Category Archives: Microbiome Clinical Trials

David Kirk and Ben Bradley Explain the Gut Microbiome and Clostridium difficile

It has access to the largest surface area of the body, alters drugs before they even enter the blood stream and could be a potent medicinal weapon… yet there is much we still don’t understand about the microbiome.

Here David Kirk and Ben Bradley tell us about their attempts to heal us from within

We are not alone. We are inhabited by hundreds of species of microbes, which represent millions of genes. Together, these microscopic organisms – bacteria, fungi, archaea and viruses ­– and their collective genomes make up the microbiome.

To review this article in its entirety please click on the following link:

https://www.labnews.co.uk/interviews/guestbook/therapeutics-live-21-05-2018/

In the gut, microbes break down otherwise indigestible dietary fibres and release nutrients, such as B-vitamins and short chain fatty acids, which can be absorbed by the intestines. They secrete other small molecules or peptides which interact with the body via the bloodstream and immune system. The majority of these have yet to be identified and characterised. In addition, commensal microbes deter opportunistic pathogens from invading the competitive niche of the intestinal tract.

LBPs are a recent concept and have their origins in a novel treatment for C. difficile infection: the faecal microbiota transplant… this is exactly what you think it is

The disruption of the microbiome, termed dysbiosis, is associated with an ever-growing list of conditions. Obesity and metabolic syndrome, for instance, are associated with a microbiome less diverse than that of a healthy individual. Inflammatory bowel disease (IBD) and colorectal cancer are associated with a decrease in butyrate-producing bacteria like Clostridia, and an increase in Enterobacteriaceae and Bacilli.

An air of scepticism comes with the phrase “associated”. Microbiome research is still a developing field, and the presence or absence of a single species or genus cannot be directly blamed for conditions like obesity or IBD in all patients. The complex interplay between host and microbiome depends as much on the host’s genetic susceptibility and environment as on the dysbiosis or lack of diversity in the microbiome. The million dollar question remains: What exactly constitutes a ‘healthy microbiome’?

A powerful tool
The microbiome is adaptive and changes in response to diet, environment and disease. It has become increasingly clear that many drugs interact with the microbiome, with some requiring microbiota derived enzymes for activation and others being rendered non-functional or even toxic via microbiota dependant conversion. As research in host-microbe interaction continues, more accurate relationships between the microbiome and human illness will be uncovered.

The gut microbiome presents an interesting medicinal target in itself. It interacts directly with one of the largest surface areas of the body. Therefore it has easy access to the bloodstream through diffusion of nutrients and small molecules, and via a mucosal layer rich in multiple cell types of the adaptive and innate immune systems. Due to the powerful delivering capacity of the gut, most microbial-based treatments in development aim to add to the microbiome rather than take away from it.

Microbial therapies using living organisms are known as live biotherapeutic products (LBPs). LBPs are a recent concept and have their origins in a novel treatment for C. difficile infection (CDI): the faecal microbiota transplant.

This is exactly what you think it is.

CDI occurs when the gut microbiome is wiped out by antibiotic use and becomes infected by C. difficile, an organism that is normally unable to compete against the natural microbiota. This illness may recur in spite of further antibiotic treatments, and can be fatal. The most effective treatment, in extreme cases, is a faecal transplant into the infected recipient. Transplanted microbes thrive and outcompete C. difficile, effectively reversing the infection in over 90% of cases. But due to the uncertainty of what constitutes a ‘healthy microbiome’, a faecal transplant cannot be considered a cure-all for dysbiosis-associated illness.

Daunting clinical trials
This “unknown” of host-microbe interaction sparked the need to develop defined microbiome therapies. Naturally, CDI was one of the first targets for a defined treatment. Several companies are developing and trialling defined cocktails of bacteria known to safely inhabit the gut with the goal of outcompeting C. difficile with Seres Therapeutics and Rebiotix entering phase 3 trials in 2018.

CHAIN Biotech is developing technology to deliver therapeutics to the gut microbiome using engineered Clostridium, a spore forming bacterium, and have a lead candidate targeting IBD. IBD is a collection of inflammatory diseases of the gut, commonly treated with steroid injections which cause numerous unpleasant side effects. Our approach is to deliver an LBP directly to the gut, where it can produce an anti-inflammatory in situ. We also make use of this species’ natural ability to produce spores, which survive the acidic environment of the stomach and germinates into therapeutic-producing cells only in the anaerobic environment of the lower intestine.

This elementary approach – adding one organism with a safe history of use in the human gut, and having it produce one novel product – minimizes the risk of disruption to the microbiome and delivers the treatment directly to the affected area. The next stages, taking LBPs to clinical trial, are daunting. A lot of unknowns exist around the human gut microbiome and these kinds of treatments. Few microbiome companies have LBPs in late-stage clinical trial, but those that do give hope to both patients and us that LBPs will someday heal us from within.

Ferring Pharmaceuticals Acquires Rebiotix, Inc.

Ferring acquires innovative biotechnology company and microbiome pioneer Rebiotix Inc.

  • Rebiotix’s RBX2660 is a non-antibiotic treatment in Phase 3 development for the prevention of recurrent Clostridium difficile infection (CDI) and has the potential to be the world’s first approved human microbiome product
  • CDI is one of the most common healthcare-associated infections in the US, affecting more than 500,000 people and causing approximately 29,000 deaths each year.1
  • Ferring’s global capabilities ensure broader patient access to any future approved human microbiome treatments derived from Rebiotix’s Microbiota Restoration Therapy™ (MRT™) drug platform

Saint-Prex, Switzerland & Roseville, MN, US – 05 April, 2018 — Ferring Pharmaceuticals* and Rebiotix Inc.  announce that they have agreed to the acquisition of Rebiotix by Ferring. This acquisition brings together two innovative healthcare companies that share a common commitment to exploring and understanding the human microbiome to develop new solutions for patients.

The most advanced investigational microbiome treatment from Rebiotix is RBX2660, a non-antibiotic treatment currently in Phase 3 development for the prevention of recurrent CDI. RBX2660 has the potential to be the first human microbiome product approved anywhere in the world. In the US, RBX2660 has received FDA Fast Track, Breakthrough Therapy and Orphan Drug Designations, which means the FDA considers it eligible for Expedited Review, once the submission has been made.

“The scientific advances Rebiotix has made add significant strategic value to Ferring’s leadership in gastroenterology,” said Michel Pettigrew, President of the Executive Board and Chief Operating Officer, Ferring Pharmaceuticals. “Therapies targeted towards the microbiome have the potential to transform healthcare. Together, we have a unique opportunity to help people living with debilitating and life-threatening conditions like Clostridium difficile infection.”

Rebiotix’s proprietary MRT drug platform delivers healthy, live, human-derived microbes into the gastrointestinal tract. It provides a standardised, stabilised product that is ready-to-use in an easy-to-administer format. The MRT pipeline consists of a number of investigational treatments including RBX7455, a non-frozen, lyophilised oral capsule formulation, in development for the prevention of recurrent CDI.

“Ferring shares our passion for understanding the role the microbiome plays in human health and has global capabilities that offer huge potential for the investigational therapies that we have in development,” said Lee Jones, Founder, President and Chief Executive Officer, Rebiotix, Inc. “Rebiotix was founded to revolutionise healthcare by harnessing the power of the human microbiome and this is a significant milestone in achieving that goal.”

