Comparative analysis of Faecalibacterium prausnitzii genomes shows a high level of genome plasticity and warrants separation into new species-level taxa

peer-reviewedBackground Faecalibacterium prausnitzii is a ubiquitous member of the human gut microbiome, constituting up to 15% of the total bacteria in the human gut. Substantial evidence connects decreased levels of F. prausnitzii with the onset and progression of certain forms of inflammatory bowel disease, which has been attributed to its anti-inflammatory potential. Two phylogroups of F. prausnitzii have been identified, with a decrease in phylogroup I being a more sensitive marker of intestinal inflammation. Much of the genomic and physiological data available to date was collected using phylogroup II strains. Little analysis of F. prausnitzii genomes has been performed so far and genetic differences between phylogroups I and II are poorly understood. Results In this study we sequenced 11 additional F. prausnitzii genomes and performed comparative genomics to investigate intraspecies diversity, functional gene complement and the mobilome of 31 high-quality draft and complete genomes. We reveal a very low level of average nucleotide identity among F. prausnitzii genomes and a high level of genome plasticity. Two genomogroups can be separated based on differences in functional gene complement, albeit that this division does not fully agree with separation based on conserved gene phylogeny, highlighting the importance of horizontal gene transfer in shaping F. prausnitzii genomes. The difference between the two genomogroups is mainly in the complement of genes associated with catabolism of carbohydrates (such as a predicted sialidase gene in genomogroup I) and amino acids, as well as defense mechanisms. Conclusions Based on the combination of ANI of genomic sequences, phylogenetic analysis of core proteomes and functional differences we propose to separate the species F. prausnitzii into two new species level taxa: F. prausnitzii sensu stricto (neotype strain A2–165T = DSM 17677T = JCM 31915T) and F. moorei sp. nov. (type strain ATCC 27768T = NCIMB 13872T).This research was conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2273, a Science Foundation Ireland’s Spokes Programme which is co-funded under the European Regional Development Fund under Grant Number SFI/14/SP APC/B3032, and a research grant from Janssen Biotech, Inc

Program evaluation with high-dimensional data

Background It has become increasingly apparent that establishing and maintaining a complex and diverse gut microbiome is fundamental to human health. There are growing efforts to identify methods that can modulate and influence the microbiome, especially in individuals who due to disease or circumstance have experienced a disruption in their native microbiome. Faecal microbial transplantation (FMT) is one method that restores diversity to the microbiome of an individual by introducing microbes from a healthy donor. FMT introduces a complete microbiome into the recipient, including the bacteriome, archaeome, mycome and virome. In this study we investigated whether transplanting an autochthonous faecal virome consisting primarily of bacteriophages could impact a bacteriome disrupted by antibiotic treatment (Faecal Virome Transplantation; FVT).Results Following disruption of the bacteriome by penicillin and streptomycin, test mice (n=8) received a bacteria free, faecal transplant, while Control mice (n=8) received a heated and nuclease treated control. The bacteriomes (as determined via 16S rRNA sequencing) of mice that received an FVT, in which bacteriophages predominate, separated from those of the Control mice as determined by principle co-ordinate analysis (PCoA), and contained differentially abundant taxa that reshaped the bacteriome profile such that it more closely resembled that of the pre-treatment mice. Similarly, metagenomic sequencing of the virome confirmed that the bacteriophages present in the gut of treatment and Control mice differed over time in both abundance and diversity, with transplanted phages seen to colonise the FVT mice.Conclusions An autochthonous virome transplant impacts on the bacteriome and virome of mice following antibiotic treatment. The virome, consisting mainly of bacteriophages, reshapes the bacteriome such that it more closely resembles the pre-antibiotic state. To date, faecal transplants have largely focussed on transferring living microbes, but given that bacteriophage are inert biological entities incapable of colonising in the absence of a sensitive host they could form a viable alternative that may have fewer safety implications and that could be delivered as a robust formulation

Autochthonous faecal viral transfer (FVT) impacts the murine microbiome after antibiotic perturbation

Background: It has become increasingly accepted that establishing and maintaining a complex and diverse gut microbiota is fundamental to human health. There are growing efforts to identify means of modulating and influencing the microbiota, especially in individuals who have experienced a disruption in their native microbiota. Faecal microbiota transplantation (FMT) is one method that restores diversity to the microbiota of an individual by introducing microbes from a healthy donor. FMT introduces the total microbial load into the recipient, including the bacteria, archaea, yeasts, protists and viruses. In this study, we investigated whether an autochthonous faecal viral transfer (FVT), in the form of a sterile faecal filtrate, could impact the recovery of a bacteriome disrupted by antibiotic treatment. Results: Following antibiotic disruption of the bacteriome, test mice received an FVT harvested prior to antibiotic treatment, while control mice received a heat- and nuclease-treated FVT. In both groups of mice, the perturbed microbiome reverted over time to one more similar to the pre-treatment one. However, the bacteriomes of mice that received an FVT, in which bacteriophages predominate, separated from those of the control mice as determined by principal co-ordinate analysis (PCoA). Moreover, analysis of the differentially abundant taxa indicated a closer resemblance to the pre-treatment bacteriome in the test mice that had received an FVT. Similarly, metagenomic sequencing of the virome confirmed that faecal bacteriophages of FVT and control mice differed over time in both abundance and diversity, with the phages constituting the FVT persisting in mice that received them. Conclusions: An autochthonous virome transfer reshaped the bacteriomes of mice post-antibiotic treatment such that they more closely resembled the pre-antibiotic microbiota profile compared to mice that received non-viable phages. Thus, FVT may have a role in addressing antibiotic-associated microbiota alterations and potentially prevent the establishment of post-antibiotic infection. Given that bacteriophages are biologically inert in the absence of their host bacteria, they could form a safe and effective alternative to whole microbiota transplants that could be delivered during/following perturbation of the gut flora

