligenes group. In summary, based on six published studies, this study identified nine new microbiome biomarkers of IBS, which might be a basis for understanding the key gut microbes associated with IBS, and could be used as potential targets for microbiome-based diagnostics and therapeutics.
| S-EPMC8231010 | biostudies-literature
Project description:The function of each renal tubule segment depends on the genes expressed therein. High-throughput methods used for global profiling of gene expression in unique cell types have shown low sensitivity and high false positivity, thereby limiting the usefulness of these methods in transcriptomic research. However, deep sequencing of RNA species (RNA-seq) achieves highly sensitive and quantitative transcriptomic profiling by sequencing RNAs in a massive, parallel manner. Here, we used RNA-seq coupled with classic renal tubule microdissection to comprehensively profile gene expression in each of 14 renal tubule segments from the proximal tubule through the inner medullary collecting duct of rat kidneys. Polyadenylated mRNAs were captured by oligo-dT primers and processed into adapter-ligated cDNA libraries that were sequenced using an Illumina platform. Transcriptomes were identified to a median depth of 8261 genes in microdissected renal tubule samples (105 replicates in total) and glomeruli (5 replicates). Manual microdissection allowed a high degree of sample purity, which was evidenced by the observed distributions of well established cell-specific markers. The main product of this work is an extensive database of gene expression along the nephron provided as a publicly accessible webpage (https://helixweb.nih.gov/ESBL/Database/NephronRNAseq/index.html). The data also provide genome-wide maps of alternative exon usage and polyadenylation sites in the kidney. We illustrate the use of the data by profiling transcription factor expression along the renal tubule and mapping metabolic pathways.
| S-EPMC4625681 | biostudies-literature
Project description:Patients with advanced oral squamous cell carcinoma (OSCC) have heterogeneous outcomes that limit the implementation of tailored treatment options. Genetic markers for improved prognostic stratification are eagerly awaited.Herein, next-generation sequencing (NGS) was performed in 345 formalin-fixed paraffin-embedded (FFPE) samples obtained from advanced OSCC patients. Genetic mutations on the hotspot regions of 45 cancer-related genes were detected using an ultra-deep (>1000×) sequencing approach. Kaplan-Meier plots and Cox regression analyses were used to investigate the associations between the mutation status and disease-free survival (DFS).We identified 1269 non-synonymous mutations in 276 OSCC samples. TP53, PIK3CA, CDKN2A, HRAS and BRAF were the most frequently mutated genes. Mutations in 14 genes were found to predict DFS. A mutation-based signature affecting ten genes (HRAS, BRAF, FGFR3, SMAD4, KIT, PTEN, NOTCH1, AKT1, CTNNB1, and PTPN11) was devised to predict DFS. Two different resampling methods were used to validate the prognostic value of the identified gene signature. Multivariate analysis demonstrated that presence of a mutated gene signature was an independent predictor of poorer DFS (P = 0.005).Genetic variants identified by NGS technology in FFPE samples are clinically useful to predict prognosis in advanced OSCC patients.
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Project description:BackgroundThe accumulation of somatic mutations in genes and molecular pathways is a major factor in the evolution of oral squamous cell carcinoma (OSCC), which sparks studies to identify somatic mutations with clinical potentials. Recently, massively parallel sequencing technique has started to revolutionize biomedical studies, due to the rapid increase in its throughput and drop in cost. Hence sequencing of whole transcriptome (RNA-Seq) becomes a superior approach in cancer studies, which enables the detection of somatic mutations and accurate measurement of gene expression simultaneously.MethodsWe used RNA-Seq data from tumor and matched normal samples to investigate somatic mutation spectrum in OSCC.ResultsBy applying a sophisticated bioinformatic pipeline, we interrogated two tumor samples and their matched normal tissues and identified 70,472 tumor somatic mutations in protein-coding regions. We further identified 515 significantly mutated genes (SMGs) and 156 tumor-specific disruptive genes (TDGs), with six genes in both sets, including ANKRA2, GTF2H5, STOML1, NUP37, PPP1R26, and TAF1L. Pathway analysis suggested that SMGs were enriched in cell adhesion pathways, which are frequently indicated in tumor development. We also found that SMGs tend to be differentially expressed between tumors and normal tissues, implying a regulatory role of accumulation of genetic aberrations in these genes.ConclusionsOur finding of known tumor genes proves of the utility of RNA-Seq in mutation screening, and functional analysis of genes detected here would help understand the molecular mechanism of OSCC.
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Project description:In contrast to gut, the oral microbiome of MS patients has not been characterized. Deep sequencing of saliva DNA from a pair of monozygotic twins (MSF1 with relapsing remitting MS; MSF2 with clinically isolated syndrome) identified 2036 bacterial species. Relative abundances of 3 phyla were higher, and 3 lower in MSF1 versus MSF2. Species diversity was greater in MSF2, and 20 abundant species differed at least 2-fold. Pathway analysis identified 116 functional hierarchies differing 50% or more. Although limited to one pair of twins, our data suggests that oral microbiome analysis may be useful for diagnosis or monitoring therapeutic efficacy.
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Project description:Here we present the case of adult medulloblastoma with minimal chromosomal rearrangements but Shh expression profile and IDH1 mutation. Data presented here are NanoString analyses of two biopsies of adult patient with a medulloblastoma which was classified as a Shh subtype Analyses were performed on 2 archival specimens of medulloblastoma, WHO Grade IV, seen at the Department of Pathology, Massachusetts General Hospital in 2007.
| S-ECPF-GEOD-43123 | biostudies-other