“This acquisition strengthens our innovation pipeline and complements our own ongoing microbiome research as well as our partnerships with world-leading organisations in this area,” said Per Falk, Chief Science Officer, Ferring Pharmaceuticals. “Rebiotix’s culture and passion for high quality, innovative research fits with our own and complements our existing R&D capabilities.”

In addition to the acquisition of Rebiotix, Ferring, as a leader in gastroenterology, is supported by ongoing partnerships with world-leading research organisations in the field of microbiome research including the Karolinska Institutet and Science for Life Laboratory, the Centre for Translational Microbiome Research, Intralytix, The Institut Pasteur, the University of Lille, MyBiotics Pharma, March of Dimes and Metabogen.


About Ferring Pharmaceuticals

Ferring Pharmaceuticals is a research-driven, specialty biopharmaceutical group committed to helping people around the world build families and live better lives. Headquartered in Saint-Prex, Switzerland, Ferring is a leader in reproductive medicine and women’s health, and in specialty areas within gastroenterology and urology. Ferring has been developing treatments for mothers and babies for over 50 years. Today, over one third of the company’s research and development investment goes towards finding innovative and personalised healthcare solutions to help mothers and babies, from conception to birth. Founded in 1950, Ferring now employs approximately 6,500 people worldwide, has its own operating subsidiaries in nearly 60 countries and markets its products in 110 countries.

Learn more at www.ferring.com, or connect with us on Twitter, Facebook, Instagram, LinkedIn and YouTube.

About Rebiotix Inc.

Rebiotix Inc. is a late-stage clinical microbiome company focused on harnessing the power of the human microbiome to revolutionise the treatment of challenging diseases. Rebiotix possesses a deep and diverse clinical pipeline targeting several other disease states with drug products built on its pioneering MRT platform. The MRT platform is a standardised, stabilised drug technology that is designed to rehabilitate the human microbiome by delivering a broad consortium of live microbes into a patient’s intestinal tract via a ready-to-use and easy-to-administer format. For more information on Rebiotix and its pipeline of human microbiome-directed therapies, visit www.rebiotix.com.

About RBX2660

RBX2660 is the most advanced product utilising Rebiotix’s proprietary MRT drug platform. RBX2660 is in Phase 3 development for the prevention of recurrent CDI and has the potential to be the first human microbiome product approved anywhere in the world. It consists of a microbiota suspension of intestinal microbes and is administered via enema.

*Ferring Holding Inc. signed the agreement as part of Ferring Pharmaceuticals Group

Rebiotix In Partnership With BioRankings® Develops Microbiome Health Index™ (MHI™) to Identify Indicators for Microbiome Restoration

Rebiotix Inc., a clinical-stage microbiome company focused on harnessing the power of the human microbiome to treat debilitating diseases, announced  on February 12, 2018 — the development of the Microbiome Health Index™ (MHI™) to provide the microbiome research community with a standardized metric to quantify the rehabilitation of the human microbiome.

MHI was established in partnership with data analytics firm, BioRankings®, to enable a non-biased comparison of the efficacy of microbiome-based therapeutics.

New MHI data will be presented at the 28th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID 2018) in April.

“In developing the Microbiome Health Index, our aim is to provide an objective, universal tool to measure the restoration of a dysbiotic microbiome across different trial designs, sequencing methods and across multiple drug technologies,” stated Ken F. Blount, Ph.D., Chief Scientific Officer of Rebiotix.  “Initial analyses using MHI in Clostridium difficile (C. diff) infections have demonstrated its significant potential to quantify and differentiate dysbiotic from healthier microbiomes.  As presented at ACG2017, MHI was able to quantify the relationship between four key bacterial classes into a single metric that can distinguish patients with dysbiosis resulting from C. diff. From this, we were able to gain valuable insight into the mechanism of action by which Rebiotix’s Phase 3 microbiota drug, RBX2660, is able to rehabilitate a dysbiotic microbiome to a healthier state.”

Blount continued, “MHI is now being employed to analyze microbiome profile data gathered in the ongoing Phase 1 clinical trial of RBX7455, Rebiotix’s lyophilized, non-frozen oral capsule formulation. The intent with this research is to further strengthen and refine MHI and confirm the RBX2660 analysis. Additionally, we will look to utilize MHI in new diseases states being studied.”

Bill Shannon, Ph.D., MBA, Co-Founder and Managing Partner of Analytics at BioRankings said, “The human microbiome is a new frontier where very little analytical methodology or rigorous statistical methods have been developed specifically for this type of data.  Analytical tools such as MHI will be critical to advance translational clinical microbiome research, and we are emboldened by the MHI data that have been reported and continuing to be collected.  Our vision is for MHI to become a standard measure for microbiome research, potentially serving as a validated endpoint for clinical trials and providing both a predictive measure and actionable data.”

MHI provides a unidimensional expression of changes in four taxonomic classes known to have relevance to microbiome health and colonization resistance – Bacteriodia, Clostridia, Gammaproteobacteria and Bacilli.

Utilizing microbiome profiles of patients from the PUNCH CD2 Phase 2b trial of RBX2660, researchers determined that MHI can effectively distinguish patients with dysbiosis from healthier patients, as defined by the RBX2660 product profile and the Human Microbiome Project.  Notably following RBX2660 treatment, MHI significantly increased as early as seven days in responders compared to baseline and continued to increase at day 30 and day 60.

About BioRankings®

BioRankings is a contract analytics firm that works with clients to extract actionable results from their data. Their business philosophy centers on providing clients and partners with the methods, software, and support they need to make full use of their data and design accurate, cost-efficient experiments.  For more information on BioRankings, please visit http://www.biorankings.com.

About Rebiotix Inc.

Rebiotix Inc. is a late-stage clinical microbiome company focused on harnessing the power of the human microbiome to revolutionize the treatment of challenging diseases. Rebiotix possesses a deep and diverse clinical pipeline, with its lead drug candidate, RBX2660, in Phase 3 clinical development for the prevention of recurrent Clostridium difficile (C. diff) infection.  RBX2660 has been granted Fast Track status, Orphan Drug and Breakthrough Therapy designation from the FDA for its potential to prevent recurrent C. diff. infection. Rebiotix’s clinical pipeline also features RBX7455, a lyophilized, non-frozen, oral capsule formulation, which is currently the subject of an investigator-sponsored Phase 1 trial for the prevention of recurrent C. diff. infection.  In addition, Rebiotix is targeting several other disease states with drug products built on its pioneering Microbiota Restoration Therapy™ (MRT™) platform.  MRT is a standardized, stabilized drug technology that is designed to rehabilitate the human microbiome by delivering a broad consortium of live microbes into a patient’s intestinal tract via a ready-to-use and easy-to-administer format. For more information on Rebiotix and its pipeline of human microbiome-directed therapies, visit http://www.rebiotix.com.

Gut Microbiome Research High-resolution Profiling Reveals the Extent of Clostridium difficile (C.diff.) Burden

Microbiome profiling through 16S rRNA gene sequencing has proven to be a valuable tool to characterize the diversity and composition of gut microbial communities, including in studies of CDI development and recurrence.8

 

Authors:

  • Ninalynn Daquigan,
  • Anna Maria Seekatz,
  • K. Leigh Greathouse,
  • Vincent B. Young &
  • James Robert White
Published online:

Abstract

Microbiome profiling through 16S rRNA gene sequence analysis has proven to be a useful research tool in the study of C. difficile infection (CDI); however, CDI microbiome studies typically report results at the genus level or higher, thus precluding identification of this pathogen relative to other members of the gut microbiota.

