Gregory B. Gloor

Stool substitute transplant therapy for the eradication of Clostridium difficile infection: ‘RePOOPulating’ the gut

BackgroundFecal bacteriotherapy (‘stool transplant’) can be effective in treating recurrent Clostridium difficile infection, but concerns of donor infection transmission and patient acceptance limit its use. Here we describe the use of a stool substitute preparation, made from purified intestinal bacterial cultures derived from a single healthy donor, to treat recurrent C. difficile infection that had failed repeated standard antibiotics. Thirty-three isolates were recovered from a healthy donor stool sample. Two patients who had failed at least three courses of metronidazole or vancomycin underwent colonoscopy and the mixture was infused throughout the right and mid colon. Pre-treatment and post-treatment stool samples were analyzed by 16 S rRNA gene sequencing using the Ion Torrent platform.ResultsBoth patients were infected with the hyper virulent C. difficile strain, ribotype 078. Following stool substitute treatment, each patient reverted to their normal bowel pattern within 2 to 3 days and remained symptom-free at 6 months. The analysis demonstrated that rRNA sequences found in the stool substitute were rare in the pre-treatment stool samples but constituted over 25% of the sequences up to 6 months after treatment.ConclusionThis proof-of-principle study demonstrates that a stool substitute mixture comprising a multi-species community of bacteria is capable of curing antibiotic-resistant C. difficile colitis. This benefit correlates with major changes in stool microbial profile and these changes reflect isolates from the synthetic mixture.Trial registrationClinical trial registration number: CinicalTrials.gov NCT01372943

Microbiota restoration: natural and supplemented recovery of human microbial communities

In a healthy host, a balance exists between members of the microbiota, such that potential pathogenic and non-pathogenic organisms can be found in apparent harmony. During infection, this balance can become disturbed, leading to often dramatic changes in the composition of the microbiota. For most bacterial infections, nonspecific antibiotics are used, killing the non-pathogenic members of the microbiota as well as the pathogens and leading to a substantial delay in the restoration of a healthy microbiota. However, in some cases, infections can self-resolve without the intervention of antibiotics. In this Review, we explore the mechanisms underlying microbiota restoration following insult (antibiotic or otherwise) to the skin, oral cavity, and gastrointestinal and urogenital tracts, highlighting recovery by natural processes and after probiotic administration.

Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction

MOTIVATION Compensating alterations during the evolution of protein families give rise to coevolving positions that contain important structural and functional information. However, a high background composed of random noise and phylogenetic components interferes with the identification of coevolving positions. RESULTS We have developed a rapid, simple and general method based on information theory that accurately estimates the level of background mutual information for each pair of positions in a given protein family. Removal of this background results in a metric, MIp, that correctly identifies substantially more coevolving positions in protein families than any existing method. A significant fraction of these positions coevolve strongly with one or only a few positions. The vast majority of such position pairs are in contact in representative structures. The identification of strongly coevolving position pairs can be used to impose significant structural limitations and should be an important additional constraint for ab initio protein folding. AVAILABILITY Alignments and program files can be found in the Supplementary Information.

Microbiome Profiling by Illumina Sequencing of Combinatorial Sequence-Tagged PCR Products

We developed a low-cost, high-throughput microbiome profiling method that uses combinatorial sequence tags attached to PCR primers that amplify the rRNA V6 region. Amplified PCR products are sequenced using an Illumina paired-end protocol to generate millions of overlapping reads. Combinatorial sequence tagging can be used to examine hundreds of samples with far fewer primers than is required when sequence tags are incorporated at only a single end. The number of reads generated permitted saturating or near-saturating analysis of samples of the vaginal microbiome. The large number of reads allowed an in-depth analysis of errors, and we found that PCR-induced errors composed the vast majority of non-organism derived species variants, an observation that has significant implications for sequence clustering of similar high-throughput data. We show that the short reads are sufficient to assign organisms to the genus or species level in most cases. We suggest that this method will be useful for the deep sequencing of any short nucleotide region that is taxonomically informative; these include the V3, V5 regions of the bacterial 16S rRNA genes and the eukaryotic V9 region that is gaining popularity for sampling protist diversity.

Using information theory to search for co-evolving residues in proteins

MOTIVATION Some functionally important protein residues are easily detected since they correspond to conserved columns in a multiple sequence alignment (MSA). However important residues may also mutate, with compensatory mutations occurring elsewhere in the protein, which serve to preserve or restore functionality. It is difficult to distinguish these co-evolving sites from other non-conserved sites. RESULTS We used Mutual Information (MI) to identify co-evolving positions. Using in silico evolved MSAs, we examined the effects of the number of sequences, the size of amino acid alphabet and the mutation rate on two sources of background MI: finite sample size effects and phylogenetic influence. We then assessed the performance of various normalizations of MI in enhancing detection of co-evolving positions and found that normalization by the pair entropy was optimal. Real protein alignments were analyzed and co-evolving isolated pairs were often found to be in contact with each other. AVAILABILITY All data and program files can be found at http://www.biochem.uwo.ca/cgi-bin/CDD/index.cgi

