Author Correction: Regional variation limits applications of healthy gut microbiome reference ranges and disease models.

In the version of this article originally published, in the sentence "Applying the same approach to obesity (Fig. 2b), MetS (Fig. 2c) and fatty liver (Fig.

Linking gut microbiota, metabolic syndrome and economic status based on a population-level analysis.

Background: The metabolic syndrome (MetS) epidemic is associated with economic development, lifestyle transition and dysbiosis of gut microbiota, but these associations are rarely studied at the population scale. Here, we utilised the Guangdong Gut Microbiome Project (GGMP), the largest Eastern population-based gut microbiome dataset covering individuals with different economic statuses, to investigate the relationships between the gut microbiome and host physiology, diet, geography, physical activity and socioeconomic status.

Results: At the population level, 529 OTUs were significantly associated with MetS.

Regional variation limits applications of healthy gut microbiome reference ranges and disease models.

Dysbiosis, departure of the gut microbiome from a healthy state, has been suggested to be a powerful biomarker of disease incidence and progression. Diagnostic applications have been proposed for inflammatory bowel disease diagnosis and prognosis, colorectal cancer prescreening and therapeutic choices in melanoma. Noninvasive sampling could facilitate large-scale public health applications, including early diagnosis and risk assessment in metabolic and cardiovascular diseases.

[A machine learning model using gut microbiome data for predicting changes of trimethylamine-N-oxide in healthy volunteers after choline consumption].

Objective: To establish a machine learning model based on gut microbiota for predicting the level of trimethylamine N-oxide (TMAO) metabolism in vivo after choline intake to provide guidance of individualized precision diet and evidence for screening population at high risks of cardiovascular disease.

Methods: We quantified plasma levels of TMAO in 18 healthy volunteers before and 8 h after a choline challenge (ingestion of two boiled eggs). The volunteers were divided into two groups with increased or decreased TMAO level following choline challenge.

The Potential Effect of Oral Microbiota in the Prediction of Mucositis During Radiotherapy for Nasopharyngeal Carcinoma.

Background: Oral mucositis is probably the most debilitating complication that can arise in treating a patient with head and neck cancer. Little is known about the impacts of oral microbiota on the initiation and progression of mucositis.

Methods: Based on 16S rRNA gene sequencing, dynamic changes in oral bacterial profile as well as correlations between the severity of mucositis and bacterial shifts during radiotherapy were investigated.

[Distribution characteristics of trimethylamine N-oxide and its association with gut microbiota].

Objective: To analyze the distribution of trimethylamine N-oxide (TMAO) in healthy adults with different risk factors and explore its association with gut microbiota.

Methods: We collected fasting blood samples and fresh fecal samples from 181 subjects without atherogenesis in the carotid arteries. Plasma TMAO levels of the subjects were determined using stable isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS).

[Bacterial community structure and diversity in soils of different forest ages and types in Bao- tianman forest, Henan Province, China].

To compare the microbial compositions and diversities in soils of different forest ages and types in Baotianman forest, Henan Province, China, genomic DNA of forest soils was extracted for amplifying the 16S rRNA V4 hyper variable region by PCR and sequencing by Illumina MiSeq. The BIPES, UCHIME and QIIME were employed to analyze the soil bacterial community. It was shown that 60 phyla were identified, with Proteobacteria, Acidobacteria, and Verrucomicrobia representing the most dominant lineages and accounting for 29%, 18.

Erratum to: Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.

[This corrects the article DOI: 10.1186/s40168-015-0081-x.].

[Methods, challenges and opportunities for big data analyses of microbiome].

Microbiome is a novel research field related with a variety of chronic inflamatory diseases. Technically, there are two major approaches to analysis of microbiome: metataxonome by sequencing the 16S rRNA variable tags, and metagenome by shot-gun sequencing of the total microbial (mainly bacterial) genome mixture. The 16S rRNA sequencing analyses pipeline includes sequence quality control, diversity analyses, taxonomy and statistics; metagenome analyses further includes gene annotation and functional analyses.

Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity.

Background: The operational taxonomic unit (OTU) is widely used in microbial ecology. Reproducibility in microbial ecology research depends on the reliability of OTU-based 16S ribosomal subunit RNA (rRNA) analyses.

Results: Here, we report that many hierarchical and greedy clustering methods produce unstable OTUs, with membership that depends on the number of sequences clustered.

Homogeneity of the vaginal microbiome at the cervix, posterior fornix, and vaginal canal in pregnant Chinese women.

The vaginal microbiome is an emerging concern in prenatal health. Because the sampling process of vaginal microbiota may pose potential risks for pregnant women, the choice of sampling site should be carefully considered. However, whether the microbial diversity is different across various sampling sites has been controversial.

Diverse vaginal microbiomes in reproductive-age women with vulvovaginal candidiasis.

Vulvovaginal candidiasis (VVC) is one of the most prevalent vaginal infectious diseases, and there are controversial reports regarding the diversity of the associated vaginal microbiota. We determined the vaginal microbial community in patients with VVC, bacterial vaginosis (BV), and mixed infection of VVC and BV using Illumina sequencing of 16S rRNA tags. Our results revealed for the first time the highly variable patterns of the vaginal microbiome from VVC patients.

Illumina sequencing of 16S rRNA tag revealed spatial variations of bacterial communities in a mangrove wetland.

The microbial community plays an essential role in the high productivity in mangrove wetlands. A proper understanding of the spatial variations of microbial communities will provide clues about the underline mechanisms that structure microbial groups and the isolation of bacterial strains of interest. In the present study, the diversity and composition of the bacterial community in sediments collected from four locations, namely mudflat, edge, bulk, and rhizosphere, within the Mai Po Ramsar Wetland in Hong Kong, SAR, China were compared using the barcoded Illumina paired-end sequencing technique.

Comparison of the levels of bacterial diversity in freshwater, intertidal wetland, and marine sediments by using millions of illumina tags.

Sediment, a special realm in aquatic environments, has high microbial diversity. While there are numerous reports about the microbial community in marine sediment, freshwater and intertidal sediment communities have been overlooked. The present study determined millions of Illumina reads for a comparison of bacterial communities in freshwater, intertidal wetland, and marine sediments along Pearl River, China, using a technically consistent approach.

Two-stage clustering (TSC): a pipeline for selecting operational taxonomic units for the high-throughput sequencing of PCR amplicons.

Clustering 16S/18S rRNA amplicon sequences into operational taxonomic units (OTUs) is a critical step for the bioinformatic analysis of microbial diversity. Here, we report a pipeline for selecting OTUs with a relatively low computational demand and a high degree of accuracy. This pipeline is referred to as two-stage clustering (TSC) because it divides tags into two groups according to their abundance and clusters them sequentially.