Accurate identification of C. difficile relative to the overall gut microbiome may be useful in assessments of colonization in research studies or as a prognostic indicator for patients with CDI.

To investigate the burden of C. difficile at the species level relative to the overall gut microbiome, we applied a high-resolution method for 16S rRNA sequence assignment to previously published gut microbiome studies of CDI and other patient populations. We identified C. difficile in 131 of 156 index cases of CDI (average abundance 1.78%), and 18 of 211 healthy controls (average abundance 0.008%).

We further detected substantial levels of C. difficile in a subset of infants that persisted over the first two to 12 months of life. Correlation analysis of C. difficile burden compared to other detected species demonstrated consistent negative associations with C. scindens and multiple Blautia species.

These analyses contribute insight into the relative burden of C. difficile in the gut microbiome for multiple patient populations, and indicate that high-resolution 16S rRNA gene sequence analysis may prove useful in the development and evaluation of new therapies for CDI.

Introduction

Clostridium difficile infection (CDI) poses a major healthcare burden to the global population, with an estimated 450,000 cases and 29,000 deaths in the United States annually.1,2 CDI is often associated with antibiotic treatment and is frequently acquired by patients during hospitalization.

Multiple diagnostic tests for CDI are available and hospitals commonly use a combination of enzyme immunoassay (EIA) and glutamate dehydrogenase (GDH) testing in tandem with real-time polymerase chain reaction (PCR) for increased sensitivity and shorter turnaround time.3

After diagnosis, patients with CDI are typically treated with metronidazole and/or vancomycin depending on symptom severity.3 Treatment failure is estimated to occur in 20% of patients, resulting in a recurrent CDI population that may require other treatment strategies.4,5 The development of microbial-based therapeutics, such as fecal microbiota transplantation (FMT) and combinations of selected microbes for the treatment of recurrent CDI suggests that mixtures of commensal microbes may be routinely utilized in the future as an alternative to powerful antibiotics.6,7

Microbiome profiling through 16S rRNA gene sequencing has proven to be a valuable tool to characterize the diversity and composition of gut microbial communities, including in studies of CDI development and recurrence.8

Given the intricate relationship between the gut microbiota and CDI, accurate                                   identification of C. difficile directly from 16S rRNA profiles in patient populations could be a valuable measure in future studies. However, a fundamental challenge to studying C. difficile through these approaches has been the level of taxonomic resolution provided through short 16S rRNA sequences.

As a result, most microbiome sequencing studies of CDI utilize higher aggregate taxonomic categories (e.g., the Clostridium XI cluster, which encompasses many other organisms related to C. difficile) as a proxy for the organism itself or simply avoid quantification altogether.9,10,11,12,13,14,15,16,17

Here we utilize a high-resolution method (Resphera Insight) for assigning species-level context to 16S rRNA gene sequence data to estimate C. difficile burden in different patient populations. This method was recently validated for detection of Listeria monocytogenes18 and Salmonella enterica,19,20 and was applied in this study to determine the relative abundance of C. difficile in several clinically relevant patient groups. Re-examining published 16S rRNA gene sequence datasets has confirmed previous associations of C. difficile with C. scindens, and identified new positive and negative correlations of C. difficile with other species, both of which may help provide insight into community aspects of C. difficile colonization and resistance against CDI.

Results

Evaluation of sensitivity and specificity for C. difficile identification

One of the challenges of 16S rRNA gene sequencing is the limited information available in these short DNA fragments to distinguish related microbial members below the genus-level. To accurately assess C. difficile at the species level from 16S rRNA gene sequence data, we used a method developed specifically for species level characterization (Resphera Insight, see Methods). We first validated this approach by obtaining full-length 16S rRNA gene sequences from 804 novel C. difficile isolates derived from multiple sources, and subsequently simulated noisy 16S rRNA gene sequence reads for taxonomic assignment (see Methods). Performance was measured using the Diagnostic True Positive Rate (DTP), defined as the percentage of sequences with an unambiguous assignment to C. difficile. The method achieved an average DTP of 99.9% (ranging from 98.92 to 100% per isolate, Table S1), indicating sufficient sensitivity to detect C. difficile from short 16S rRNA gene sequence reads.

In addition to establishing sufficient sensitivity to detect C. difficile, we also sought to evaluate false positive rates in which the method incorrectly assigns a sequence to C. difficile. As this species is a member of the Clostridium XI cluster, a false positive assessment was performed based on in silico simulations of 22 other members of this group, including the very similar Clostridium irregulare. Simulating 10,000 16S rRNA gene sequence reads per species with a 0.5% error rate, 20 of 22 species resulted in zero false positive assignments to C. difficile, with the highest false positive rate (0.07%) attributed to Clostridium irregulare (Table 1).

Table 1: False positive rates for 22 related species

Representation of C. difficile relative to the microbiota in adult cases of CDI and healthy individuals

To examine the presence of C. difficile in different human populations, we re-examined existing published 16S rRNA gene sequencing datasets with our validated method. We first compared the relative abundance of C. difficile across a cohort of healthy individuals to two cohorts of patients diagnosed with CDI (symptomatic index cases) from Seekatz et al.10 and Khanna et al.21 (Table S2). The Seekatz protocol for CDI diagnosis followed a two-stage algorithm employing enzyme immunoassay for GDH antigen and toxins A and B, with confirmation of tcdB gene presence via PCR if toxin and GDH results were discordant; the Khanna et al. protocol for CDI diagnosis was not reported in the original publication. The healthy patient cohort and Seekatz CDI datasets were generated using equivalent processing and sequencing methods.10 Average analyzed sequencing depths per sample for CDI and healthy groups were 16,114 and 14,937, respectively.

Overall, C. difficile was detected in 58 of 70 CDI index patients (82.9%) in the Seekatz study with an average abundance of 3.04% (Fig. 1a). In the Khanna dataset, C. difficile was detected in 73 of 86 CDI index patients (84.9%) with an average abundance of 0.76% (Fig. 1b). Among healthy controls, only 18 of 211 (8.5%) harbored detectable levels of C. difficile, with an average abundance of 0.008%, significantly less than both Seekatz and Khanna index cases (P < 2e-16; Mann–Whitney test).

Fig. 1
Fig. 1

Relative burden of C. difficile in the gut microbiome of two cohorts of CDI index patients and healthy controls. a Index cases of recurrent CDI (Seekatz et al.) and b CDI index patients (Khanna et al.) frequently harbored moderate to high levels of C. difficile. c Healthy controls. Overall 91.5% of controls had no detectable C. difficile and 0.9% maintained C. difficile levels higher than 0.1%

We were further interested in determining whether the ability to detect C. difficile or varying levels of C. difficile relative abundance from 16S rRNA gene sequences was related to disease outcome. The Seekatz dataset included samples collected from patients that went on to develop recurrent CDI, a serious outcome following primary diagnosis, or from patients who were later reinfected with CDI beyond the standard time recurrence window.10 Additionally, a severity score22 was available for some of the patients. Across the full Seekatz CDI positive sample set, our method detected C. difficile above 0.1% abundance in 59.2% of samples (Table 2). On average, patients with CDI for index (at primary diagnosis), recurrence or reinfection events had C. difficile abundances greater than 1% regardless of the calculated severity status using Infectious Diseases Society of America (IDSA) standards. We found no significant associations of C. difficile abundance with IDSA severity status among index samples or at the time of recurrence or reinfection (P > 0.05, Mann–Whitney test).