Transforming Microbial Genotyping: A Robotic Pipeline for Genotyping Bacterial Strains

<div><p>Microbial genotyping increasingly deals with large numbers of samples, and data are commonly evaluated by unstructured approaches, such as spread-sheets. The efficiency, reliability and throughput of genotyping would benefit from the automation of manual manipulations within the context of sophisticated data storage. We developed a medium- throughput genotyping pipeline for MultiLocus Sequence Typing (MLST) of bacterial pathogens. This pipeline was implemented through a combination of four automated liquid handling systems, a Laboratory Information Management System (LIMS) consisting of a variety of dedicated commercial operating systems and programs, including a Sample Management System, plus numerous Python scripts. All tubes and microwell racks were bar-coded and their locations and status were recorded in the LIMS. We also created a hierarchical set of items that could be used to represent bacterial species, their products and experiments. The LIMS allowed reliable, semi-automated, traceable bacterial genotyping from initial single colony isolation and sub-cultivation through DNA extraction and normalization to PCRs, sequencing and MLST sequence trace evaluation. We also describe robotic sequencing to facilitate cherrypicking of sequence dropouts. This pipeline is user-friendly, with a throughput of 96 strains within 10 working days at a total cost of < €25 per strain. Since developing this pipeline, >200,000 items were processed by two to three people. Our sophisticated automated pipeline can be implemented by a small microbiology group without extensive external support, and provides a general framework for semi-automated bacterial genotyping of large numbers of samples at low cost.</p> </div

Yields of DNA after automated extraction and normalisation in Module B.

<p>(A) Notched box and whiskers plots of DNA yields after automated DNA extraction from <i>S. enterica</i> or <i>L</i>. <i>monocytogenes</i>. The notch indicates the 95% confidence estimate of the median value (central line), which splits the boxes in the second and third quartiles of the data. The first and fourth quartiles are indicated by the external horizontal lines with outliers shown by single circles. The number of samples that has been summarized is indicated in parentheses under the bacterial designations on the X axis. The left scale reflects the DNA concentration and the right scale is the total yield within the 150 µl elution volume. (B) DNA concentrations for one rack of 96 tubes of <i>S</i>. <i>enterica</i> after elution as in part (A) (empty squares), and after automated normalisation (solid circles) to 3.3 ng/µl.</p

Number of Items in sample management system.

*<p>As of March 2012.</p

Overview of robotic sequencing in Module E.

<p>Top. 1-D and 2-D bar-codes of DNA tubes and 384-well plates are scanned, and information for genes sequencing, including orientation, is collated from the Cherrypicking database for the scanned DNA tubes. Bottom. Left: a pipetting layout which optimises pipetting efficiency is calculated by Script E7 for one to two 384-well plates. Color-coded arrows indicate different genes for each DNA which are to be sequenced. Right: LHS4 dispenses primer mixes from 2 ml tubes in a cooled thermoshaker to a 384-well plate, followed by DNA.</p

Time and costing of pipeline for processing 96 strains.

1<p>Costing includes €0.40 per 2-D bar-coded tube.</p>2<p>Costing includes a repeat rate of 10%.</p>3<p>Sequencing is performed externally, which usually results in a delay of 3–5 days before sequencing traces are available.</p

Overview of five discrete modules within the pipeline with indications of their throughput and principles.

<p>This figure includes photographs of the four liquid handler systems, LHS1-4, which are shown in greater detail in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s001" target="_blank">Fig. S1</a>. Still other details on LHS1 are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone-0048022-g003" target="_blank">Fig. 3A</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s023" target="_blank">File S2</a>. Additional details on Module E are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone-0048022-g005" target="_blank">Fig. 5</a>. GUIs used in Modules A and D/E are in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s002" target="_blank">Figs. S2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s003" target="_blank">S3</a>, respectively.</p

Automated sub-cultivation with LHS1.

<p>(A) Schematic layout of the equipment within the LHS1 cabinet. Positions A and B represent stack units where racks of 2D tubes and deep well plates are stored prior to operations. Position C designates the 5-position, XY-moveable stage for the 96-tip pipettor. Position D represents a rest position used for regripping of racks of 2D tubes before and after capping/decapping in position G. Positions E and F represent 2-D and 1-D bar-code readers. H is a SCARA robotic arm for moving between these positions. Further details of how LHS1 was used are presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s023" target="_blank">File S2</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s006" target="_blank">Figs. S6</a>/<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s008" target="_blank">S8</a> for sterile dispensing of media into 2D tubes, and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s007" target="_blank">S7</a>/<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048022#pone.0048022.s009" target="_blank">S9</a> for aseptic sub-cultivation of bacteria into 2D tubes and deep well plates. (B) Improvements in pipetting parameters (right) which eliminated aerosol formation that led to cross-contamination between cultures (left).</p