We introduce a novel methodology for differential abundance analysis in sparse high-throughput marker gene survey data. Our approach, implemented in the metagenomeSeq Bioconductor package, relies on a novel normalization technique and a statistical model that accounts for undersampling: a common feature of large-scale marker gene studies. We show, using simulated data and several published microbiota datasets, that metagenomeSeq outperforms the tools currently used in this field.

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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A signi®cant portion of gastric cancers exhibit defective DNA mismatch repair, manifested as microsatellite instability (MSI). High-frequency MSI (MSI-H) is associated with hypermethylation of the human mut-L homologue 1 (hMLH1) mismatch repair gene promoter and diminished hMLH1 expression in advanced gastric cancers. However, the relationship between MSI and hMLH1 hypermethylation has not been studied in early gastric neoplasms. We therefore investigated hMLH1 hypermethylation, hMLH1 expression and MSI in a group of early gastric cancers and gastric adenomas. Sixty-four early gastric neoplasms were evaluated, comprising 28 adenomas, 18 mucosal carcinomas, and 18 carcinomas with super®cial submucosal invasion but clear margins. MSI was evaluated using multiplex uorescent PCR to amplify loci D2S123, D5S346, D17S250, BAT 25 and BAT 26. Methylation-speci®c PCR was performed to determine the methylation status of hMLH1. In two hypermethylated MSI-H cancers, hMLH1 protein expression was also evaluated by immunohistochemistry. Six of sixty-four early gastric lesions were MSI-H, comprising 1 adenoma, 4 mucosal carcinomas, and 1 carcinoma with super®cial submucosal invasion. Two lesions (one adenoma and one mucosal carcinoma) demonstrated low-frequency MSI (MSI-L). The remaining 56 neoplasms were MSI-stable (MSI-S). Six of six MSI-H, one of two MSI-L, and none of thirty MSI-S lesions showed hMLH1 hypermethylation (P50.001). Diminished hMLH1 protein expression was demonstrated by immunohistochemistry in two of two MSI-H hypermethylated lesions. hMLH1 promoter hypermethylation is signi®cantly associated with MSI and diminished hMLH1 expression in early gastric neoplasms. MSI and hypermethylation-associated inactivation of hMLH1 are more prevalent in early gastric cancers than in gastric adenomas. Thus, hypermethylation-associated inactivation of the hMLH1 gene can occur early in gastric carcinogenesis. Oncogene (2001) 20, 329 ± 335.

BackgroundDiarrheal diseases continue to contribute significantly to morbidity and mortality in infants and young children in developing countries. There is an urgent need to better understand the contributions of novel, potentially uncultured, diarrheal pathogens to severe diarrheal disease, as well as distortions in normal gut microbiota composition that might facilitate severe disease.ResultsWe use high throughput 16S rRNA gene sequencing to compare fecal microbiota composition in children under five years of age who have been diagnosed with moderate to severe diarrhea (MSD) with the microbiota from diarrhea-free controls. Our study includes 992 children from four low-income countries in West and East Africa, and Southeast Asia. Known pathogens, as well as bacteria currently not considered as important diarrhea-causing pathogens, are positively associated with MSD, and these include Escherichia/Shigella, and Granulicatella species, and Streptococcus mitis/pneumoniae groups. In both cases and controls, there tend to be distinct negative correlations between facultative anaerobic lineages and obligate anaerobic lineages. Overall genus-level microbiota composition exhibit a shift in controls from low to high levels of Prevotella and in MSD cases from high to low levels of Escherichia/Shigella in younger versus older children; however, there was significant variation among many genera by both site and age.ConclusionsOur findings expand the current understanding of microbiota-associated diarrhea pathogenicity in young children from developing countries. Our findings are necessarily based on correlative analyses and must be further validated through epidemiological and molecular techniques.