Table 2: C. difficile relative abundances in cases of CDI from Seekatz et al.10 compared to healthy controls

Representation of C. difficile relative to the microbiota in infants

To assess the levels of C. difficile carriage among infants relative to the total gut microbiome, we re-examined 16S rRNA gene sequence datasets describing longitudinal studies of pre-term infants in the neonatal intensive care unit (NICU) by Zhou et al.23 and a single infant profiled during the first 18 months of life by Davis et al.16 In the Zhao dataset, 12 necrotizing enterocolitis (NEC) cases and 26 age-matched controls (all treated at Brigham and Women’s Hospital NICU, Boston, MA) were sequenced with an average of seven samples per subject. The Davis asymptomatic case study consisted of profiling 50 fecal samples over time, during which researchers noted colonization switching between toxigenic and non-toxigenic strains and observed 100,000-fold fluctuations of C. difficile spore counts.16

In these two 16S rRNA gene sequence datasets, moderate levels of C. difficile (>1.0% abundance) appeared consistently within infants over time. In the Zhao dataset, C. difficile was detected in 25 of 38 (66%) infants, including 6 of 12 (50%) infants with NEC, and 19 of 26 (73%) normal infants. There was no significant difference in overall C. difficile presence between NEC and normal infants (P = 0.27, Fisher’s exact test), and both groups maintained statistically similar C. difficile abundance distributions relative to their total gut microbial communities under multivariate regression after adjustment for patient source (Fig. 2a). As the original Davis case study determined C. difficile carriage using spore counts and GDH concentration, we detected substantial representation of C. difficile (up to 7.1% abundance) until the time of weaning and transition to cow’s milk (Fig. 2b). We further found a statistically significant correlation between our C. difficile relative abundance estimates and GDH concentration measurements from the Davis study (Spearman correlation = 0.817; P = 5e-13).

Fig. 2
Fig. 2

Distribution of C. difficile during longitudinal gut microbiome sampling of infants. a Pre-term infants in a NICU, including those developing necrotizing enterocolitis (purple) and normal (grey). Each boxplot reflects a single patient with multiple time points (total samples per patient shown along the x-axis). b A longitudinal case study of an infant before (red) and after (blue) weaning during the first 18 months of life. During the transition to cow’s milk, C. difficile relative abundance fell to undetectable levels

Correlations of C. difficile with other bacterial species

Recent studies in animal models have indicated that certain species may generate metabolites that inhibit C. difficile, such as the production of secondary bile acids by C. scindens.15 However, previous studies correlating the abundance of C. difficile with other taxa did not utilize the microbiome-based abundances directly, but rather quantified C. difficile abundance through other means such as real-time PCR, colony forming units through culture, measuring GDH concentration or spore counts.15,16,17

We sought to determine whether high-resolution analysis of the 16S rRNA gene sequence data itself could reveal the same associations, and perhaps other relevant species. Computing correlations using Compositionality Corrected by REnormalization and PErmutation (CCREPE)24 across our re-analyzed cohorts, we found a significant negative association between C. difficile and C. scindens for the Khanna CDI patient cohort and the Davis infant longitudinal study (P < 0.02 for both datasets), with a supporting trend in the other studies (Fig. 3, Table S3). Additionally, multiple members of Blautia spp. displayed a consistent negative correlation like that of C. scindens (Fig. 3, Table S3). In contrast, other Clostridia such as C. neonatale and C. paraputrificum and members of Veillonella showed strong positive associations with C. difficile abundance. In silico simulations of noisy 16S rRNA gene sequence reads from these species confirmed a low mis-assignment rate (average 0.08%; see Table S4).

Fig. 3
Fig. 3

Correlation analysis identifies species positively or negatively associated with C. difficile. The CCREPE N-dimensional checkerboard score (y-axis) incorporates the ratio of co-variation to co-exclusion patterns normalized to a range of (−1, +1). In addition to C. scindens, we identify significant negative correlations with C. difficile for members of Blautia and positive correlations with other Clostridia and Veillonella spp. (*P ≤ 0.05). Ambiguous species level assignments are denoted by slashes. Key for re-analyzed datasets from the following studies: Recurrent CDI=10, Index CDI=21, FMT=9, Infant longitudinal=16, NICU=23 (Table S2)

Discussion

In this study, we sought to identify species-level abundances of C. difficile in 16S rRNA gene sequence datasets from different patient populations using a validated algorithm (Resphera Insight). Similar to previous studies of Listeria monocytogenes18 and Salmonella enterica,19,20 validation using a high-resolution taxonomic assignment method from 804 novel C. difficile isolates established an overall sensitivity of 99.9% with a marginal false positive rate less than 0.1%, suggesting that C. difficile could be distinguished from other related microbiota members.

Compared to the microbiota of healthy individuals, we observed a higher presence and relative abundance of C. difficile in microbiota data collected from two CDI patient cohorts. 8.5% of healthy individuals were positive for C. difficile using our approach, supporting previous epidemiological assessments of asymptomatic carriage rates.25,26,27,28 Although analysis of CDI datasets revealed a wide distribution of C. difficile relative abundances (ranging from virtually undetectable to above 50% of total sequences), the relative abundance of detected C. difficile in relation to other members of the microbiota was significantly lower in healthy individuals than that of CDI patients. The ability to assess C. difficile levels as part of the microbiota community is potentially more important within population surveys compared to diagnosis using traditional PCR or GDH/EIA tests that merely account for the presence of C. difficile using toxin B or GDH as a proxy.

While detection of C. difficile from 16S rRNA gene sequence data is limited by sequencing depth, our results suggest that C. difficile does not generally reside in healthy adults. In contrast, we did not detect C. difficile in all patients with CDI. The relative presence of C. difficile in these patients is likely below the detection limit given the available sequencing depth, however some of the samples collected from patients in the Seekatz dataset were collected during antibiotic treatment, thus potentially limiting growth of C. difficile during those time points. Indeed, Seekatz et al. report that they were unable to retrieve C. difficile strains from all patient time points via anaerobic cultivation, generally the gold standard for C. difficile detection and diagnosis.

In a third cohort of 14 recurrent CDI patients receiving fecal microbiota transplantation from nine healthy donors (FMT; Table S2, Fig. 3), C. difficile was less frequently detected than the Seekatz and Khanna index CDI patient groups. Only 4 of 14 FMT patients had any detectable levels of C. difficile before treatment, and 3 of 14 had observations of C. difficile post-FMT. Notably, Resphera Insight detected C. difficile presence in both patients who went on to develop symptomatic CDI post-FMT (recipient IDs 005 and 006).9 Prior to FMT, all patients were treated with vancomycin (125 mg 4× per day) for at least 4 days before and the day of transplantation. Thus, we attribute the reduced detection of C. difficile in this cohort to differences in patient treatment before sampling.