Deep sequencing of the vaginal microbiota of women with HIV

Background Women living with HIV and co-infected with bacterial vaginosis (BV) are at higher risk for transmitting HIV to a partner or newborn. It is poorly understood which bacterial communities constitute BV or the normal vaginal microbiota among this population and how the microbiota associated with BV responds to antibiotic treatment. Methods and Findings The vaginal microbiota of 132 HIV positive Tanzanian women, including 39 who received metronidazole treatment for BV, were profiled using Illumina to sequence the V6 region of the 16S rRNA gene. Of note, Gardnerella vaginalis and Lactobacillus iners were detected in each sample constituting core members of the vaginal microbiota. Eight major clusters were detected with relatively uniform microbiota compositions. Two clusters dominated by L. iners or L. crispatus were strongly associated with a normal microbiota. The L. crispatus dominated microbiota were associated with low pH, but when L. crispatus was not present, a large fraction of L. iners was required to predict a low pH. Four clusters were strongly associated with BV, and were dominated by Prevotella bivia, Lachnospiraceae, or a mixture of different species. Metronidazole treatment reduced the microbial diversity and perturbed the BV-associated microbiota, but rarely resulted in the establishment of a lactobacilli-dominated microbiota. Conclusions Illumina based microbial profiling enabled high though-put analyses of microbial samples at a high phylogenetic resolution. The vaginal microbiota among women living with HIV in Sub-Saharan Africa constitutes several profiles associated with a normal microbiota or BV. Recurrence of BV frequently constitutes a different BV-associated profile than before antibiotic treatment.

High throughput sequencing methods and analysis for microbiome research

High-throughput sequencing technology is rapidly improving in quality, speed and cost. It is therefore becoming more widely used to study whole communities of prokaryotes in many niches. This review discusses these techniques, including nucleic acid extraction from different environments, sample preparation and high-throughput sequencing platforms. We also discuss commonly used and recently developed bioinformatic tools applied to microbiomes, including analyzing amplicon sequences, metagenome shotgun sequences and metatranscriptome sequences. This field is relatively new and rapidly evolving, thus we hope that this review will provide a baseline for understanding these methods of microbiome analyses. Additionally, we seek to stimulate others to solve the many problems that still exist with the sensitivity, specificity and interpretation of high throughput microbiome sequence analysis.

Comparative meta-RNA-seq of the vaginal microbiota and differential expression by Lactobacillus iners in health and dysbiosis

BackgroundBacterial vaginosis (BV), the most common vaginal condition of reproductive-aged women, is associated with a highly diverse and heterogeneous microbiota. Here we present a proof-of-principle analysis to uncover the function of the microbiota using meta-RNA-seq to uncover genes and pathways that potentially differentiate healthy vaginal microbial communities from those in the dysbiotic state of bacterial vaginosis (BV).ResultsThe predominant organism, Lactobacillus iners, was present in both conditions and showed a differing expression profile in BV compared to healthy. Despite its minimal genome, L. iners differentially expressed over 10% of its gene complement. Notably, in a BV environment L. iners increased expression of a cholesterol-dependent cytolysin, and of mucin and glycerol transport and related metabolic enzymes. Genes belonging to a CRISPR system were greatly upregulated suggesting that bacteriophage influence the community. Reflective of L. iners, the bacterial community as a whole demonstrated a preference for glycogen and glycerol as carbon sources under BV conditions. The predicted end-products of metabolism under BV conditions include an abundance of succinate and other short-chain fatty-acids, while healthy conditions are predicted to largely contain lactic acid.ConclusionsOur study underscores the importance of understanding the functional activity of the bacterial community in addition to characterizing the population structure when investigating the human microbiome.

At the crossroads of vaginal health and disease, the genome sequence of Lactobacillus iners AB-1

Lactobacilli have long been regarded as important constituents of the healthy human vagina. Lactobacillus iners is the most frequently detected bacterial species in the vagina, but little is known about its characteristics. We report a description of the whole-genome sequence of L. iners AB-1 along with comparative analysis of published genomes of closely related strains of lactobacilli. The genome is the smallest Lactobacillus reported to date, with a 1.3-Mbp single chromosome. The genome seems to have undergone one or more rapid evolution events that resulted in large-scale gene loss and horizontal acquisition of a number of genes for survival in the vagina. L. iners may exhibit specialized adaptation mechanisms to the vaginal environment, such as an iron–sulfur cluster assembly system, and several unique σ factors to regulate gene transcription in this fluctuating environment. A potentially highly expressed homolog of a cholesterol-binding lysin may also contribute to host cell adhesion or act as a defense mechanism against other microbes. Notably, there is a lack of apparent adhesion proteins, but several cell-anchor proteins were identified and may be important for interaction with the host mucosal tissues. L. iners is widely present in healthy females as well as those suffering from bacterial vaginosis or who have undergone antimicrobial therapy, suggesting that it is an important indigenous species of the vagina.

Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis.

BackgroundExperimental designs that take advantage of high-throughput sequencing to generate datasets include RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), sequencing of 16S rRNA gene fragments, metagenomic analysis and selective growth experiments. In each case the underlying data are similar and are composed of counts of sequencing reads mapped to a large number of features in each sample. Despite this underlying similarity, the data analysis methods used for these experimental designs are all different, and do not translate across experiments. Alternative methods have been developed in the physical and geological sciences that treat similar data as compositions. Compositional data analysis methods transform the data to relative abundances with the result that the analyses are more robust and reproducible.ResultsData from an in vitro selective growth experiment, an RNA-seq experiment and the Human Microbiome Project 16S rRNA gene abundance dataset were examined by ALDEx2, a compositional data analysis tool that uses Bayesian methods to infer technical and statistical error. The ALDEx2 approach is shown to be suitable for all three types of data: it correctly identifies both the direction and differential abundance of features in the differential growth experiment, it identifies a substantially similar set of differentially expressed genes in the RNA-seq dataset as the leading tools and it identifies as differential the taxa that distinguish the tongue dorsum and buccal mucosa in the Human Microbiome Project dataset. The design of ALDEx2 reduces the number of false positive identifications that result from datasets composed of many features in few samples.ConclusionStatistical analysis of high-throughput sequencing datasets composed of per feature counts showed that the ALDEx2 R package is a simple and robust tool, which can be applied to RNA-seq, 16S rRNA gene sequencing and differential growth datasets, and by extension to other techniques that use a similar approach.