Baseline human gut microbiota profile in healthy people and standard reporting template

Abstract

A comprehensive knowledge of the types and ratios of microbes that inhabit the healthy human gut is necessary before any kind of pre-clinical or clinical study can be performed that attempts to alter the microbiome to treat a condition or improve therapy outcome. To address this need we present an innovative scalable comprehensive analysis workflow, a healthy human reference microbiome list and abundance profile (GutFeelingKB), and a novel Fecal Biome Population Report (FecalBiome) with clinical applicability. GutFeelingKB provides a list of 157 organisms (8 phyla, 18 classes, 23 orders, 38 families, 59 genera and 109 species) that forms the baseline biome and therefore can be used as healthy controls for studies related to dysbiosis. This list can be expanded to 863 organisms if closely related proteomes are considered. The incorporation of microbiome science into routine clinical practice necessitates a standard report for comparison of an individual's microbiome to the growing knowledgebase of "normal" microbiome data. The FecalBiome and the underlying technology of GutFeelingKB address this need. The knowledgebase can be useful to regulatory agencies for the assessment of fecal transplant and other microbiome products, as it contains a list of organisms from healthy individuals. In addition to the list of organisms and their abundances, this study also generated a collection of assembled contiguous sequences (contigs) of metagenomics dark matter. In this study, metagenomic dark matter represents sequences that cannot be mapped to any known sequence but can be assembled into contigs of 10,000 nucleotides or higher. These sequences can be used to create primers to study potential novel organisms. All data is freely available from https://hive.biochemistry.gwu.edu/gfkb and NCBI's Short Read Archive.

Fig 1. Metagenomic analysis pipeline for 3 samples.

Step 1: CensuScope is run for each read file against Filtered-nt. Each of the aligned organism approved by manually check is added to the GutFeelingKB and it is versioned. Step 2: For the final analysis the raw read files are mapped against GutFeelingKB organism sequences using HIVE-hexagon. Outputs are tabulated as relative abundance percentages. Unaligned reads from each sample were assembled using IDBA-UD. Contigs that were over 10,000 nucleotides long had their headers modified to include the following: sample ID, numbered according to length (long to short), and additional metadata data about the participant. These contigs are available as a download at (https://hive.biochemistry.gwu.edu/gfkb).

Fig 2. Stacked bar plot of phylogenetic composition of all microbiome taxa in this study collapsed at the phyla level in fecal samples.

Green bars represent Firmicutes and the blue represent Bacteroidetes, the two most abundant bacterial families. For aesthetic purposes the samples (n = 98, bottom) were sorted according to their composition of Bacteroidetes and Firmicutes to demonstrate how the baseline gut microbiome results from this study could be used in conjunction with results from past studies.

Fig 3. Correlation between bacterial organism and nutrient data.

(A) Bifidobacterium is positively correlated with dietary protein intake, specifically vegetable protein, present in vegetables such as broccoli, brussel sprouts, beans, peas, asparagus and beans. (B) Akkermansia is positively associated with body mass index (BMI). (C) Bacteriodes ovatus is positively correlated with daily calorie intake. (D) Bacteriodes ovatus is negatively correlated with body weight.

Fig 4. The range of correlation for all features that have been measured for each of the GW samples.

Each line is a graph of the min and max values using a Cosine Similarity coefficient correlation. A positive value means strong correlation, and a negative value means strong anticorrelation, whereas zero means absolutely no correlation. Given the size of sample pool of 16, 0.7 is taken as the marginal threshold for evidence of some degree of correlation. Each feature that had a correlation with any organism is highlighted in blue. For example, some characteristics such as fat intake have anticorrelation with members of Campulobacter jejuni and Eubacterium family.

Fig 5. FecalBiome Reporting Template.

Personal Information section of the report contains information about the individual who had a sample sequenced, as well as the individual who ordered the sequence. It contains information about the pipeline used for analysis, as well as the sample number for ease of retrieval. Result section contains microbes representing the most abundant organisms which comprise the top 50% of inhabitants. Organismal Comment section includes information from the GutFeelingKB which pertains to the potential function of that organism.