Applying our approach to a longitudinal dataset of 38 premature infants in a single NICU, we identified C. difficile in two-thirds of this patient cohort. Asymptomatic carriage of C. difficile among infants has been observed to be higher than for adults, and it remains unknown whether infant cases of CDI represent true disease.29,30 While CDI testing of infants is not recommended,30 recent epidemiological studies indicate 26% of children hospitalized with CDI are infants under 12 months of age, and 5% are neonates.31 In one study of 753 pediatric patients 0 to 12 years of age, 2.9% of CDI outpatients, 4.6% of CDI inpatients, and 6.6% of healthy controls were positive for C. difficile toxin B.32 Another recent study of C. difficile in 338 healthy infants (<2 yrs) in the United Kingdom found 10% were colonized at enrollment with a toxigenic strain, and 49% became colonized with a toxigenic strain post-enrollment.33 Symptomatic Clostridium difficile infections are believed not to occur in infants due to the expected lack of specific toxin receptors and under-developed signaling pathways in the gut; however, these proposed mechanisms have not been rigorously evaluated in studies of humans.34,35,36 Multiple case studies have argued that CDI can occur in this patient population,36 and there is ongoing debate about the appropriate policy for treatment of symptomatic children who test positive for C. difficile.37,38

Our analysis of an infant case study of asymptomatic colonization during the first 18 months of life identified a reduction in C. difficile relative abundance after abrupt transition from human milk to cow’s milk. Yet in a large longitudinal study by Stoesser and colleagues, multivariate analysis demonstrated that breastfeeding (mixed with formula or exclusively) was protective against asymptomatic C. difficile colonization.33 As noted by Davis and colleagues,16C. difficile does not carry the functional capacity for cleaving monosaccharides from oligosaccharide side chains and thus depends on the generation of monomeric glucose by other commensal members of the gut microbiome.39 Additionally, C. difficile relies on sialic acid as a carbon source for expansion made available by other commensals such as Bifidobacterium species.40 Therefore, the reduction of C. difficile after transition to cow’s milk is potentially the result not of milk source alone, but shifting microbial community composition and the presence of substrates by which C. difficile may thrive.

We were also able to identify a significant negative correlation between the abundance of C. difficile and C. scindens in one of the CDI cohorts, confirming similar trends reported by Buffie et al.15C. scindens, a secondary bile acid producer of deoxycholic acid which has been shown to protect against CDI, may have important translational implications.13,41 New and consistent negative correlations were also identified between C. difficile and multiple species within the Blautia genus including B. faecis, B. luti, B. schinkii, and B. wexlerae. Notably, some members of the Blautia genus are known for 7α-dehydroxylating activity of primary bile acids,42,43,44 however this remains to be evaluated for the species we identified in this study. These data suggest that species other than C. scindens may provide relevant functional capabilities in the context of CDI and prove to be informative in the development of future microbial-based therapeutics. One exception to these findings was the lack of negative correlations identified within the NICU infant cohort, which can be attributed to the very limited observations of these Blautia species and C. scindens in the overall dataset (Table S3). Indeed, among the 322 NICU infant samples analyzed, only B. luti and B. wexlerae were observed at all, and only in 5 (1.6%) and 2 (0.6%) samples, respectively, which precluded their evaluation with the CCREPE method.

While microbiome profiling through 16S rRNA gene sequencing is unlikely to replace existing methods for routine diagnosis of CDI, sequence-based assessment of C. difficile levels in the context of microbiota profiling rather than presence alone may prove valuable in surveillance of C. difficile in patient populations, prediction of disease outcome, or the development of new therapies for CDI. Although our study is limited to 16S rRNA gene-based identification of C. difficile and cannot predict whether a strain produces toxin or carries a functional pathogenicity locus,45 consideration for accurate identification of C. difficile and related members may be useful in assessing clinical outcomes of new microbial therapies that rely on 16S rRNA gene sequencing to validate recovery of the microbiota.

Methods

Validation of Resphera Insight for identification of C. difficile

Whole-genome shotgun sequence datasets available from (i) The Wellcome Trust Sanger Institute and (ii) The University of Maryland Institute for Genome Sciences designated as novel C. difficile isolates were downloaded from the NCBI Sequence Read Archive (see Table S1 for accessions), trimmed for quality using Trimmomatic46 and assembled into contigs using Minia.47 Contigs containing portions of 16S rRNA genes were identified using BLASTN48 and extracted for amplicon simulations. For each isolate, we subsequently simulated 16S rRNA amplicon sequence reads (10,000 per isolate) from the V4 region (the primary amplicon region selected in the real datasets) with a random nucleotide error rate of 0.5%. The Diagnostic True Positive Rate was computed as the percentage of sequences unambiguously assigned by Resphera Insight to C. difficile.

For false positive assessment, simulated V4 sequences were generated from reference 16S rRNA genes for 22 unique species within the Clostridium XI cluster (10,000 per species, 0.5% nucleotide error rate). False positives were defined as unambiguous assignments to C. difficile.


Processing of 16S rRNA gene sequence datasets

Raw 16S rRNA gene sequence datasets were processed as follows: Raw overlapping paired-end reads were merged into consensus fragments by FLASH49 requiring a minimum 20 bp overlap with 5% maximum mismatch density, and subsequently filtered for quality (targeting error rates < 1%) and length (minimum 200 bp) using Trimmomatic46 and QIIME.50 Spurious hits to the PhiX control genome were identified using BLASTN and removed. Sequences were then trimmed of their associated primers, evaluated for chimeras with UCLUST (de novo mode),51 and screened for human-associated contaminants using Bowtie252 searches of NCBI Homo sapiens Annotation Release 106. Mitochondrial contaminants were detected and filtered using the RDP classifier53 with a confidence threshold of 50%, and passing high-quality 16S rRNA gene sequences were subsequently assigned to a high-resolution taxonomic lineage using Resphera Insight (Baltimore, MD).18,19,20,54,55 Briefly, the method relies on (i) a manually curated 16S rRNA gene database including 11,000 unique species and (ii) a hybrid global-local alignment strategy to assign sequences a species-level taxonomic lineage. While the method attempts to achieve species-level resolution, if the internal statistical model indicates uncertainty in final species membership, the tool minimizes false positives by providing “ambiguous assignments” i.e., a list of species reflecting all relevant candidates. For example, if a 16S rRNA gene fragment is ambiguous between Veillonella atypica and Veillonella dispar, the algorithm will provide the ambiguous assignment: “Veillonella_atypica:Veillonella_dispar.”


Statistical analyses

Correlations between C. difficile and other species were computed using CCREPE (v.1.10.0)24 (http://huttenhower.sph.harvard.edu/ccrepe). CCREPE (Compositionality Corrected by REnormalization and PErmutation) utilizes an N-dimensional extension of the checkerboard score particularly suited to similarity score calculations between compositions derived from ecological relative abundance measurements of co-occurrence or co-exclusion. Two sample statistical comparisons utilized the Mann-Whitney U test unless otherwise noted.

In silico evaluation for species identified in CCREPE analysis

For single species reported in CCREPE correlation analysis, we simulated noisy 16S rRNA gene sequences (V4 region; 0.5% error rate; 1000 seqs per species), and calculated the frequency of (1) assignments that included the correct species (allowing for ambiguous assignments), (2) unambiguous assignments to the correct species, and (iii) mis-assignments that did not include the correct species (Table S4).


Ethics approvals and consent to participate

IRB approval and patient consent statements from each study: Recurrent CDI (Seekatz et al.10)—All subjects signed written consent to participate in this study. This study was approved by the University of Michigan Institutional Review Board (Study HUM33286; originally approved 8/26/2009).

Index CDI (Khanna et al.21)—We prospectively recruited 88 patients (median age 52.7 years, interquartile range 36.9–65.1; 60.2% female) with their first CDI episode (from 3/2012–9/2013) as identified from the Clinical Microbiology Laboratory at Mayo Clinic, Rochester, Minnesota and collected an aliquot from the stool samples that led to the diagnosis. Clinical data including demographics, hospitalization status, concomitant medications, CDI severity, laboratory parameters, prior and concomitant antibiotic use, initial CDI treatment, treatment response and recurrent CDI were obtained by a review of the electronic medical record.

NICU Infants (Zhou et al.23)—Samples were collected following a protocol that was approved by the Partner’ s Human Research Committee (IRB) for Brigham and Women’ s Hospital. All study procedures were approved by the IRBs at both Brigham and Women’ s Hospital in Boston, MA and at The Genome Institute in St. Louis, MO. The IRB deemed this study to be of minimal risk with no interaction and no intervention with human subjects and thus, was exempt from consent.

Infant Longitudinal (Davis et al.16)—The study was approved by the TechLab Institutional Review Board and included informed consent obtained from the mother.

FMT (Seekatz et al.9)—Informed consent was received from all participants under an approved Institutional Review Board (IRB) protocol at Essentia Health Duluth Clinic (IRB no. SMDC-09068; principal investigator, Timothy Rubin, FDA Investigational New Drug [IND] no. 15460).

Healthy Controls (Seekatz et al. submitted)—All subjects signed written consent to participate in this study. This study was approved by the University of Michigan Institutional Review Board (Study HUM33286; originally approved 8/26/2009).


Data availability

NCBI BioProject accessions of publicly available 16S rRNA gene sequence datasets used in this study: PRJNA307992, PRJNA342347, PRJNA264177, PRJNA331150, PRJNA238042, and PRJNA386260 (Table S2).

Additional Information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.

    Leffler, D. A. & Lamont, J. T. Clostridium difficile Infection. N. Engl. J. Med. 373, 287–288 (2015).

 

  • 2.

    Lessa, F. C. et al. Burden of Clostridium difficile infection in the United States. N. Engl. J. Med. 372, 825–834 (2015).

  • 3.

    Surawicz, C. M. et al. Guidelines for diagnosis, treatment, and prevention of Clostridium difficile infections. Am. J. Gastroenterol. 108, 478–498 (2013).

  • 4.

    Pepin, J. et al. Increasing risk of relapse after treatment of Clostridium difficile colitis in Quebec, Canada. Clin. Infect. Dis. 40, 1591–1597 (2005).

  • 5.

    Vincent, Y., Manji, A., Gregory-Miller, K. & Lee, C. A review of management of Clostridium difficile Infection: primary and recurrence. Antibiotics 4, 411–423 (2015).

  • 6.

    Seekatz, A. M. & Young, V. B. Clostridium difficile and the microbiota. J. Clin. Invest. 124, 4182–4189 (2014).

  • 7.

    Kelly, C. R. et al. Update on fecal microbiota transplantation 2015: indications, methodologies, mechanisms, and outlook. Gastroenterology 149, 223–237 (2015).

  • 8.

    Lynch, S. V. & Pedersen, O. The human intestinal microbiome in health and disease. N. Engl. J. Med. 375, 2369–2379 (2016).

  • 9.

    Seekatz, A. M. et al. Recovery of the gut microbiome following fecal microbiota transplantation. MBio 5, e00893–00814 (2014).

  • 10.

    Seekatz, A. M., Rao, K., Santhosh, K. & Young, V. B. Dynamics of the fecal microbiome in patients with recurrent and nonrecurrent Clostridium difficile infection. Genome Med. 8, 47 (2016).

  • 11.

    Seekatz, A. M. et al. Fecal microbiota transplantation eliminates Clostridium difficile in a murine model of relapsing disease. Infect. Immun. 83, 3838–3846 (2015).

  • 12.

    Zackular, J. P. et al. Dietary zinc alters the microbiota and decreases resistance to Clostridium difficile infection. Nat. Med. 22, 1330–1334 (2016).

  • 13.

    Theriot, C. M. et al. Antibiotic-induced shifts in the mouse gut microbiome and metabolome increase susceptibility to Clostridium difficile infection. Nat. Commun. 5, 3114 (2014).

  • 14.

    Weingarden, A. R. et al. Microbiota transplantation restores normal fecal bile acid composition in recurrent Clostridium difficile infection. Am. J. Physiol. Gastrointest. Liver Physiol. 306, G310–G319 (2014).

  • 15.

    Buffie, C. G. et al. Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile. Nature 517, 205–208 (2015).

  • 16.

    Davis, M. Y., Zhang, H., Brannan, L. E., Carman, R. J. & Boone, J. H. Rapid change of fecal microbiome and disappearance of Clostridium difficile in a colonized infant after transition from breast milk to cow milk. Microbiome 4, 53 (2016).

  • 17.

    Schubert, A. M., Sinani, H. & Schloss, P. D. Antibiotic-induced alterations of the murine gut microbiota and subsequent effects on colonization resistance against Clostridium difficile. MBio 6, e00974 (2015).

  • 18.

    Ottesen, A. et al. Enrichment dynamics of Listeria monocytogenes and the associated microbiome from naturally contaminated ice cream linked to a listeriosis outbreak. BMC Microbiol. 16, 275 (2016).

  • 19.

    Daquigan, N., Grim, C. J., White, J. R., Hanes, D. E. & Jarvis, K. G. Early recovery of Salmonella from food using a 6-hour non-selective pre-enrichment and reformulation of tetrathionate broth. Front. Microbiol. 7, 2103 (2016).

  • 20.

    Grim, C. J. et al. High-resolution microbiome profiling for detection and tracking of Salmonella enterica. Front. Microbiol. 8, 1587 (2017).

  • 21.

    Khanna, S. et al. Gut microbiome predictors of treatment response and recurrence in primary Clostridium difficile infection. Aliment. Pharmacol. Ther. 44, 715–727 (2016).

  • 22.

    Cohen, S. H. et al. Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the society for healthcare epidemiology of America (SHEA) and the infectious diseases society of America (IDSA). Infect. Control Hosp. Epidemiol. 31, 431–455 (2010).

  • 23.

    Zhou, Y. et al. Longitudinal analysis of the premature infant intestinal microbiome prior to necrotizing enterocolitis: a case-control study. PLoS One 10, e0118632 (2015).

  • 24.

    Gevers, D. et al. The treatment-naive microbiome in new-onset Crohn’s disease. Cell. Host. Microbe 15, 382–392 (2014).

  • 25.

    Furuya-Kanamori, L. et al. Asymptomatic Clostridium difficile colonization: epidemiology and clinical implications. BMC Infect. Dis. 15, 516 (2015).

  • 26.

    McNamara, S. E. et al. Carriage of Clostridium difficile and other enteric pathogens among a 4-H avocational cohort. Zoonoses Public Health 58, 192–199 (2011).

  • 27.

    Miyajima, F. et al. Characterisation and carriage ratio of Clostridium difficile strains isolated from a community-dwelling elderly population in the United Kingdom. PLoS One 6, e22804 (2011).

  • 28.

    Ozaki, E. et al. Clostridium difficile colonization in healthy adults: transient colonization and correlation with enterococcal colonization. J. Med. Microbiol. 53, 167–172 (2004).

  • 29.

    Rousseau, C. et al. Clostridium difficile carriage in healthy infants in the community: a potential reservoir for pathogenic strains. Clin. Infect. Dis. 55, 1209–1215 (2012).

  • 30.

    Schutze, G. E. & Willoughby, R. E. Committee on infectious diseases and American academy of pediatrics. Clostridium difficile infection in infants and children. Pediatrics 131, 196–200 (2013).

  • 31.

    Kim, J. et al. Epidemiological features of Clostridium difficile-associated disease among inpatients at children’s hospitals in the United States, 2001–2006. Pediatrics 122, 1266–1270 (2008).

  • 32.

    Cerquetti, M., Luzzi, I., Caprioli, A., Sebastianelli, A. & Mastrantonio, P. Role of Clostridium difficile in childhood diarrhea. Pediatr. Infect. Dis. J. 14, 598–603 (1995).

  • 33.

    Stoesser, N. et al. Epidemiology of Clostridium difficile in infants in Oxfordshire, UK: Risk factors for colonization and carriage, and genetic overlap with regional C. difficile infection strains. PLoS One 12, e0182307 (2017).

  • 34.

    Chang, T. W., Sullivan, N. M. & Wilkins, T. D. Insusceptibility of fetal intestinal mucosa and fetal cells to Clostridium difficile toxins. Zhongguo Yao Li Xue Bao 7, 448–453 (1986).

  • 35.

    Eglow, R. et al. Diminished Clostridium difficile toxin A sensitivity in newborn rabbit ileum is associated with decreased toxin A receptor. J. Clin. Invest. 90, 822–829 (1992).

  • 36.

    Kuiper, G. A. et al. Clostridium difficile infections in young infants: case presentations and literature review. IDCases 10, 7–11 (2017).

  • 37.

    Nicholson, M. R., Thomsen, I. P. & Edwards, K. M. Controversies surrounding Clostridium difficile infection ininfants and young children. Children. 1, 40–47 (2014).

  • 38.

    El Feghaly, R. E., Stauber, J. L., Tarr, P. I. & Haslam, D. B. Intestinal inflammatory biomarkers and outcome in pediatric Clostridium difficile infections. J. Pediatr. 163, 1697–1704 (2013).

  • 39.

    Wilson, K. H. & Perini, F. Role of competition for nutrients in suppression of Clostridium difficile by the colonic microflora. Infect. Immun. 56, 2610–2614 (1988).

  • 40.

    Baumler, A. J. & Sperandio, V. Interactions between the microbiota and pathogenic bacteria in the gut. Nature 535, 85–93 (2016).

  • 41.

    Greathouse, K. L., Harris, C. C. & Bultman, S. J. Dysfunctional families: Clostridium scindens and secondary bile acids inhibit the growth of Clostridium difficile. Cell. Metab. 21, 9–10 (2015).

  • 42.

    Ridlon, J. M., Alves, J. M., Hylemon, P. B. & Bajaj, J. S. Cirrhosis, bile acids and gut microbiota: unraveling a complex relationship. Gut Microbes 4, 382–387 (2013).

  • 43.

    Kakiyama, G. et al. Modulation of the fecal bile acid profile by gut microbiota in cirrhosis. J. Hepatol. 58, 949–955 (2013).

  • 44.

    Theriot, C. M., Bowman, A. A. & Young, V. B. Antibiotic-induced alterations of the gut microbiota alter secondary bile acid production and allow for Clostridium difficile spore germination and outgrowth in the large intestine. mSphere 1, e00045-15 (2016).

  • 45.

    Natarajan, M., Walk, S. T., Young, V. B. & Aronoff, D. M. A clinical and epidemiological review of non-toxigenic Clostridium difficile. Anaerobe 22, 1–5 (2013).

  • 46.

    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

  • 47.

    Chikhi, R. & Rizk, G. Space-efficient and exact de Bruijn graph representation based on a Bloom filter. Algorithms Mol. Biol. 8, 22 (2013).

  • 48.

    Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997).

  • 49.

    Magoc, T. & Salzberg, S. L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).

  • 50.

    Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7, 335–336 (2010).

  • 51.

    Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).

  • 52.

    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

  • 53.

    Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).

  • 54.

    Abernethy, M. G. et al. Urinary microbiome and cytokine levels in women with interstitial cystitis. Obstet. Gynecol. 129, 500–506 (2017).

  • 55.

    Guerrero-Preston, R. et al. High-resolution microbiome profiling uncovers Fusobacterium nucleatum, Lactobacillus gasseri/johnsonii, and Lactobacillus vaginalis associated to oral and oropharyngeal cancer in saliva from HPV positive and HPV negative patients treated with surgery and chemo-radiation. Oncotarget. https://doi.org/10.18632/oncotarget.20677 (2017).

 

Acknowledgements

We thank Cynthia Sears, Karen Carroll, and David Cook for helpful suggestions on this work. This work was supported in part by the ERIN CRC (Enteric Research Investigative Network Cooperative Research Center), (U19AI09087, NIAID), awarded to V.B.Y. A.M.S. supported by the National Center for Advancing Translational Sciences (UL1TR000433).

To review the article in its entirety please click on the following link:

https://www.nature.com/articles/s41522-017-0043-0

Learn More About Clostridium difficile (C.diff., C.difficile) infection and Recurrent CDI Clinical Trials In Progress

 

 

 

The C Diff Foundation has implemented a global campaign to raise awareness of Clostridium difficile infection (C.difficile) clinical trials, clinical studies, clinical research and observational studies evaluating interventions for C. difficile prevention, treatments, and environmental safety.

In the USA: Nearly half a million Americans suffer from Clostridium difficile (C. diff.) infections in a single year according to a study released in 2015 by the Centers for Disease Control and Prevention (CDC). Approximately 29,000 patients died within 30 days of the initial diagnosis of C. difficile. Of those, about 15,000 deaths were estimated to be directly attributable to C. difficile infections making C. difficile a very important cause of infectious disease death in the United States.

“Clostridium difficile infections are not only the most common cause of healthcare-acquired infections in the United States but also very common in the community in younger patients who previously were thought to be less susceptible to C. difficile. The rate of recurrent C. difficile infections is increasing tremendously and this increase is higher than the rate of primary C. difficile infections,” stated Sahil Khanna, MD, Assistant Professor of Medicine Division of Gastroenterology and Hepatology, Director of the C. difficile Clinic, Fecal Microbiota Transplantation program and C. difficile related Clinical Trials, Mayo Clinic, Rochester, MN.

Dr. Khanna also added, “It is imperative and important for clinical trials to be done to advance the development of new treatments, new medications, and new ways to prevent and treat Clostridium difficile infections.”

Individuals volunteer to participate in clinical trials in hopes of improving their own health, to access treatments that might not be available otherwise, often because they are new and not yet widely available. They help others by contributing to advances in medicine. There can also be potential risks participating in clinical trials and clinical studies. All of the known risks associated with a particular trial and or study will be discussed during the informed consent process. It will be thoroughly explained in the informed consent document that a volunteer will receive from the research staff prior to participating in any study.

To learn more about clinical research (e.g., Clostridium difficile, C.difficile) visit the U.S. Food and Drug Administration http://www.fda.gov or telephone 1-800-835-4709, The National Institutes of Health (NIH) http://www.nih.gov and ClinicalTrials.gov.

“Clinical trials are vital to improving our knowledge about how best to prevent and treat C. difficile infections. Informing patients of clinical trials is important, and in recent years several clinical trials have led to significant improvements in the treatments available for patients with C. difficile infections,” stated Mark Wilcox, MD, FRCPath, Consultant Microbiologist, Head of Microbiology and Academic Lead of Pathology Leeds Teaching Hospitals, Professor of Medical Microbiology University of Leeds Institute of Biomedical and Clinical Sciences, Lead on Clostridium difficile for Public Health England, UK.

About the U.S. Food and Drug Administration (FDA):
The FDA is responsible for protecting the public health by assuring that foods are safe, wholesome, sanitary and properly labeled; ensuring that human and veterinary drug, and vaccines and other biological products and medical devices intended for human use are safe and effective. FDA’s responsibilities extend to the 50 United States, the District of Columbia, Puerto Rico, Guam, the Virgin Islands, American Samoa, and other U.S. territories and possessions.

About the National Institutes of Health (NIH):
The National Institutes of Health (NIH), a part of the U.S. Department of Health and Human Services, is the nation’s medical research agency making important discoveries that improve health and save lives.

About ClinicalTrials.gov
ClinicalTrials.gov is a Web-based resource that provides patients, their family members, health care professionals, researchers, and the public with easy access to information on publicly and privately supported clinical studies on a wide range of diseases and conditions.

Rebiotix Announces Expansion of Phase 1 Study For Prevention of Recurrent C.diff. Infection Oral Capsule Microbiota Product RBX7455

Rebiotix Announces Expansion of Phase 1 Trial of the Company’s Oral
Capsule Microbiota Product, RBX7455, Following Successful Completion of
Initial Study Arms

Additional cohorts to examine potential of reduced dosing regimens of RBX7455 for the prevention of recurrent Clostridium difficile infection

Rebiotix Inc., a clinical-stage microbiome company
focused on harnessing the power of the human microbiome to treat challenging diseases, announced on November 30, 2017
an expansion of the investigator sponsored Phase 1 study of RBX7455 for the prevention of  recurrent Clostridium difficile (C. diff.) infection. The expansion follows the successful completion of the study’s two initial cohorts and is intended to explore reduced dosing regimens of RBX7455 in two new treatment arms. RBX7455 is a lyophilized, non-frozen oral capsule formulation of Rebiotix’s Microbiota Restoration Therapy™ (MRT), a standardized, stabilized drug technology that is designed to rehabilitate the human microbiome by delivering a broad spectrum of live microbes into a patient’s  intestinal tract via a ready-to-use and easy-to-administer format.
“Expansion of the Phase 1 study is a key advancement in the development of RBX7455 as it provides an opportunity to explore the potential efficacy of reduced dosing regimens of our oral capsule product in the prevention of recurrent C. diff. infection,” stated Lee Jones, president and CEO of Rebiotix. “RBX7455 is a ground-breaking product in that its oral capsule design is the first in the microbiome industry not requiring storage in frozen conditions. As such, patients are able to administer RBX7455 at home as they would a typical oral capsule medication, which potentially makes RBX7455 ideally suited for diseases where chronic or repeat dosing is required.”
The Phase 1 study of RBX7455 is an investigator sponsored, prospective, single center, proof of concept dosing study of RBX7455 for the prevention of recurrent C. diff. infection. The first two arms enrolled 10 patients per arm (20 total). The expansion of the Phase 1 study adds two additional arms, which will enroll approximately 10 patients per arm (20 total) with reduced dosing regimens from the 2
first two arms. Rebiotix expects data from the first two cohorts of the Phase 1 study of RBX7455 to be released publicly by mid-2018.
In addition to the expanded Phase 1 study of RBX7455, Rebiotix’s clinical development pipeline is highlighted by the company’s ongoing Phase 3 clinical trial of RBX2660 for the prevention of recurrent C. diff. infection. RBX2660 is the first and only microbiome drug to be tested in three separate Phase 2 trials, with more than 300 subjects having been treated with the microbial therapy.
Recently, Rebiotix announced the presentation of research from the RBX2660 Phase 2 program demonstrating measurable evidence of the drug’s rehabilitative effect on the human microbiome and the potential advantages of its broad consortia design.
Ms. Jones continued, “We look forward to the continued progress of the RBX7455 Phase 1 study as well as our Phase 3 study of RBX2660, our lead microbiome drug candidate. Importantly, since both drugs were developed with our MRT platform, we can leverage knowledge from the extensive RBX2660 clinical program, as well as research into the drug’s rehabilitative impact on the gut microbiome, to inform and expedite the development of RBX7455.”
About Rebiotix Inc.
Rebiotix Inc. is a late-stage clinical microbiome company focused on harnessing the power of the human microbiome to revolutionize the treatment of challenging diseases. Rebiotix possesses a deep and diverse clinical pipeline, with its lead drug candidate, RBX2660, in Phase 3 clinical development for the prevention of recurrent Clostridium difficile (C. diff.) infection. RBX2660 has been granted Fast Track status, Orphan Drug and Breakthrough Therapy designation from the FDA for its potential to prevent recurrent C. diff. infection.
Rebiotix’s clinical pipeline also features RBX7455, a lyophilized nonfrozen,
oral capsule formulation, which is currently the subject of an investigator-sponsored Phase 1 trial for the prevention of recurrent C. diff. infection. In addition, Rebiotix is targeting several other disease states with drug products built on its pioneering Microbiota Restoration TherapyTM (MRT) platform.
MRT is a standardized, stabilized drug technology that is designed to rehabilitate the human microbiome by delivering a broad consortium of live microbes into a patient’s intestinal tract via a ready – to-use and easy-to-administer format. For more information on Rebiotix and its pipeline of human microbiome-directed therapies, visit www.rebiotix.com

Minnesota Has Declared November “C. difficile Infection Awareness Month

 

 

 

 

http://www.clipsyndicate.com/video/play/7172019

According to research, C. Diff is the most common infection in U.S. hospitals within the last decade.

The state of Minnesota has declared November C. difficile Infection Awareness Month.” According to research, C. Diff is the most common infection in U.S. hospitals within the last decade.

Doctors at Mayo Clinic want people to know that they can get the infection even outside of hospitals. They also say once you get it, it’s easier to get it each time.

Dr. Sahil Khanna said ways to prevent C. diff is to wash hands and avoid unnecessary antibiotics.

He said Mayo Clinic is also studying whether or not there could be a vaccination for C. Diff.

“So there’s a large multi-center study that’s going on right now in people who may be at risk for C. Diff infection,” Khanna said. “So if you’ve been to the hospital, if you’ve received antibiotics, those patients can be enrolled in a vaccine study to see if this vaccine would prevent C. Diff from happening.”

Mayo Clinic is also working with Minnesota-based company Rebiotix on another form of treatment for the infection where people can simply ingest a tablet.

“Newer studies are being derived where you can actually take material from donor stool, process donor stool in a lab, and derive all the good bacteria that you need from the donor stool and put them in capsule form,” Khanna said.

Khanna said this capsule-based treatment has more advantages than a colonoscopy-based treatment that is currently being used to treat C. Diff.